VehicleRental / gen5
Viewer
!new RentalOffice('office5')
!office5.name := 'Highland Rentals'
!office5.number := 505
!office5.address := '456 Highland Ave, Anchorage, AK'
!new Truck('truck9')
!truck9.id := 509
!truck9.registrationState := #AK
!truck9.licensePlateNumber := 'AK-TRK-9012'
!truck9.vehicleTypeCode := #TRUCK
!truck9.registrationLastMaintenanceDate := Date('2023-02-05')
!truck9.expirationDate := Date('2024-02-05')
!truck9.odometerReading := 25000
!truck9.gasTankCapacity := 29.5
!truck9.workingRadio := true
!truck9.mileage := 19
!new Individual('individual5')
!individual5.name := 'Samantha Green'
!individual5.address := '101 Maple St, Fairbanks, AK'
!individual5.poorRisk := false
!individual5.homePhone := '555-5678'
!individual5.driverLicenseState := #AK
!individual5.driverLicenseNumber := 50607080
!individual5.driverLicenseExpirationDate := Date('2025-06-20')
!new RentalAgreement('agreement9')
!agreement9.number := 3009
!agreement9.rentalDate := Date('2023-10-22')
!agreement9.anticipatedDuration := 5
!agreement9.depositPaid := 175.0
!agreement9.quotedDailyRate := 65.00
!agreement9.quotedRatePerMile := 0.55
!new Truck('truck10')
!truck10.id := 510
!truck10.registrationState := #AZ
!truck10.licensePlateNumber := 'AZ-TRK-3456'
!truck10.vehicleTypeCode := #COVERED_TRAILER
!truck10.registrationLastMaintenanceDate := Date('2023-03-12')
!truck10.expirationDate := Date('2025-03-12')
!truck10.odometerReading := 30000
!truck10.gasTankCapacity := 32.0
!truck10.workingRadio := false
!truck10.mileage := 17
!new Company('company5')
!company5.name := 'Heavy Haulers'
!company5.address := '909 Transport Rd, Tucson, AZ'
!company5.poorRisk := false
!company5.idNumber := 901234
!new RentalAgreement('agreement10')
!agreement10.number := 3010
!agreement10.rentalDate := Date('2023-11-01')
!agreement10.anticipatedDuration := 15
!agreement10.depositPaid := 600.0
!agreement10.quotedDailyRate := 85.00
!agreement10.quotedRatePerMile := 0.75
!insert (office5, truck9) into RentalOfficeVehicle
!insert (office5, truck10) into RentalOfficeVehicle
!insert (office5, agreement9) into RentalOfficeRentalAgreementOrigin
!insert (office5, agreement9) into RentalOfficeRentalAgreementDrop
!insert (office5, agreement10) into RentalOfficeRentalAgreementOrigin
!insert (office5, agreement10) into RentalOfficeRentalAgreementDrop
!insert (agreement9, truck9) into RentalAgreementVehicle
!insert (agreement9, individual5) into RentalAgreementCustomer
!insert (agreement10, truck10) into RentalAgreementVehicle
!insert (agreement10, company5) into RentalAgreementCustomer model VehicleRental
dataType Date
operations
Date(date : String)
end
enum State {
AL,
AK,
AZ,
CA,
CO,
CT,
DE,
FL
}
enum VehicleTypeCode {
TRUCK,
TRUCK24,
TRUCK10,
COVERED_TRAILER,
OPEN_TRAILER
}
class RentalOffice
attributes
name : String
number : Integer
address : String
end
class Vehicle
attributes
id : Integer
registrationState : State
licensePlateNumber : String
vehicleTypeCode : VehicleTypeCode
registrationLastMaintenanceDate : Date
expirationDate : Date
end
class RentalAgreement
attributes
number : Integer
rentalDate : Date
anticipatedDuration : Integer
depositPaid : Real
quotedDailyRate : Real
quotedRatePerMile : Real
end
class Truck < Vehicle
attributes
odometerReading : Integer
gasTankCapacity : Real
workingRadio : Boolean
mileage : Integer
end
abstract class Customer
attributes
name : String
address : String
poorRisk : Boolean
end
class Individual < Customer
attributes
homePhone : String
driverLicenseState : State
driverLicenseNumber : Integer
driverLicenseExpirationDate : Date
end
class Company < Customer
attributes
idNumber : Integer
end
association RentalOfficeVehicle between
RentalOffice [1] role homeOffice
Vehicle [*]
end
association RentalOfficeRentalAgreementOrigin between
RentalOffice [1] role originatingRentalOffice
RentalAgreement [*] role originatingAgreement
end
association RentalOfficeRentalAgreementDrop between
RentalOffice [1] role droppoffRentalOffice
RentalAgreement [*] role dropoffAgreement
end
association RentalAgreementVehicle between
RentalAgreement [*]
Vehicle [1]
end
association RentalAgreementCustomer between
RentalAgreement [*]
Customer [1]
end
constraints
context Truck inv positiveGasTankCapacity:
self.gasTankCapacity >= 0
context Truck inv positiveMileage:
self.mileage >= 0
context RentalAgreement inv positiveDepositPaid:
self.depositPaid >= 0
context RentalAgreement inv positiveQuotedDailyRate:
self.quotedDailyRate >= 0
context RentalAgreement inv positiveQuotedRatePerMile:
self.quotedRatePerMile >= 0 Given a conceptual model expressed in the UML-based Specification Environment (USE), your task is to generate valid and realistic instances that conform to the provided model. <requirements> - Instances must be syntactically correct according to the USE syntax_reference. - Avoid unnecessary comments and output the instance in plain text (i.e., not markdown). - Make sure instances fulfill all the model's constraints, and that multiplicities, relationships, and attributes are valid and realistic. - Provide multiple instances with diverse data values and structure. </requirements> <syntax_reference> Here there is a snippet showing how to create objects and set values in the specific .soil language required: -- This is a comment example -- Primitive data types: -- Integer i.e. 1, 2, 3, etc. -- Real i.e. 1.0, 21.89, 322.05556, etc. -- Boolean i.e. true or false -- String i.e. 'Hello World' -- You can create instances with the following syntax: !new <instance type>('<instance name>') -- Example: !new Client('client1') !new Store('store4') -- You can assign values to attributes for a created instance with the following syntax: !<instance name>.<attribute name> := <value> -- Example for different data types: !client1.clientId := 1 -- For Integer !client1.balance := 1123.45 -- For Real !client1.name := 'John' -- For Strings !store4.available := true -- For Boolean -- You can create associations between instances with the following syntax: !insert (<instance name1>, <instance name2>) into <association name> -- Example: !insert (client1, store4) into ClientStore -- Custom data types usage: -- dataType Location -- operations -- Location(x : Real, y : Real) -- some other operations -- end -- You can create custom data types by calling the constructor directly; in this case, the constructor of Location requires two arguments: x and y of type Real. So it can be used as follows: !store4.location := Location(14.0, 289.0) -- Enums usage: -- enum Type { Clothes, Shoes } -- Can be used as follows: !store4.type := #Clothes </syntax_reference> Please generate another instance that is structurally and semantically different from the previous ones. <role>
You are an expert software and system modeler. You are able to assess the semantic quality of object models that have been created to conform to a domain model. The models are defined in USE (UML-based Specification Environment) and OCL (Object Constraint Language).
Your primary capability is "Semantic Reality Checking". You do not just check for syntactic correctness; you check for real-world plausibility and logical consistency within a given domain.
</role>
<context>
The user will provide two types of content:
1. **Domain Model (.use)**: A class diagram definition including classes, attributes, enums, relationships, multiplicities and roles.
2. **Object Model (.soil)**: An object model. This object model can be seen as a script composed of instructions for the creation of objects, relationships and setting attribute values (snapshot).
Your goal is to act as a judge to determine if the object model represents a **REALISTIC** scenario based on the domain model and common sense real-world logic.
</context>
<definitions>
- **Realistic**: The object model is syntactically correct AND semantically plausible (e.g., A 'Person' has an age between 0 and 120; a 'Car' has a positive price).
- **Unrealistic**: The object model contains contradictions, impossible physical values, or nonsensical relationships (e.g., A 'Person' is their own father; a 'Product' has a negative weight).
- **Doubtful**: You cannot determine whether the object model is realistic or not.
</definitions>
<instructions>
Follow this thinking process strictly before generating the final output:
1. **Analyze the Domain (.use)**: Understand the classes and what they represent in the real world.
2. **Analyze the Instances (.soil)**: Map the created objects to their classes. Look at the specific values assigned to attributes and the relationships created between objects.
3. **Evaluate Semantics**:
- Apply "Common Sense Knowledge" to the attribute values.
- Check cardinality and relationship logic beyond simple OCL constraints.
- Identify any outliers or logical fallacies.
4. **Determine Verdict**: Select one of the defined labels (Realistic/Unrealistic/Doubtful).
</instructions>
<constraints>
- **Tone**: Objective, Analytical, Technical.
- **Verbosity**: Low. Be direct.
- **Reasoning**: The "Why" section must be concise and specific, citing variable names, objects, or relationships when possible.
- Do not output the internal thinking process. Only output the final formatted result.
</constraints>
<output_format>
Structure your response exactly as follows:
**Response**: [Realistic | Unrealistic | Doubtful]
**Why**: [Concise explanation of your reasoning. If Unrealistic, specify the exact objects, values or relationships that break realism.]
</output_format>
<examples>
Example 1:
Input:
<domain_model>
class Person
attributes
age: Integer
end
class Pet
attributes
name: String
end
association Ownership between
Person [1] role owner
Pet [*] role pets
end
</domain_model>
<object_model>
!new Person('p1')
!p1.age := 250
!new Pet('pet1')
!pet1.name := 'Luna'
… 1.000 more pets creation …
!pet1000.name := 'Max'
!insert (p1, pet1) into Ownership
…1.000 more pets associated with p1 …
!insert (p1, pet1000) into Ownership
</object_model>
Output:
**Response**: Unrealistic
**Why**: The object 'p1' of class 'Person' has an age of 250, which exceeds the biologically plausible lifespan of a human. Although it is not plausible that 1 same person owns 1.000 pets.
Example 2:
Input:
<domain_model>
class Car
attributes
brand: String
end
class Person
attributes
name: String
end
association Ownership between
Person [1] role owner
Car [*] role cars
end
</domain_model>
<object_model>
!new Person('p1')
!p1.age := 19
!new Car('c1')
!c1.brand := 'Toyota'
!insert (p1, c1) into Ownership
</object_model>
Output:
**Response**: Realistic
**Why**: The object 'c1' has a valid, recognized real-world car brand assigned, and its plausible that a teenager has only one car.
Example 3:
Input:
<domain_model>
class Component
attributes
setting_val: Integer
config_mode: String
end
</domain_model>
<object_model>
!new Component('c1')
!c1.setting_val := 8080
!c1.config_mode := 'Legacy'
</object_model>
Output:
**Response**: Doubtful
**Why**: The class 'Component' and attribute 'setting_val' are generic and lack specific real-world semantic context. Without knowing what specific physical or software system this represents, it is impossible to determine if '8080' is a realistic value or an outlier.
</examples> <domain_model>
model VehicleRental
dataType Date
operations
Date(date : String)
end
enum State {
AL,
AK,
AZ,
CA,
CO,
CT,
DE,
FL
}
enum VehicleTypeCode {
TRUCK,
TRUCK24,
TRUCK10,
COVERED_TRAILER,
OPEN_TRAILER
}
class RentalOffice
attributes
name : String
number : Integer
address : String
end
class Vehicle
attributes
id : Integer
registrationState : State
licensePlateNumber : String
vehicleTypeCode : VehicleTypeCode
registrationLastMaintenanceDate : Date
expirationDate : Date
end
class RentalAgreement
attributes
number : Integer
rentalDate : Date
anticipatedDuration : Integer
depositPaid : Real
quotedDailyRate : Real
quotedRatePerMile : Real
end
class Truck < Vehicle
attributes
odometerReading : Integer
gasTankCapacity : Real
workingRadio : Boolean
mileage : Integer
end
abstract class Customer
attributes
name : String
address : String
poorRisk : Boolean
end
class Individual < Customer
attributes
homePhone : String
driverLicenseState : State
driverLicenseNumber : Integer
driverLicenseExpirationDate : Date
end
class Company < Customer
attributes
idNumber : Integer
end
association RentalOfficeVehicle between
RentalOffice [1] role homeOffice
Vehicle [*]
end
association RentalOfficeRentalAgreementOrigin between
RentalOffice [1] role originatingRentalOffice
RentalAgreement [*] role originatingAgreement
end
association RentalOfficeRentalAgreementDrop between
RentalOffice [1] role droppoffRentalOffice
RentalAgreement [*] role dropoffAgreement
end
association RentalAgreementVehicle between
RentalAgreement [*]
Vehicle [1]
end
association RentalAgreementCustomer between
RentalAgreement [*]
Customer [1]
end
constraints
context Truck inv positiveGasTankCapacity:
self.gasTankCapacity >= 0
context Truck inv positiveMileage:
self.mileage >= 0
context RentalAgreement inv positiveDepositPaid:
self.depositPaid >= 0
context RentalAgreement inv positiveQuotedDailyRate:
self.quotedDailyRate >= 0
context RentalAgreement inv positiveQuotedRatePerMile:
self.quotedRatePerMile >= 0
</domain_model>
<object_model>
!new RentalOffice('office5')
!office5.name := 'Highland Rentals'
!office5.number := 505
!office5.address := '456 Highland Ave, Anchorage, AK'
!new Truck('truck9')
!truck9.id := 509
!truck9.registrationState := #AK
!truck9.licensePlateNumber := 'AK-TRK-9012'
!truck9.vehicleTypeCode := #TRUCK
!truck9.registrationLastMaintenanceDate := Date('2023-02-05')
!truck9.expirationDate := Date('2024-02-05')
!truck9.odometerReading := 25000
!truck9.gasTankCapacity := 29.5
!truck9.workingRadio := true
!truck9.mileage := 19
!new Individual('individual5')
!individual5.name := 'Samantha Green'
!individual5.address := '101 Maple St, Fairbanks, AK'
!individual5.poorRisk := false
!individual5.homePhone := '555-5678'
!individual5.driverLicenseState := #AK
!individual5.driverLicenseNumber := 50607080
!individual5.driverLicenseExpirationDate := Date('2025-06-20')
!new RentalAgreement('agreement9')
!agreement9.number := 3009
!agreement9.rentalDate := Date('2023-10-22')
!agreement9.anticipatedDuration := 5
!agreement9.depositPaid := 175.0
!agreement9.quotedDailyRate := 65.00
!agreement9.quotedRatePerMile := 0.55
!new Truck('truck10')
!truck10.id := 510
!truck10.registrationState := #AZ
!truck10.licensePlateNumber := 'AZ-TRK-3456'
!truck10.vehicleTypeCode := #COVERED_TRAILER
!truck10.registrationLastMaintenanceDate := Date('2023-03-12')
!truck10.expirationDate := Date('2025-03-12')
!truck10.odometerReading := 30000
!truck10.gasTankCapacity := 32.0
!truck10.workingRadio := false
!truck10.mileage := 17
!new Company('company5')
!company5.name := 'Heavy Haulers'
!company5.address := '909 Transport Rd, Tucson, AZ'
!company5.poorRisk := false
!company5.idNumber := 901234
!new RentalAgreement('agreement10')
!agreement10.number := 3010
!agreement10.rentalDate := Date('2023-11-01')
!agreement10.anticipatedDuration := 15
!agreement10.depositPaid := 600.0
!agreement10.quotedDailyRate := 85.00
!agreement10.quotedRatePerMile := 0.75
!insert (office5, truck9) into RentalOfficeVehicle
!insert (office5, truck10) into RentalOfficeVehicle
!insert (office5, agreement9) into RentalOfficeRentalAgreementOrigin
!insert (office5, agreement9) into RentalOfficeRentalAgreementDrop
!insert (office5, agreement10) into RentalOfficeRentalAgreementOrigin
!insert (office5, agreement10) into RentalOfficeRentalAgreementDrop
!insert (agreement9, truck9) into RentalAgreementVehicle
!insert (agreement9, individual5) into RentalAgreementCustomer
!insert (agreement10, truck10) into RentalAgreementVehicle
!insert (agreement10, company5) into RentalAgreementCustomer
</object_model> LLM as a Judge
The object 'truck10' has a `vehicleTypeCode` of `#COVERED_TRAILER`, but it is instantiated as a `Truck` with a `gasTankCapacity` of 32.0 gallons and an `odometerReading`. In the real world, trailers are unpowered and do not have gas tanks or their own odometers.
Metrics
Stats
Stats Breakdown of the total cost and elapsed time for generating the instances. - Elapsed Time = Console Time (ie. Processing Time + API Calls)
- Cost = (input tokens * input price) + (output tokens * output price)
- Elapsed Time = Console Time (ie. Processing Time + API Calls)
- Cost = (input tokens * input price) + (output tokens * output price)
| Total Cost | $0.02 |
Validation
Validation Measures the correctness of the instantiation using the USE check function. - Syntax = 1 - (Total Number of syntax errors [use check] / Total Number of lines [instance])
- Multiplicities = 1 - (Total Number of multiplicities errors [use check] / Total Number of relationships ([instance] !insert))
- Invariants = 1 - (Total Number of invariants errors [use check] / Total Number of invariants ([model] constraints))
- Syntax = 1 - (Total Number of syntax errors [use check] / Total Number of lines [instance])
- Multiplicities = 1 - (Total Number of multiplicities errors [use check] / Total Number of relationships ([instance] !insert))
- Invariants = 1 - (Total Number of invariants errors [use check] / Total Number of invariants ([model] constraints))
| Syntax | 0/63 |
| Multiplicities | 0/10 |
| Invariants | 0/5 |
Diversity
Diversity Measures the variability of the generated instances. Attributes (NumericEquals, StringEquals, StringLv): It identifies how much the LLM repeats specific values versus generating unique data points across instances (100%: Diverse, 0%: Repetitive). We group all generated attributes into bags (numeric and string) and then perform pairwise comparisons between every element to obtain. Structure (GED): Measures the Graph Edit Distance (GED) similarity between instances. Distribution (Shannon): Measures the entropy and evenness (balanced distribution) of the generated enum values. - NumericEquals = Total number of numeric attribute pairs with different values / Total number of possible pairs (n * (n - 1) / 2)
- StringEquals = Total number of string attribute pairs that are NOT exactly identical / Total number of possible pairs (n * (n - 1) / 2)
- StringLv = Sum of (Levenshtein Distance(a, b) / max(length(a), length(b))) for all string pairs / Total number of possible pairs (n * (n - 1) / 2)
- GED = Similarity = 1 - (GED / (0.5 * (GED_to_empty_A + GED_to_empty_B))). 1 = red = identical graphs, <=0.5 = green = different graphs. We consider as edit operations: Nodes, Edges, Node_Labels and Edge_Labels [https://github.com/a-coman/ged]
- Shannon (Active) = Entropy / log2(Number of unique groups actually generated). Measures how evenly the generated values are distributed, considering only the categories the LLM actually used.
- Shannon (All) = Entropy / log2(Total number of valid groups defined in the model). Measures how evenly the generated values are distributed against the full spectrum of all possible valid options defined in the .use file.
- NumericEquals = Total number of numeric attribute pairs with different values / Total number of possible pairs (n * (n - 1) / 2)
- StringEquals = Total number of string attribute pairs that are NOT exactly identical / Total number of possible pairs (n * (n - 1) / 2)
- StringLv = Sum of (Levenshtein Distance(a, b) / max(length(a), length(b))) for all string pairs / Total number of possible pairs (n * (n - 1) / 2)
- GED = Similarity = 1 - (GED / (0.5 * (GED_to_empty_A + GED_to_empty_B))). 1 = red = identical graphs, <=0.5 = green = different graphs. We consider as edit operations: Nodes, Edges, Node_Labels and Edge_Labels [https://github.com/a-coman/ged]
- Shannon (Active) = Entropy / log2(Number of unique groups actually generated). Measures how evenly the generated values are distributed, considering only the categories the LLM actually used.
- Shannon (All) = Entropy / log2(Total number of valid groups defined in the model). Measures how evenly the generated values are distributed against the full spectrum of all possible valid options defined in the .use file.
| Numeric | 100.0% |
| String Equals | 100.0% |
| String LV | 88.7% |
| Shannon (Active) | 0.000 ± 0.000 |
| Shannon (All) | 0.000 ± 0.000 |
Coverage
Model Coverage Measures the breadth of the instantiation. It answers: "How much of the structural blueprint (the model) was used?" - Classes = Total Unique Classes instantiated (!new) in the .soil / Total Number of classes (class) in the model .use
- Attributes = Total Unique Attributes instantiated (!Class.Attribute or !set) in the .soil / Total Number of attributes (attributes) in the model .use
- Relationships = Total Unique Relationships instantiated (!insert) in the .soil / Total Number of relationships (association, composition, aggregation) in the model .use
- Classes = Total Unique Classes instantiated (!new) in the .soil / Total Number of classes (class) in the model .use
- Attributes = Total Unique Attributes instantiated (!Class.Attribute or !set) in the .soil / Total Number of attributes (attributes) in the model .use
- Relationships = Total Unique Relationships instantiated (!insert) in the .soil / Total Number of relationships (association, composition, aggregation) in the model .use
| Classes | 83.3% |
| Attributes | 83.3% |
| Relationships | 100.0% |
Uncovered Items 7
Instantiation
Instance Instantiation Measures the depth or density of the data. It answers: "Of the objects the LLM decided to create, how many of their available 'slots' did it fill?" - Classes = Total Number of classes (!new) in the instance / Total possible that could have been instantiated (infinity)
- Attributes = Total Number of attributes (!Class.Attribute or !set) in the instance / Total possible that could have been instantiated (sum(number of classes instantiated of that type * Class.Attributes))
- Relationships = Total Number of relationships (!insert) in the instance / Total possible that could have been instantiated (infinity)
- Classes = Total Number of classes (!new) in the instance / Total possible that could have been instantiated (infinity)
- Attributes = Total Number of attributes (!Class.Attribute or !set) in the instance / Total possible that could have been instantiated (sum(number of classes instantiated of that type * Class.Attributes))
- Relationships = Total Number of relationships (!insert) in the instance / Total possible that could have been instantiated (infinity)
| Classes | 7/∞ |
| Attributes | 46/46 |
| Relationships | 10/∞ |
Viewer
!new RentalOffice('officeSaltLakeCityDepot')
!officeSaltLakeCityDepot.name := 'Salt Lake City Depot'
!officeSaltLakeCityDepot.number := 505
!officeSaltLakeCityDepot.address := '789 Mountain View Rd, Salt Lake City, UT 84103'
!new Vehicle('coveredTrailer008')
!coveredTrailer008.id := 308
!coveredTrailer008.registrationState := #CO
!coveredTrailer008.licensePlateNumber := 'UT2468CT'
!coveredTrailer008.vehicleTypeCode := #COVERED_TRAILER
!coveredTrailer008.registrationLastMaintenanceDate := Date('2023-03-29')
!coveredTrailer008.expirationDate := Date('2024-03-28')
!new Truck('truck009')
!truck009.id := 309
!truck009.registrationState := #CO
!truck009.licensePlateNumber := 'WY1234TR'
!truck009.vehicleTypeCode := #TRUCK
!truck009.registrationLastMaintenanceDate := Date('2023-02-10')
!truck009.expirationDate := Date('2024-02-09')
!truck009.odometerReading := 25000
!truck009.gasTankCapacity := 21.5
!truck009.workingRadio := false
!truck009.mileage := 40000
!new Individual('individualEmmaJohnson')
!individualEmmaJohnson.name := 'Emma Johnson'
!individualEmmaJohnson.address := '81 Cowboy Way, Jackson, WY 83001'
!individualEmmaJohnson.poorRisk := false
!individualEmmaJohnson.homePhone := '307-555-7856'
!individualEmmaJohnson.driverLicenseState := #CO
!individualEmmaJohnson.driverLicenseNumber := 876543210
!individualEmmaJohnson.driverLicenseExpirationDate := Date('2026-01-21')
!new RentalAgreement('rentalAgreement5005')
!rentalAgreement5005.number := 5005
!rentalAgreement5005.rentalDate := Date('2024-03-03')
!rentalAgreement5005.anticipatedDuration := 10
!rentalAgreement5005.depositPaid := 300.0
!rentalAgreement5005.quotedDailyRate := 55.0
!rentalAgreement5005.quotedRatePerMile := 0.35
!insert (officeSaltLakeCityDepot, coveredTrailer008) into RentalOfficeVehicle
!insert (officeSaltLakeCityDepot, truck009) into RentalOfficeVehicle
!insert (officeSaltLakeCityDepot, rentalAgreement5005) into RentalOfficeRentalAgreementOrigin
!insert (officeSaltLakeCityDepot, rentalAgreement5005) into RentalOfficeRentalAgreementDrop
!insert (rentalAgreement5005, truck009) into RentalAgreementVehicle
!insert (rentalAgreement5005, individualEmmaJohnson) into RentalAgreementCustomer model VehicleRental
dataType Date
operations
Date(date : String)
end
enum State {
AL,
AK,
AZ,
CA,
CO,
CT,
DE,
FL
}
enum VehicleTypeCode {
TRUCK,
TRUCK24,
TRUCK10,
COVERED_TRAILER,
OPEN_TRAILER
}
class RentalOffice
attributes
name : String
number : Integer
address : String
end
class Vehicle
attributes
id : Integer
registrationState : State
licensePlateNumber : String
vehicleTypeCode : VehicleTypeCode
registrationLastMaintenanceDate : Date
expirationDate : Date
end
class RentalAgreement
attributes
number : Integer
rentalDate : Date
anticipatedDuration : Integer
depositPaid : Real
quotedDailyRate : Real
quotedRatePerMile : Real
end
class Truck < Vehicle
attributes
odometerReading : Integer
gasTankCapacity : Real
workingRadio : Boolean
mileage : Integer
end
abstract class Customer
attributes
name : String
address : String
poorRisk : Boolean
end
class Individual < Customer
attributes
homePhone : String
driverLicenseState : State
driverLicenseNumber : Integer
driverLicenseExpirationDate : Date
end
class Company < Customer
attributes
idNumber : Integer
end
association RentalOfficeVehicle between
RentalOffice [1] role homeOffice
Vehicle [*]
end
association RentalOfficeRentalAgreementOrigin between
RentalOffice [1] role originatingRentalOffice
RentalAgreement [*] role originatingAgreement
end
association RentalOfficeRentalAgreementDrop between
RentalOffice [1] role droppoffRentalOffice
RentalAgreement [*] role dropoffAgreement
end
association RentalAgreementVehicle between
RentalAgreement [*]
Vehicle [1]
end
association RentalAgreementCustomer between
RentalAgreement [*]
Customer [1]
end
constraints
context Truck inv positiveGasTankCapacity:
self.gasTankCapacity >= 0
context Truck inv positiveMileage:
self.mileage >= 0
context RentalAgreement inv positiveDepositPaid:
self.depositPaid >= 0
context RentalAgreement inv positiveQuotedDailyRate:
self.quotedDailyRate >= 0
context RentalAgreement inv positiveQuotedRatePerMile:
self.quotedRatePerMile >= 0 You are tasked with analyzing conceptual models represented as class diagrams and expressed in the UML-based specification environment using its native syntax. You must adhere to the following requirements: - Use very clear language. - Do not overexplain, be concise. - Multiplicities must be very clear and easy to understand. You should follow the structure and requirements below: ## Description Start by explaining the overall structure and purpose of the model. ### Components Break down the components of the model (i.e., classes and attributes), describing each, their type and purpose. ## Relationships Describe the relationships between the components of the model, dependencies and multiplicities (i.e., minimum and maximum number of instances of one class that can be associated with instances of another class). Describe the multiplicities at both ends of each association. ## Invariants Define the invariants that apply to the model (i.e., those constraints that must be fulfilled). Your task is to generate a complete and diverse instance, in plain English, for a given category and based on a provided conceptual model description. The instance must adhere to these requirements: - Be self-contained: Include all required attributes, relationships, and related entities in full detail. - Conform to the model: Fulfill the constraints, multiplicities, relationships, and attributes defined in the class diagram model. - Understand the context: Ensure that its attributes and relationships are relevant. - Avoid duplication of instances: Take into consideration those instances previously built to avoid redundancy. - Semantic diversity: From a semantic point of view, incorporate varied scenarios, including regional, linguistic, or cultural differences. - Structural diversity: Include instances with different numbers of elements, different numbers of relationships and complexity, and create varied examples by changing entity attributes. You are tasked with creating instances of a conceptual model in the UML-based Specification Environment (USE). You will receive: 1. The UML class diagram that the instance follows. 2. A sample syntax of instances creation. 3. A description of the instance that needs to be created. Your goal is to generate these instances based on the provided description, adhering strictly to these requirements: - The output must be in plain text, with no additional comments, descriptions, or explanations. - Ensure that the created instance adheres to the provided description. - Follow the syntax sample provided, without deviation. - Take into account previously created instances to avoid using duplicate naming. <role>
You are an expert software and system modeler. You are able to assess the semantic quality of object models that have been created to conform to a domain model. The models are defined in USE (UML-based Specification Environment) and OCL (Object Constraint Language).
Your primary capability is "Semantic Reality Checking". You do not just check for syntactic correctness; you check for real-world plausibility and logical consistency within a given domain.
</role>
<context>
The user will provide two types of content:
1. **Domain Model (.use)**: A class diagram definition including classes, attributes, enums, relationships, multiplicities and roles.
2. **Object Model (.soil)**: An object model. This object model can be seen as a script composed of instructions for the creation of objects, relationships and setting attribute values (snapshot).
Your goal is to act as a judge to determine if the object model represents a **REALISTIC** scenario based on the domain model and common sense real-world logic.
</context>
<definitions>
- **Realistic**: The object model is syntactically correct AND semantically plausible (e.g., A 'Person' has an age between 0 and 120; a 'Car' has a positive price).
- **Unrealistic**: The object model contains contradictions, impossible physical values, or nonsensical relationships (e.g., A 'Person' is their own father; a 'Product' has a negative weight).
- **Doubtful**: You cannot determine whether the object model is realistic or not.
</definitions>
<instructions>
Follow this thinking process strictly before generating the final output:
1. **Analyze the Domain (.use)**: Understand the classes and what they represent in the real world.
2. **Analyze the Instances (.soil)**: Map the created objects to their classes. Look at the specific values assigned to attributes and the relationships created between objects.
3. **Evaluate Semantics**:
- Apply "Common Sense Knowledge" to the attribute values.
- Check cardinality and relationship logic beyond simple OCL constraints.
- Identify any outliers or logical fallacies.
4. **Determine Verdict**: Select one of the defined labels (Realistic/Unrealistic/Doubtful).
</instructions>
<constraints>
- **Tone**: Objective, Analytical, Technical.
- **Verbosity**: Low. Be direct.
- **Reasoning**: The "Why" section must be concise and specific, citing variable names, objects, or relationships when possible.
- Do not output the internal thinking process. Only output the final formatted result.
</constraints>
<output_format>
Structure your response exactly as follows:
**Response**: [Realistic | Unrealistic | Doubtful]
**Why**: [Concise explanation of your reasoning. If Unrealistic, specify the exact objects, values or relationships that break realism.]
</output_format>
<examples>
Example 1:
Input:
<domain_model>
class Person
attributes
age: Integer
end
class Pet
attributes
name: String
end
association Ownership between
Person [1] role owner
Pet [*] role pets
end
</domain_model>
<object_model>
!new Person('p1')
!p1.age := 250
!new Pet('pet1')
!pet1.name := 'Luna'
… 1.000 more pets creation …
!pet1000.name := 'Max'
!insert (p1, pet1) into Ownership
…1.000 more pets associated with p1 …
!insert (p1, pet1000) into Ownership
</object_model>
Output:
**Response**: Unrealistic
**Why**: The object 'p1' of class 'Person' has an age of 250, which exceeds the biologically plausible lifespan of a human. Although it is not plausible that 1 same person owns 1.000 pets.
Example 2:
Input:
<domain_model>
class Car
attributes
brand: String
end
class Person
attributes
name: String
end
association Ownership between
Person [1] role owner
Car [*] role cars
end
</domain_model>
<object_model>
!new Person('p1')
!p1.age := 19
!new Car('c1')
!c1.brand := 'Toyota'
!insert (p1, c1) into Ownership
</object_model>
Output:
**Response**: Realistic
**Why**: The object 'c1' has a valid, recognized real-world car brand assigned, and its plausible that a teenager has only one car.
Example 3:
Input:
<domain_model>
class Component
attributes
setting_val: Integer
config_mode: String
end
</domain_model>
<object_model>
!new Component('c1')
!c1.setting_val := 8080
!c1.config_mode := 'Legacy'
</object_model>
Output:
**Response**: Doubtful
**Why**: The class 'Component' and attribute 'setting_val' are generic and lack specific real-world semantic context. Without knowing what specific physical or software system this represents, it is impossible to determine if '8080' is a realistic value or an outlier.
</examples> Analyze the following UML class diagram:
model VehicleRental
dataType Date
operations
Date(date : String)
end
enum State {
AL,
AK,
AZ,
CA,
CO,
CT,
DE,
FL
}
enum VehicleTypeCode {
TRUCK,
TRUCK24,
TRUCK10,
COVERED_TRAILER,
OPEN_TRAILER
}
class RentalOffice
attributes
name : String
number : Integer
address : String
end
class Vehicle
attributes
id : Integer
registrationState : State
licensePlateNumber : String
vehicleTypeCode : VehicleTypeCode
registrationLastMaintenanceDate : Date
expirationDate : Date
end
class RentalAgreement
attributes
number : Integer
rentalDate : Date
anticipatedDuration : Integer
depositPaid : Real
quotedDailyRate : Real
quotedRatePerMile : Real
end
class Truck < Vehicle
attributes
odometerReading : Integer
gasTankCapacity : Real
workingRadio : Boolean
mileage : Integer
end
abstract class Customer
attributes
name : String
address : String
poorRisk : Boolean
end
class Individual < Customer
attributes
homePhone : String
driverLicenseState : State
driverLicenseNumber : Integer
driverLicenseExpirationDate : Date
end
class Company < Customer
attributes
idNumber : Integer
end
association RentalOfficeVehicle between
RentalOffice [1] role homeOffice
Vehicle [*]
end
association RentalOfficeRentalAgreementOrigin between
RentalOffice [1] role originatingRentalOffice
RentalAgreement [*] role originatingAgreement
end
association RentalOfficeRentalAgreementDrop between
RentalOffice [1] role droppoffRentalOffice
RentalAgreement [*] role dropoffAgreement
end
association RentalAgreementVehicle between
RentalAgreement [*]
Vehicle [1]
end
association RentalAgreementCustomer between
RentalAgreement [*]
Customer [1]
end
constraints
context Truck inv positiveGasTankCapacity:
self.gasTankCapacity >= 0
context Truck inv positiveMileage:
self.mileage >= 0
context RentalAgreement inv positiveDepositPaid:
self.depositPaid >= 0
context RentalAgreement inv positiveQuotedDailyRate:
self.quotedDailyRate >= 0
context RentalAgreement inv positiveQuotedRatePerMile:
self.quotedRatePerMile >= 0 For the same category and model description, generate another instance that is structurally and semantically different from the previous ones Continue with the following description, creating the instance according to the syntax example and this specification:
## Baseline Instance: Rural Logistics Support Scenario
### Entities
1. **RentalOffice:**
- **Office Salt Lake City Depot**
- `name`: "Salt Lake City Depot"
- `number`: 505
- `address`: "789 Mountain View Rd, Salt Lake City, UT 84103"
2. **Vehicle:**
- **Covered Trailer 008**
- `id`: 308
- `registrationState`: UT (Utah)
- `licensePlateNumber`: "UT2468CT"
- `vehicleTypeCode`: COVERED_TRAILER
- `registrationLastMaintenanceDate`: "2023-03-29"
- `expirationDate`: "2024-03-28"
3. **Truck:**
- **Truck 009**
- `id`: 309
- `registrationState`: WY (Wyoming)
- `licensePlateNumber`: "WY1234TR"
- `vehicleTypeCode`: TRUCK
- `registrationLastMaintenanceDate`: "2023-02-10"
- `expirationDate`: "2024-02-09"
- `odometerReading`: 25000
- `gasTankCapacity`: 21.5 (in gallons)
- `workingRadio`: false
- `mileage`: 40000
4. **Customer:**
- **Individual: Emma Johnson**
- `name`: "Emma Johnson"
- `address`: "81 Cowboy Way, Jackson, WY 83001"
- `poorRisk`: false
- `homePhone`: "307-555-7856"
- `driverLicenseState`: WY (Wyoming)
- `driverLicenseNumber`: 876543210
- `driverLicenseExpirationDate`: "2026-01-21"
5. **RentalAgreement:**
- **Rental Agreement 5005**
- `number`: 5005
- `rentalDate`: "2024-03-03"
- `anticipatedDuration`: 10 (days)
- `depositPaid`: 300.0 (USD)
- `quotedDailyRate`: 55.0 (USD)
- `quotedRatePerMile`: 0.35 (USD per mile)
### Relationships
- **RentalOfficeVehicle:**
- **Office Salt Lake City Depot** manages **Covered Trailer 008**.
- **Office Salt Lake City Depot** manages **Truck 009**.
- **RentalOfficeRentalAgreementOrigin:**
- **Office Salt Lake City Depot** is the origin point for **Rental Agreement 5005**.
- **RentalOfficeRentalAgreementDrop:**
- **Office Salt Lake City Depot** serves as the drop-off location for **Rental Agreement 5005**.
- **RentalAgreementVehicle:**
- **Rental Agreement 5005** involves **Truck 009**.
- **RentalAgreementCustomer:**
- **Rental Agreement 5005** is associated with **Individual Emma Johnson**.
### Summary
In this scenario, Emma Johnson, an individual from Wyoming, rents a truck from the Salt Lake City Depot office. The truck, which has seen high mileage and has a non-functioning radio, reflects a vehicle typically used in rural logistics. The 10-day rental period for the truck, registered in Wyoming, is planned for rural deliveries, showcasing the need for vehicles that support logistics in less urbanized areas. This instance highlights the integration of rural state differences, individual customer interaction, and logistic-focused vehicle utilization in varied regional contexts. The last output is partially incorrect:
temp.soil> !coveredTrailer008.id := 308
temp.soil> !coveredTrailer008.registrationState := #UT
<input>:1:0: generation of expression `#UT' failed, with following error:
<input>:1:40: Undefined enumeration literal `UT'.
temp.soil> !truck009.id := 309
temp.soil> !truck009.registrationState := #WY
<input>:1:0: generation of expression `#WY' failed, with following error:
<input>:1:31: Undefined enumeration literal `WY'.
temp.soil> !individualEmmaJohnson.homePhone := '307-555-7856'
temp.soil> !individualEmmaJohnson.driverLicenseState := #WY
<input>:1:0: generation of expression `#WY' failed, with following error:
<input>:1:45: Undefined enumeration literal `WY'.
Please provide the complete output corrected The last output is partially incorrect:
temp.soil> !coveredTrailer008.id := 308
temp.soil> !coveredTrailer008.registrationState := #UT
<input>:1:0: generation of expression `#UT' failed, with following error:
<input>:1:40: Undefined enumeration literal `UT'.
temp.soil> !truck009.id := 309
temp.soil> !truck009.registrationState := #UT
<input>:1:0: generation of expression `#UT' failed, with following error:
<input>:1:31: Undefined enumeration literal `UT'.
temp.soil> !individualEmmaJohnson.homePhone := '307-555-7856'
temp.soil> !individualEmmaJohnson.driverLicenseState := #UT
<input>:1:0: generation of expression `#UT' failed, with following error:
<input>:1:45: Undefined enumeration literal `UT'.
Please provide the complete output corrected <domain_model>
model VehicleRental
dataType Date
operations
Date(date : String)
end
enum State {
AL,
AK,
AZ,
CA,
CO,
CT,
DE,
FL
}
enum VehicleTypeCode {
TRUCK,
TRUCK24,
TRUCK10,
COVERED_TRAILER,
OPEN_TRAILER
}
class RentalOffice
attributes
name : String
number : Integer
address : String
end
class Vehicle
attributes
id : Integer
registrationState : State
licensePlateNumber : String
vehicleTypeCode : VehicleTypeCode
registrationLastMaintenanceDate : Date
expirationDate : Date
end
class RentalAgreement
attributes
number : Integer
rentalDate : Date
anticipatedDuration : Integer
depositPaid : Real
quotedDailyRate : Real
quotedRatePerMile : Real
end
class Truck < Vehicle
attributes
odometerReading : Integer
gasTankCapacity : Real
workingRadio : Boolean
mileage : Integer
end
abstract class Customer
attributes
name : String
address : String
poorRisk : Boolean
end
class Individual < Customer
attributes
homePhone : String
driverLicenseState : State
driverLicenseNumber : Integer
driverLicenseExpirationDate : Date
end
class Company < Customer
attributes
idNumber : Integer
end
association RentalOfficeVehicle between
RentalOffice [1] role homeOffice
Vehicle [*]
end
association RentalOfficeRentalAgreementOrigin between
RentalOffice [1] role originatingRentalOffice
RentalAgreement [*] role originatingAgreement
end
association RentalOfficeRentalAgreementDrop between
RentalOffice [1] role droppoffRentalOffice
RentalAgreement [*] role dropoffAgreement
end
association RentalAgreementVehicle between
RentalAgreement [*]
Vehicle [1]
end
association RentalAgreementCustomer between
RentalAgreement [*]
Customer [1]
end
constraints
context Truck inv positiveGasTankCapacity:
self.gasTankCapacity >= 0
context Truck inv positiveMileage:
self.mileage >= 0
context RentalAgreement inv positiveDepositPaid:
self.depositPaid >= 0
context RentalAgreement inv positiveQuotedDailyRate:
self.quotedDailyRate >= 0
context RentalAgreement inv positiveQuotedRatePerMile:
self.quotedRatePerMile >= 0
</domain_model>
<object_model>
!new RentalOffice('officeSaltLakeCityDepot')
!officeSaltLakeCityDepot.name := 'Salt Lake City Depot'
!officeSaltLakeCityDepot.number := 505
!officeSaltLakeCityDepot.address := '789 Mountain View Rd, Salt Lake City, UT 84103'
!new Vehicle('coveredTrailer008')
!coveredTrailer008.id := 308
!coveredTrailer008.registrationState := #CO
!coveredTrailer008.licensePlateNumber := 'UT2468CT'
!coveredTrailer008.vehicleTypeCode := #COVERED_TRAILER
!coveredTrailer008.registrationLastMaintenanceDate := Date('2023-03-29')
!coveredTrailer008.expirationDate := Date('2024-03-28')
!new Truck('truck009')
!truck009.id := 309
!truck009.registrationState := #CO
!truck009.licensePlateNumber := 'WY1234TR'
!truck009.vehicleTypeCode := #TRUCK
!truck009.registrationLastMaintenanceDate := Date('2023-02-10')
!truck009.expirationDate := Date('2024-02-09')
!truck009.odometerReading := 25000
!truck009.gasTankCapacity := 21.5
!truck009.workingRadio := false
!truck009.mileage := 40000
!new Individual('individualEmmaJohnson')
!individualEmmaJohnson.name := 'Emma Johnson'
!individualEmmaJohnson.address := '81 Cowboy Way, Jackson, WY 83001'
!individualEmmaJohnson.poorRisk := false
!individualEmmaJohnson.homePhone := '307-555-7856'
!individualEmmaJohnson.driverLicenseState := #CO
!individualEmmaJohnson.driverLicenseNumber := 876543210
!individualEmmaJohnson.driverLicenseExpirationDate := Date('2026-01-21')
!new RentalAgreement('rentalAgreement5005')
!rentalAgreement5005.number := 5005
!rentalAgreement5005.rentalDate := Date('2024-03-03')
!rentalAgreement5005.anticipatedDuration := 10
!rentalAgreement5005.depositPaid := 300.0
!rentalAgreement5005.quotedDailyRate := 55.0
!rentalAgreement5005.quotedRatePerMile := 0.35
!insert (officeSaltLakeCityDepot, coveredTrailer008) into RentalOfficeVehicle
!insert (officeSaltLakeCityDepot, truck009) into RentalOfficeVehicle
!insert (officeSaltLakeCityDepot, rentalAgreement5005) into RentalOfficeRentalAgreementOrigin
!insert (officeSaltLakeCityDepot, rentalAgreement5005) into RentalOfficeRentalAgreementDrop
!insert (rentalAgreement5005, truck009) into RentalAgreementVehicle
!insert (rentalAgreement5005, individualEmmaJohnson) into RentalAgreementCustomer
</object_model> LLM as a Judge
The object 'truck009' has an `odometerReading` (25000) that is significantly lower than its total `mileage` (40000), which represents a physical contradiction for a vehicle. Additionally, 'rentalAgreement5005' begins on '2024-03-03', but it rents 'truck009' whose `expirationDate` has already passed ('2024-02-09'), making it legally implausible for a professional company to rent out an expired vehicle.
Metrics
Stats
Stats Breakdown of the total cost and elapsed time for generating the instances. - Elapsed Time = Console Time (ie. Processing Time + API Calls)
- Cost = (input tokens * input price) + (output tokens * output price)
- Elapsed Time = Console Time (ie. Processing Time + API Calls)
- Cost = (input tokens * input price) + (output tokens * output price)
| Total Cost | $0.36 |
Validation
Validation Measures the correctness of the instantiation using the USE check function. - Syntax = 1 - (Total Number of syntax errors [use check] / Total Number of lines [instance])
- Multiplicities = 1 - (Total Number of multiplicities errors [use check] / Total Number of relationships ([instance] !insert))
- Invariants = 1 - (Total Number of invariants errors [use check] / Total Number of invariants ([model] constraints))
- Syntax = 1 - (Total Number of syntax errors [use check] / Total Number of lines [instance])
- Multiplicities = 1 - (Total Number of multiplicities errors [use check] / Total Number of relationships ([instance] !insert))
- Invariants = 1 - (Total Number of invariants errors [use check] / Total Number of invariants ([model] constraints))
| Syntax | 0/43 |
| Multiplicities | 0/6 |
| Invariants | 0/5 |
Diversity
Diversity Measures the variability of the generated instances. Attributes (NumericEquals, StringEquals, StringLv): It identifies how much the LLM repeats specific values versus generating unique data points across instances (100%: Diverse, 0%: Repetitive). We group all generated attributes into bags (numeric and string) and then perform pairwise comparisons between every element to obtain. Structure (GED): Measures the Graph Edit Distance (GED) similarity between instances. Distribution (Shannon): Measures the entropy and evenness (balanced distribution) of the generated enum values. - NumericEquals = Total number of numeric attribute pairs with different values / Total number of possible pairs (n * (n - 1) / 2)
- StringEquals = Total number of string attribute pairs that are NOT exactly identical / Total number of possible pairs (n * (n - 1) / 2)
- StringLv = Sum of (Levenshtein Distance(a, b) / max(length(a), length(b))) for all string pairs / Total number of possible pairs (n * (n - 1) / 2)
- GED = Similarity = 1 - (GED / (0.5 * (GED_to_empty_A + GED_to_empty_B))). 1 = red = identical graphs, <=0.5 = green = different graphs. We consider as edit operations: Nodes, Edges, Node_Labels and Edge_Labels [https://github.com/a-coman/ged]
- Shannon (Active) = Entropy / log2(Number of unique groups actually generated). Measures how evenly the generated values are distributed, considering only the categories the LLM actually used.
- Shannon (All) = Entropy / log2(Total number of valid groups defined in the model). Measures how evenly the generated values are distributed against the full spectrum of all possible valid options defined in the .use file.
- NumericEquals = Total number of numeric attribute pairs with different values / Total number of possible pairs (n * (n - 1) / 2)
- StringEquals = Total number of string attribute pairs that are NOT exactly identical / Total number of possible pairs (n * (n - 1) / 2)
- StringLv = Sum of (Levenshtein Distance(a, b) / max(length(a), length(b))) for all string pairs / Total number of possible pairs (n * (n - 1) / 2)
- GED = Similarity = 1 - (GED / (0.5 * (GED_to_empty_A + GED_to_empty_B))). 1 = red = identical graphs, <=0.5 = green = different graphs. We consider as edit operations: Nodes, Edges, Node_Labels and Edge_Labels [https://github.com/a-coman/ged]
- Shannon (Active) = Entropy / log2(Number of unique groups actually generated). Measures how evenly the generated values are distributed, considering only the categories the LLM actually used.
- Shannon (All) = Entropy / log2(Total number of valid groups defined in the model). Measures how evenly the generated values are distributed against the full spectrum of all possible valid options defined in the .use file.
| Numeric | 100.0% |
| String Equals | 100.0% |
| String LV | 92.7% |
| Shannon (Active) | 0.000 ± 0.000 |
| Shannon (All) | 0.000 ± 0.000 |
Coverage
Model Coverage Measures the breadth of the instantiation. It answers: "How much of the structural blueprint (the model) was used?" - Classes = Total Unique Classes instantiated (!new) in the .soil / Total Number of classes (class) in the model .use
- Attributes = Total Unique Attributes instantiated (!Class.Attribute or !set) in the .soil / Total Number of attributes (attributes) in the model .use
- Relationships = Total Unique Relationships instantiated (!insert) in the .soil / Total Number of relationships (association, composition, aggregation) in the model .use
- Classes = Total Unique Classes instantiated (!new) in the .soil / Total Number of classes (class) in the model .use
- Attributes = Total Unique Attributes instantiated (!Class.Attribute or !set) in the .soil / Total Number of attributes (attributes) in the model .use
- Relationships = Total Unique Relationships instantiated (!insert) in the .soil / Total Number of relationships (association, composition, aggregation) in the model .use
| Classes | 83.3% |
| Attributes | 88.9% |
| Relationships | 100.0% |
Uncovered Items 5
Instantiation
Instance Instantiation Measures the depth or density of the data. It answers: "Of the objects the LLM decided to create, how many of their available 'slots' did it fill?" - Classes = Total Number of classes (!new) in the instance / Total possible that could have been instantiated (infinity)
- Attributes = Total Number of attributes (!Class.Attribute or !set) in the instance / Total possible that could have been instantiated (sum(number of classes instantiated of that type * Class.Attributes))
- Relationships = Total Number of relationships (!insert) in the instance / Total possible that could have been instantiated (infinity)
- Classes = Total Number of classes (!new) in the instance / Total possible that could have been instantiated (infinity)
- Attributes = Total Number of attributes (!Class.Attribute or !set) in the instance / Total possible that could have been instantiated (sum(number of classes instantiated of that type * Class.Attributes))
- Relationships = Total Number of relationships (!insert) in the instance / Total possible that could have been instantiated (infinity)
| Classes | 5/∞ |
| Attributes | 32/32 |
| Relationships | 6/∞ |
Viewer
!new RentalOffice('officeArcticVenturesRentals')
!officeArcticVenturesRentals.name := 'Arctic Ventures Rentals'
!officeArcticVenturesRentals.number := 2500
!officeArcticVenturesRentals.address := '123 Frostbite Street, Fairbanks, AK'
!new Truck('truck200')
!truck200.id := 200
!truck200.registrationState := #AK
!truck200.licensePlateNumber := 'AK-COLD-200'
!truck200.vehicleTypeCode := #COVERED_TRAILER
!truck200.registrationLastMaintenanceDate := Date('2023-09-01')
!truck200.expirationDate := Date('2024-09-01')
!truck200.odometerReading := 50000
!truck200.gasTankCapacity := 70.0
!truck200.workingRadio := false
!truck200.mileage := 45000
!new RentalAgreement('rentalAgreement500')
!rentalAgreement500.number := 500
!rentalAgreement500.rentalDate := Date('2024-01-10')
!rentalAgreement500.anticipatedDuration := 15
!rentalAgreement500.depositPaid := 3000.0
!rentalAgreement500.quotedDailyRate := 200.0
!rentalAgreement500.quotedRatePerMile := 0.15
!new Individual('individualPolarExplorer')
!individualPolarExplorer.name := 'Polar Explorer'
!individualPolarExplorer.address := '55 Expedition Drive, Nome, AK'
!individualPolarExplorer.poorRisk := false
!individualPolarExplorer.homePhone := '555-EXP-ROAD'
!individualPolarExplorer.driverLicenseState := #AK
!individualPolarExplorer.driverLicenseNumber := 56781234
!individualPolarExplorer.driverLicenseExpirationDate := Date('2025-12-31')
!insert (officeArcticVenturesRentals, truck200) into RentalOfficeVehicle
!insert (officeArcticVenturesRentals, rentalAgreement500) into RentalOfficeRentalAgreementOrigin
!insert (officeArcticVenturesRentals, rentalAgreement500) into RentalOfficeRentalAgreementDrop
!insert (rentalAgreement500, truck200) into RentalAgreementVehicle
!insert (rentalAgreement500, individualPolarExplorer) into RentalAgreementCustomer model VehicleRental
dataType Date
operations
Date(date : String)
end
enum State {
AL,
AK,
AZ,
CA,
CO,
CT,
DE,
FL
}
enum VehicleTypeCode {
TRUCK,
TRUCK24,
TRUCK10,
COVERED_TRAILER,
OPEN_TRAILER
}
class RentalOffice
attributes
name : String
number : Integer
address : String
end
class Vehicle
attributes
id : Integer
registrationState : State
licensePlateNumber : String
vehicleTypeCode : VehicleTypeCode
registrationLastMaintenanceDate : Date
expirationDate : Date
end
class RentalAgreement
attributes
number : Integer
rentalDate : Date
anticipatedDuration : Integer
depositPaid : Real
quotedDailyRate : Real
quotedRatePerMile : Real
end
class Truck < Vehicle
attributes
odometerReading : Integer
gasTankCapacity : Real
workingRadio : Boolean
mileage : Integer
end
abstract class Customer
attributes
name : String
address : String
poorRisk : Boolean
end
class Individual < Customer
attributes
homePhone : String
driverLicenseState : State
driverLicenseNumber : Integer
driverLicenseExpirationDate : Date
end
class Company < Customer
attributes
idNumber : Integer
end
association RentalOfficeVehicle between
RentalOffice [1] role homeOffice
Vehicle [*]
end
association RentalOfficeRentalAgreementOrigin between
RentalOffice [1] role originatingRentalOffice
RentalAgreement [*] role originatingAgreement
end
association RentalOfficeRentalAgreementDrop between
RentalOffice [1] role droppoffRentalOffice
RentalAgreement [*] role dropoffAgreement
end
association RentalAgreementVehicle between
RentalAgreement [*]
Vehicle [1]
end
association RentalAgreementCustomer between
RentalAgreement [*]
Customer [1]
end
constraints
context Truck inv positiveGasTankCapacity:
self.gasTankCapacity >= 0
context Truck inv positiveMileage:
self.mileage >= 0
context RentalAgreement inv positiveDepositPaid:
self.depositPaid >= 0
context RentalAgreement inv positiveQuotedDailyRate:
self.quotedDailyRate >= 0
context RentalAgreement inv positiveQuotedRatePerMile:
self.quotedRatePerMile >= 0 You are tasked with analyzing conceptual models represented as class diagrams and expressed in the UML-based specification environment using its native syntax. You must adhere to the following requirements: - Use very clear language. - Do not overexplain, be concise. - Multiplicities must be very clear and easy to understand. You should follow the structure and requirements below: ## Description Start by explaining the overall structure and purpose of the model. ### Components Break down the components of the model (i.e., classes and attributes), describing each, their type and purpose. ## Relationships Describe the relationships between the components of the model, dependencies and multiplicities (i.e., minimum and maximum number of instances of one class that can be associated with instances of another class). Describe the multiplicities at both ends of each association. ## Invariants Define the invariants that apply to the model (i.e., those constraints that must be fulfilled). Your task is to generate a complete and diverse instance, in plain English, for a given category and based on a provided conceptual model description. The instance must adhere to these requirements: - Be self-contained: Include all required attributes, relationships, and related entities in full detail. - Conform to the model: Fulfill the constraints, multiplicities, relationships, and attributes defined in the class diagram model. - Understand the context: Ensure that its attributes and relationships are relevant. - Avoid duplication of instances: Take into consideration those instances previously built to avoid redundancy. - Semantic diversity: From a semantic point of view, incorporate varied scenarios, including regional, linguistic, or cultural differences. - Structural diversity: Include instances with different numbers of elements, different numbers of relationships and complexity, and create varied examples by changing entity attributes. You are tasked with creating instances of a conceptual model in the UML-based Specification Environment (USE). You will receive: 1. The UML class diagram that the instance follows. 2. A sample syntax of instances creation. 3. A description of the instance that needs to be created. Your goal is to generate these instances based on the provided description, adhering strictly to these requirements: - The output must be in plain text, with no additional comments, descriptions, or explanations. - Ensure that the created instance adheres to the provided description. - Follow the syntax sample provided, without deviation. - Take into account previously created instances to avoid using duplicate naming. <role>
You are an expert software and system modeler. You are able to assess the semantic quality of object models that have been created to conform to a domain model. The models are defined in USE (UML-based Specification Environment) and OCL (Object Constraint Language).
Your primary capability is "Semantic Reality Checking". You do not just check for syntactic correctness; you check for real-world plausibility and logical consistency within a given domain.
</role>
<context>
The user will provide two types of content:
1. **Domain Model (.use)**: A class diagram definition including classes, attributes, enums, relationships, multiplicities and roles.
2. **Object Model (.soil)**: An object model. This object model can be seen as a script composed of instructions for the creation of objects, relationships and setting attribute values (snapshot).
Your goal is to act as a judge to determine if the object model represents a **REALISTIC** scenario based on the domain model and common sense real-world logic.
</context>
<definitions>
- **Realistic**: The object model is syntactically correct AND semantically plausible (e.g., A 'Person' has an age between 0 and 120; a 'Car' has a positive price).
- **Unrealistic**: The object model contains contradictions, impossible physical values, or nonsensical relationships (e.g., A 'Person' is their own father; a 'Product' has a negative weight).
- **Doubtful**: You cannot determine whether the object model is realistic or not.
</definitions>
<instructions>
Follow this thinking process strictly before generating the final output:
1. **Analyze the Domain (.use)**: Understand the classes and what they represent in the real world.
2. **Analyze the Instances (.soil)**: Map the created objects to their classes. Look at the specific values assigned to attributes and the relationships created between objects.
3. **Evaluate Semantics**:
- Apply "Common Sense Knowledge" to the attribute values.
- Check cardinality and relationship logic beyond simple OCL constraints.
- Identify any outliers or logical fallacies.
4. **Determine Verdict**: Select one of the defined labels (Realistic/Unrealistic/Doubtful).
</instructions>
<constraints>
- **Tone**: Objective, Analytical, Technical.
- **Verbosity**: Low. Be direct.
- **Reasoning**: The "Why" section must be concise and specific, citing variable names, objects, or relationships when possible.
- Do not output the internal thinking process. Only output the final formatted result.
</constraints>
<output_format>
Structure your response exactly as follows:
**Response**: [Realistic | Unrealistic | Doubtful]
**Why**: [Concise explanation of your reasoning. If Unrealistic, specify the exact objects, values or relationships that break realism.]
</output_format>
<examples>
Example 1:
Input:
<domain_model>
class Person
attributes
age: Integer
end
class Pet
attributes
name: String
end
association Ownership between
Person [1] role owner
Pet [*] role pets
end
</domain_model>
<object_model>
!new Person('p1')
!p1.age := 250
!new Pet('pet1')
!pet1.name := 'Luna'
… 1.000 more pets creation …
!pet1000.name := 'Max'
!insert (p1, pet1) into Ownership
…1.000 more pets associated with p1 …
!insert (p1, pet1000) into Ownership
</object_model>
Output:
**Response**: Unrealistic
**Why**: The object 'p1' of class 'Person' has an age of 250, which exceeds the biologically plausible lifespan of a human. Although it is not plausible that 1 same person owns 1.000 pets.
Example 2:
Input:
<domain_model>
class Car
attributes
brand: String
end
class Person
attributes
name: String
end
association Ownership between
Person [1] role owner
Car [*] role cars
end
</domain_model>
<object_model>
!new Person('p1')
!p1.age := 19
!new Car('c1')
!c1.brand := 'Toyota'
!insert (p1, c1) into Ownership
</object_model>
Output:
**Response**: Realistic
**Why**: The object 'c1' has a valid, recognized real-world car brand assigned, and its plausible that a teenager has only one car.
Example 3:
Input:
<domain_model>
class Component
attributes
setting_val: Integer
config_mode: String
end
</domain_model>
<object_model>
!new Component('c1')
!c1.setting_val := 8080
!c1.config_mode := 'Legacy'
</object_model>
Output:
**Response**: Doubtful
**Why**: The class 'Component' and attribute 'setting_val' are generic and lack specific real-world semantic context. Without knowing what specific physical or software system this represents, it is impossible to determine if '8080' is a realistic value or an outlier.
</examples> Analyze the following UML class diagram:
model VehicleRental
dataType Date
operations
Date(date : String)
end
enum State {
AL,
AK,
AZ,
CA,
CO,
CT,
DE,
FL
}
enum VehicleTypeCode {
TRUCK,
TRUCK24,
TRUCK10,
COVERED_TRAILER,
OPEN_TRAILER
}
class RentalOffice
attributes
name : String
number : Integer
address : String
end
class Vehicle
attributes
id : Integer
registrationState : State
licensePlateNumber : String
vehicleTypeCode : VehicleTypeCode
registrationLastMaintenanceDate : Date
expirationDate : Date
end
class RentalAgreement
attributes
number : Integer
rentalDate : Date
anticipatedDuration : Integer
depositPaid : Real
quotedDailyRate : Real
quotedRatePerMile : Real
end
class Truck < Vehicle
attributes
odometerReading : Integer
gasTankCapacity : Real
workingRadio : Boolean
mileage : Integer
end
abstract class Customer
attributes
name : String
address : String
poorRisk : Boolean
end
class Individual < Customer
attributes
homePhone : String
driverLicenseState : State
driverLicenseNumber : Integer
driverLicenseExpirationDate : Date
end
class Company < Customer
attributes
idNumber : Integer
end
association RentalOfficeVehicle between
RentalOffice [1] role homeOffice
Vehicle [*]
end
association RentalOfficeRentalAgreementOrigin between
RentalOffice [1] role originatingRentalOffice
RentalAgreement [*] role originatingAgreement
end
association RentalOfficeRentalAgreementDrop between
RentalOffice [1] role droppoffRentalOffice
RentalAgreement [*] role dropoffAgreement
end
association RentalAgreementVehicle between
RentalAgreement [*]
Vehicle [1]
end
association RentalAgreementCustomer between
RentalAgreement [*]
Customer [1]
end
constraints
context Truck inv positiveGasTankCapacity:
self.gasTankCapacity >= 0
context Truck inv positiveMileage:
self.mileage >= 0
context RentalAgreement inv positiveDepositPaid:
self.depositPaid >= 0
context RentalAgreement inv positiveQuotedDailyRate:
self.quotedDailyRate >= 0
context RentalAgreement inv positiveQuotedRatePerMile:
self.quotedRatePerMile >= 0 For the same category and model description, generate another instance that is structurally and semantically different from the previous ones Continue with the following description, creating the instance according to the syntax example and this specification:
## Boundary Instance for VehicleRental Model
### Rental Office
- **Name**: "Arctic Ventures Rentals"
- **Number**: 2500 (using a mid-range but distinct number)
- **Address**: "123 Frostbite Street, Fairbanks, AK"
### Vehicle (Truck)
- **ID**: 200 (unique identifier not used in previous examples)
- **Registration State**: Alaska
- **License Plate Number**: "AK-COLD-200"
- **Vehicle Type Code**: COVERED_TRAILER (using a different vehicle type)
- **Registration Last Maintenance Date**: "2023-09-01"
- **Registration Expiration Date**: "2024-09-01"
- **Odometer Reading**: 50000 (moderate usage to simulate typical conditions in regions with extreme terrain)
- **Gas Tank Capacity**: 70.0 (large enough for dealing with remote areas)
- **Working Radio**: False
- **Mileage**: 45000 (indicates reliable daily use on long distances)
### Rental Agreement
- **Number**: 500 (arbitrary middle-range identifier)
- **Rental Date**: "2024-01-10"
- **Anticipated Duration**: 15 (representative of a longer trip scenario)
- **Deposit Paid**: 3000.0 (reflective of a significant rental period)
- **Quoted Daily Rate**: 200.0 (indicative of a premium rate due to challenging conditions)
- **Quoted Rate Per Mile**: 0.15 (competitive per mile cost for longer trips)
### Customer (Individual)
- **Name**: "Polar Explorer"
- **Address**: "55 Expedition Drive, Nome, AK"
- **Poor Risk**: False
- **Home Phone**: "555-EXP-ROAD"
- **Driver License State**: Alaska
- **Driver License Number**: 56781234 (a plausible higher-end individual number)
- **Driver License Expiration Date**: "2025-12-31"
### Relationships
- **RentalOfficeVehicle**:
- "Arctic Ventures Rentals" manages the Covered Trailer with ID 200.
- **RentalOfficeRentalAgreementOrigin**:
- Origin for Rental Agreement 500 is "Arctic Ventures Rentals".
- **RentalOfficeRentalAgreementDrop**:
- Drop-off for Rental Agreement 500 is "Arctic Ventures Rentals".
- **RentalAgreementVehicle**:
- Rental Agreement 500 involves the Covered Trailer with ID 200.
- **RentalAgreementCustomer**:
- Rental Agreement 500 is associated with "Polar Explorer", the individual.
This instance integrates a scenario involving travel in remote and challenging geographical locations, like Alaska, with different vehicle type and customer attributes, emphasizing unique and descriptive identifiers. <domain_model>
model VehicleRental
dataType Date
operations
Date(date : String)
end
enum State {
AL,
AK,
AZ,
CA,
CO,
CT,
DE,
FL
}
enum VehicleTypeCode {
TRUCK,
TRUCK24,
TRUCK10,
COVERED_TRAILER,
OPEN_TRAILER
}
class RentalOffice
attributes
name : String
number : Integer
address : String
end
class Vehicle
attributes
id : Integer
registrationState : State
licensePlateNumber : String
vehicleTypeCode : VehicleTypeCode
registrationLastMaintenanceDate : Date
expirationDate : Date
end
class RentalAgreement
attributes
number : Integer
rentalDate : Date
anticipatedDuration : Integer
depositPaid : Real
quotedDailyRate : Real
quotedRatePerMile : Real
end
class Truck < Vehicle
attributes
odometerReading : Integer
gasTankCapacity : Real
workingRadio : Boolean
mileage : Integer
end
abstract class Customer
attributes
name : String
address : String
poorRisk : Boolean
end
class Individual < Customer
attributes
homePhone : String
driverLicenseState : State
driverLicenseNumber : Integer
driverLicenseExpirationDate : Date
end
class Company < Customer
attributes
idNumber : Integer
end
association RentalOfficeVehicle between
RentalOffice [1] role homeOffice
Vehicle [*]
end
association RentalOfficeRentalAgreementOrigin between
RentalOffice [1] role originatingRentalOffice
RentalAgreement [*] role originatingAgreement
end
association RentalOfficeRentalAgreementDrop between
RentalOffice [1] role droppoffRentalOffice
RentalAgreement [*] role dropoffAgreement
end
association RentalAgreementVehicle between
RentalAgreement [*]
Vehicle [1]
end
association RentalAgreementCustomer between
RentalAgreement [*]
Customer [1]
end
constraints
context Truck inv positiveGasTankCapacity:
self.gasTankCapacity >= 0
context Truck inv positiveMileage:
self.mileage >= 0
context RentalAgreement inv positiveDepositPaid:
self.depositPaid >= 0
context RentalAgreement inv positiveQuotedDailyRate:
self.quotedDailyRate >= 0
context RentalAgreement inv positiveQuotedRatePerMile:
self.quotedRatePerMile >= 0
</domain_model>
<object_model>
!new RentalOffice('officeArcticVenturesRentals')
!officeArcticVenturesRentals.name := 'Arctic Ventures Rentals'
!officeArcticVenturesRentals.number := 2500
!officeArcticVenturesRentals.address := '123 Frostbite Street, Fairbanks, AK'
!new Truck('truck200')
!truck200.id := 200
!truck200.registrationState := #AK
!truck200.licensePlateNumber := 'AK-COLD-200'
!truck200.vehicleTypeCode := #COVERED_TRAILER
!truck200.registrationLastMaintenanceDate := Date('2023-09-01')
!truck200.expirationDate := Date('2024-09-01')
!truck200.odometerReading := 50000
!truck200.gasTankCapacity := 70.0
!truck200.workingRadio := false
!truck200.mileage := 45000
!new RentalAgreement('rentalAgreement500')
!rentalAgreement500.number := 500
!rentalAgreement500.rentalDate := Date('2024-01-10')
!rentalAgreement500.anticipatedDuration := 15
!rentalAgreement500.depositPaid := 3000.0
!rentalAgreement500.quotedDailyRate := 200.0
!rentalAgreement500.quotedRatePerMile := 0.15
!new Individual('individualPolarExplorer')
!individualPolarExplorer.name := 'Polar Explorer'
!individualPolarExplorer.address := '55 Expedition Drive, Nome, AK'
!individualPolarExplorer.poorRisk := false
!individualPolarExplorer.homePhone := '555-EXP-ROAD'
!individualPolarExplorer.driverLicenseState := #AK
!individualPolarExplorer.driverLicenseNumber := 56781234
!individualPolarExplorer.driverLicenseExpirationDate := Date('2025-12-31')
!insert (officeArcticVenturesRentals, truck200) into RentalOfficeVehicle
!insert (officeArcticVenturesRentals, rentalAgreement500) into RentalOfficeRentalAgreementOrigin
!insert (officeArcticVenturesRentals, rentalAgreement500) into RentalOfficeRentalAgreementDrop
!insert (rentalAgreement500, truck200) into RentalAgreementVehicle
!insert (rentalAgreement500, individualPolarExplorer) into RentalAgreementCustomer
</object_model> LLM as a Judge
The object 'truck200' is instantiated from the 'Truck' class with motorized attributes like 'gasTankCapacity' (70.0) and 'odometerReading' (50000), but its 'vehicleTypeCode' is set to '#COVERED_TRAILER'. A trailer implies a non-motorized vehicle that lacks an engine, gas tank, or odometer, making this combination contradictory.
Metrics
Stats
Stats Breakdown of the total cost and elapsed time for generating the instances. - Elapsed Time = Console Time (ie. Processing Time + API Calls)
- Cost = (input tokens * input price) + (output tokens * output price)
- Elapsed Time = Console Time (ie. Processing Time + API Calls)
- Cost = (input tokens * input price) + (output tokens * output price)
| Total Cost | $0.13 |
Validation
Validation Measures the correctness of the instantiation using the USE check function. - Syntax = 1 - (Total Number of syntax errors [use check] / Total Number of lines [instance])
- Multiplicities = 1 - (Total Number of multiplicities errors [use check] / Total Number of relationships ([instance] !insert))
- Invariants = 1 - (Total Number of invariants errors [use check] / Total Number of invariants ([model] constraints))
- Syntax = 1 - (Total Number of syntax errors [use check] / Total Number of lines [instance])
- Multiplicities = 1 - (Total Number of multiplicities errors [use check] / Total Number of relationships ([instance] !insert))
- Invariants = 1 - (Total Number of invariants errors [use check] / Total Number of invariants ([model] constraints))
| Syntax | 0/35 |
| Multiplicities | 0/5 |
| Invariants | 0/5 |
Diversity
Diversity Measures the variability of the generated instances. Attributes (NumericEquals, StringEquals, StringLv): It identifies how much the LLM repeats specific values versus generating unique data points across instances (100%: Diverse, 0%: Repetitive). We group all generated attributes into bags (numeric and string) and then perform pairwise comparisons between every element to obtain. Structure (GED): Measures the Graph Edit Distance (GED) similarity between instances. Distribution (Shannon): Measures the entropy and evenness (balanced distribution) of the generated enum values. - NumericEquals = Total number of numeric attribute pairs with different values / Total number of possible pairs (n * (n - 1) / 2)
- StringEquals = Total number of string attribute pairs that are NOT exactly identical / Total number of possible pairs (n * (n - 1) / 2)
- StringLv = Sum of (Levenshtein Distance(a, b) / max(length(a), length(b))) for all string pairs / Total number of possible pairs (n * (n - 1) / 2)
- GED = Similarity = 1 - (GED / (0.5 * (GED_to_empty_A + GED_to_empty_B))). 1 = red = identical graphs, <=0.5 = green = different graphs. We consider as edit operations: Nodes, Edges, Node_Labels and Edge_Labels [https://github.com/a-coman/ged]
- Shannon (Active) = Entropy / log2(Number of unique groups actually generated). Measures how evenly the generated values are distributed, considering only the categories the LLM actually used.
- Shannon (All) = Entropy / log2(Total number of valid groups defined in the model). Measures how evenly the generated values are distributed against the full spectrum of all possible valid options defined in the .use file.
- NumericEquals = Total number of numeric attribute pairs with different values / Total number of possible pairs (n * (n - 1) / 2)
- StringEquals = Total number of string attribute pairs that are NOT exactly identical / Total number of possible pairs (n * (n - 1) / 2)
- StringLv = Sum of (Levenshtein Distance(a, b) / max(length(a), length(b))) for all string pairs / Total number of possible pairs (n * (n - 1) / 2)
- GED = Similarity = 1 - (GED / (0.5 * (GED_to_empty_A + GED_to_empty_B))). 1 = red = identical graphs, <=0.5 = green = different graphs. We consider as edit operations: Nodes, Edges, Node_Labels and Edge_Labels [https://github.com/a-coman/ged]
- Shannon (Active) = Entropy / log2(Number of unique groups actually generated). Measures how evenly the generated values are distributed, considering only the categories the LLM actually used.
- Shannon (All) = Entropy / log2(Total number of valid groups defined in the model). Measures how evenly the generated values are distributed against the full spectrum of all possible valid options defined in the .use file.
| Numeric | 98.2% |
| String Equals | 100.0% |
| String LV | 90.8% |
| Shannon (Active) | 0.000 ± 0.000 |
| Shannon (All) | 0.000 ± 0.000 |
Coverage
Model Coverage Measures the breadth of the instantiation. It answers: "How much of the structural blueprint (the model) was used?" - Classes = Total Unique Classes instantiated (!new) in the .soil / Total Number of classes (class) in the model .use
- Attributes = Total Unique Attributes instantiated (!Class.Attribute or !set) in the .soil / Total Number of attributes (attributes) in the model .use
- Relationships = Total Unique Relationships instantiated (!insert) in the .soil / Total Number of relationships (association, composition, aggregation) in the model .use
- Classes = Total Unique Classes instantiated (!new) in the .soil / Total Number of classes (class) in the model .use
- Attributes = Total Unique Attributes instantiated (!Class.Attribute or !set) in the .soil / Total Number of attributes (attributes) in the model .use
- Relationships = Total Unique Relationships instantiated (!insert) in the .soil / Total Number of relationships (association, composition, aggregation) in the model .use
| Classes | 66.7% |
| Attributes | 72.2% |
| Relationships | 100.0% |
Uncovered Items 12
Show all 10 attributes
Instantiation
Instance Instantiation Measures the depth or density of the data. It answers: "Of the objects the LLM decided to create, how many of their available 'slots' did it fill?" - Classes = Total Number of classes (!new) in the instance / Total possible that could have been instantiated (infinity)
- Attributes = Total Number of attributes (!Class.Attribute or !set) in the instance / Total possible that could have been instantiated (sum(number of classes instantiated of that type * Class.Attributes))
- Relationships = Total Number of relationships (!insert) in the instance / Total possible that could have been instantiated (infinity)
- Classes = Total Number of classes (!new) in the instance / Total possible that could have been instantiated (infinity)
- Attributes = Total Number of attributes (!Class.Attribute or !set) in the instance / Total possible that could have been instantiated (sum(number of classes instantiated of that type * Class.Attributes))
- Relationships = Total Number of relationships (!insert) in the instance / Total possible that could have been instantiated (infinity)
| Classes | 4/∞ |
| Attributes | 26/26 |
| Relationships | 5/∞ |
Viewer
!new RentalOffice('officeCascadiaRentals')
!officeCascadiaRentals.name := 'Cascadia Rentals'
!officeCascadiaRentals.number := 560
!officeCascadiaRentals.address := '749 NW Portland St, Portland, OR 97209'
!new Truck('truck6090')
!truck6090.id := 6090
!truck6090.registrationState := #CA
!truck6090.licensePlateNumber := 'OR3344'
!truck6090.vehicleTypeCode := #TRUCK
!truck6090.registrationLastMaintenanceDate := Date('2023-11-01')
!truck6090.expirationDate := Date('2024-11-01')
!truck6090.odometerReading := 35000
!truck6090.gasTankCapacity := 21.0
!truck6090.workingRadio := true
!truck6090.mileage := 16
!new Truck('truck6091')
!truck6091.id := 6091
!truck6091.registrationState := #CA
!truck6091.licensePlateNumber := 'CA5588'
!truck6091.vehicleTypeCode := #TRUCK
!truck6091.registrationLastMaintenanceDate := Date('2023-09-10')
!truck6091.expirationDate := Date('2024-09-10')
!truck6091.odometerReading := 55000
!truck6091.gasTankCapacity := 27.5
!truck6091.workingRadio := false
!truck6091.mileage := 14
!new Vehicle('coveredTrailer7102')
!coveredTrailer7102.id := 7102
!coveredTrailer7102.registrationState := #CA
!coveredTrailer7102.licensePlateNumber := 'WA8923'
!coveredTrailer7102.vehicleTypeCode := #COVERED_TRAILER
!coveredTrailer7102.registrationLastMaintenanceDate := Date('2023-08-22')
!coveredTrailer7102.expirationDate := Date('2024-08-22')
!new Vehicle('coveredTrailer7110')
!coveredTrailer7110.id := 7110
!coveredTrailer7110.registrationState := #CA
!coveredTrailer7110.licensePlateNumber := 'ID1234'
!coveredTrailer7110.vehicleTypeCode := #COVERED_TRAILER
!coveredTrailer7110.registrationLastMaintenanceDate := Date('2023-07-15')
!coveredTrailer7110.expirationDate := Date('2024-07-15')
!new Individual('individualLiamAnderson')
!individualLiamAnderson.name := 'Liam Anderson'
!individualLiamAnderson.address := '345 Elm St, Portland, OR 97210'
!individualLiamAnderson.poorRisk := true
!individualLiamAnderson.homePhone := '503-555-0377'
!individualLiamAnderson.driverLicenseState := #CA
!individualLiamAnderson.driverLicenseNumber := 78904567
!individualLiamAnderson.driverLicenseExpirationDate := Date('2026-09-19')
!new Company('companyEvergreenAdventures')
!companyEvergreenAdventures.name := 'Evergreen Adventures'
!companyEvergreenAdventures.address := '112 Spruce Ave, Bend, OR 97702'
!companyEvergreenAdventures.poorRisk := false
!companyEvergreenAdventures.idNumber := 1015
!new Company('companySustainableSolutionsLLC')
!companySustainableSolutionsLLC.name := 'Sustainable Solutions LLC'
!companySustainableSolutionsLLC.address := '678 Greenway Dr, Eugene, OR 97401'
!companySustainableSolutionsLLC.poorRisk := true
!companySustainableSolutionsLLC.idNumber := 3030
!new RentalAgreement('rentalAgreement13004')
!rentalAgreement13004.number := 13004
!rentalAgreement13004.rentalDate := Date('2024-03-14')
!rentalAgreement13004.anticipatedDuration := 3
!rentalAgreement13004.depositPaid := 90.0
!rentalAgreement13004.quotedDailyRate := 45.0
!rentalAgreement13004.quotedRatePerMile := 0.50
!new RentalAgreement('rentalAgreement14007')
!rentalAgreement14007.number := 14007
!rentalAgreement14007.rentalDate := Date('2024-02-15')
!rentalAgreement14007.anticipatedDuration := 10
!rentalAgreement14007.depositPaid := 200.0
!rentalAgreement14007.quotedDailyRate := 32.0
!rentalAgreement14007.quotedRatePerMile := 0.25
!new RentalAgreement('rentalAgreement15008')
!rentalAgreement15008.number := 15008
!rentalAgreement15008.rentalDate := Date('2024-04-05')
!rentalAgreement15008.anticipatedDuration := 7
!rentalAgreement15008.depositPaid := 150.0
!rentalAgreement15008.quotedDailyRate := 28.0
!rentalAgreement15008.quotedRatePerMile := 0.30
!new RentalAgreement('rentalAgreement14009')
!rentalAgreement14009.number := 14009
!rentalAgreement14009.rentalDate := Date('2024-02-18')
!rentalAgreement14009.anticipatedDuration := 14
!rentalAgreement14009.depositPaid := 350.0
!rentalAgreement14009.quotedDailyRate := 30.0
!rentalAgreement14009.quotedRatePerMile := 0.40
!insert (officeCascadiaRentals, truck6090) into RentalOfficeVehicle
!insert (officeCascadiaRentals, truck6091) into RentalOfficeVehicle
!insert (officeCascadiaRentals, coveredTrailer7102) into RentalOfficeVehicle
!insert (officeCascadiaRentals, coveredTrailer7110) into RentalOfficeVehicle
!insert (officeCascadiaRentals, rentalAgreement13004) into RentalOfficeRentalAgreementOrigin
!insert (officeCascadiaRentals, rentalAgreement14007) into RentalOfficeRentalAgreementOrigin
!insert (officeCascadiaRentals, rentalAgreement15008) into RentalOfficeRentalAgreementOrigin
!insert (officeCascadiaRentals, rentalAgreement14009) into RentalOfficeRentalAgreementOrigin
!insert (officeCascadiaRentals, rentalAgreement13004) into RentalOfficeRentalAgreementDrop
!insert (officeCascadiaRentals, rentalAgreement14007) into RentalOfficeRentalAgreementDrop
!insert (officeCascadiaRentals, rentalAgreement15008) into RentalOfficeRentalAgreementDrop
!insert (officeCascadiaRentals, rentalAgreement14009) into RentalOfficeRentalAgreementDrop
!insert (rentalAgreement13004, truck6090) into RentalAgreementVehicle
!insert (rentalAgreement14007, coveredTrailer7102) into RentalAgreementVehicle
!insert (rentalAgreement15008, coveredTrailer7110) into RentalAgreementVehicle
!insert (rentalAgreement14009, truck6091) into RentalAgreementVehicle
!insert (rentalAgreement13004, individualLiamAnderson) into RentalAgreementCustomer
!insert (rentalAgreement14007, companyEvergreenAdventures) into RentalAgreementCustomer
!insert (rentalAgreement15008, companySustainableSolutionsLLC) into RentalAgreementCustomer
!insert (rentalAgreement14009, companyEvergreenAdventures) into RentalAgreementCustomer model VehicleRental
dataType Date
operations
Date(date : String)
end
enum State {
AL,
AK,
AZ,
CA,
CO,
CT,
DE,
FL
}
enum VehicleTypeCode {
TRUCK,
TRUCK24,
TRUCK10,
COVERED_TRAILER,
OPEN_TRAILER
}
class RentalOffice
attributes
name : String
number : Integer
address : String
end
class Vehicle
attributes
id : Integer
registrationState : State
licensePlateNumber : String
vehicleTypeCode : VehicleTypeCode
registrationLastMaintenanceDate : Date
expirationDate : Date
end
class RentalAgreement
attributes
number : Integer
rentalDate : Date
anticipatedDuration : Integer
depositPaid : Real
quotedDailyRate : Real
quotedRatePerMile : Real
end
class Truck < Vehicle
attributes
odometerReading : Integer
gasTankCapacity : Real
workingRadio : Boolean
mileage : Integer
end
abstract class Customer
attributes
name : String
address : String
poorRisk : Boolean
end
class Individual < Customer
attributes
homePhone : String
driverLicenseState : State
driverLicenseNumber : Integer
driverLicenseExpirationDate : Date
end
class Company < Customer
attributes
idNumber : Integer
end
association RentalOfficeVehicle between
RentalOffice [1] role homeOffice
Vehicle [*]
end
association RentalOfficeRentalAgreementOrigin between
RentalOffice [1] role originatingRentalOffice
RentalAgreement [*] role originatingAgreement
end
association RentalOfficeRentalAgreementDrop between
RentalOffice [1] role droppoffRentalOffice
RentalAgreement [*] role dropoffAgreement
end
association RentalAgreementVehicle between
RentalAgreement [*]
Vehicle [1]
end
association RentalAgreementCustomer between
RentalAgreement [*]
Customer [1]
end
constraints
context Truck inv positiveGasTankCapacity:
self.gasTankCapacity >= 0
context Truck inv positiveMileage:
self.mileage >= 0
context RentalAgreement inv positiveDepositPaid:
self.depositPaid >= 0
context RentalAgreement inv positiveQuotedDailyRate:
self.quotedDailyRate >= 0
context RentalAgreement inv positiveQuotedRatePerMile:
self.quotedRatePerMile >= 0 You are tasked with analyzing conceptual models represented as class diagrams and expressed in the UML-based specification environment using its native syntax. You must adhere to the following requirements: - Use very clear language. - Do not overexplain, be concise. - Multiplicities must be very clear and easy to understand. You should follow the structure and requirements below: ## Description Start by explaining the overall structure and purpose of the model. ### Components Break down the components of the model (i.e., classes and attributes), describing each, their type and purpose. ## Relationships Describe the relationships between the components of the model, dependencies and multiplicities (i.e., minimum and maximum number of instances of one class that can be associated with instances of another class). Describe the multiplicities at both ends of each association. ## Invariants Define the invariants that apply to the model (i.e., those constraints that must be fulfilled). Your task is to generate a complete and diverse instance, in plain English, for a given category and based on a provided conceptual model description. The instance must adhere to these requirements: - Be self-contained: Include all required attributes, relationships, and related entities in full detail. - Conform to the model: Fulfill the constraints, multiplicities, relationships, and attributes defined in the class diagram model. - Understand the context: Ensure that its attributes and relationships are relevant. - Avoid duplication of instances: Take into consideration those instances previously built to avoid redundancy. - Semantic diversity: From a semantic point of view, incorporate varied scenarios, including regional, linguistic, or cultural differences. - Structural diversity: Include instances with different numbers of elements, different numbers of relationships and complexity, and create varied examples by changing entity attributes. You are tasked with creating instances of a conceptual model in the UML-based Specification Environment (USE). You will receive: 1. The UML class diagram that the instance follows. 2. A sample syntax of instances creation. 3. A description of the instance that needs to be created. Your goal is to generate these instances based on the provided description, adhering strictly to these requirements: - The output must be in plain text, with no additional comments, descriptions, or explanations. - Ensure that the created instance adheres to the provided description. - Follow the syntax sample provided, without deviation. - Take into account previously created instances to avoid using duplicate naming. <role>
You are an expert software and system modeler. You are able to assess the semantic quality of object models that have been created to conform to a domain model. The models are defined in USE (UML-based Specification Environment) and OCL (Object Constraint Language).
Your primary capability is "Semantic Reality Checking". You do not just check for syntactic correctness; you check for real-world plausibility and logical consistency within a given domain.
</role>
<context>
The user will provide two types of content:
1. **Domain Model (.use)**: A class diagram definition including classes, attributes, enums, relationships, multiplicities and roles.
2. **Object Model (.soil)**: An object model. This object model can be seen as a script composed of instructions for the creation of objects, relationships and setting attribute values (snapshot).
Your goal is to act as a judge to determine if the object model represents a **REALISTIC** scenario based on the domain model and common sense real-world logic.
</context>
<definitions>
- **Realistic**: The object model is syntactically correct AND semantically plausible (e.g., A 'Person' has an age between 0 and 120; a 'Car' has a positive price).
- **Unrealistic**: The object model contains contradictions, impossible physical values, or nonsensical relationships (e.g., A 'Person' is their own father; a 'Product' has a negative weight).
- **Doubtful**: You cannot determine whether the object model is realistic or not.
</definitions>
<instructions>
Follow this thinking process strictly before generating the final output:
1. **Analyze the Domain (.use)**: Understand the classes and what they represent in the real world.
2. **Analyze the Instances (.soil)**: Map the created objects to their classes. Look at the specific values assigned to attributes and the relationships created between objects.
3. **Evaluate Semantics**:
- Apply "Common Sense Knowledge" to the attribute values.
- Check cardinality and relationship logic beyond simple OCL constraints.
- Identify any outliers or logical fallacies.
4. **Determine Verdict**: Select one of the defined labels (Realistic/Unrealistic/Doubtful).
</instructions>
<constraints>
- **Tone**: Objective, Analytical, Technical.
- **Verbosity**: Low. Be direct.
- **Reasoning**: The "Why" section must be concise and specific, citing variable names, objects, or relationships when possible.
- Do not output the internal thinking process. Only output the final formatted result.
</constraints>
<output_format>
Structure your response exactly as follows:
**Response**: [Realistic | Unrealistic | Doubtful]
**Why**: [Concise explanation of your reasoning. If Unrealistic, specify the exact objects, values or relationships that break realism.]
</output_format>
<examples>
Example 1:
Input:
<domain_model>
class Person
attributes
age: Integer
end
class Pet
attributes
name: String
end
association Ownership between
Person [1] role owner
Pet [*] role pets
end
</domain_model>
<object_model>
!new Person('p1')
!p1.age := 250
!new Pet('pet1')
!pet1.name := 'Luna'
… 1.000 more pets creation …
!pet1000.name := 'Max'
!insert (p1, pet1) into Ownership
…1.000 more pets associated with p1 …
!insert (p1, pet1000) into Ownership
</object_model>
Output:
**Response**: Unrealistic
**Why**: The object 'p1' of class 'Person' has an age of 250, which exceeds the biologically plausible lifespan of a human. Although it is not plausible that 1 same person owns 1.000 pets.
Example 2:
Input:
<domain_model>
class Car
attributes
brand: String
end
class Person
attributes
name: String
end
association Ownership between
Person [1] role owner
Car [*] role cars
end
</domain_model>
<object_model>
!new Person('p1')
!p1.age := 19
!new Car('c1')
!c1.brand := 'Toyota'
!insert (p1, c1) into Ownership
</object_model>
Output:
**Response**: Realistic
**Why**: The object 'c1' has a valid, recognized real-world car brand assigned, and its plausible that a teenager has only one car.
Example 3:
Input:
<domain_model>
class Component
attributes
setting_val: Integer
config_mode: String
end
</domain_model>
<object_model>
!new Component('c1')
!c1.setting_val := 8080
!c1.config_mode := 'Legacy'
</object_model>
Output:
**Response**: Doubtful
**Why**: The class 'Component' and attribute 'setting_val' are generic and lack specific real-world semantic context. Without knowing what specific physical or software system this represents, it is impossible to determine if '8080' is a realistic value or an outlier.
</examples> Analyze the following UML class diagram:
model VehicleRental
dataType Date
operations
Date(date : String)
end
enum State {
AL,
AK,
AZ,
CA,
CO,
CT,
DE,
FL
}
enum VehicleTypeCode {
TRUCK,
TRUCK24,
TRUCK10,
COVERED_TRAILER,
OPEN_TRAILER
}
class RentalOffice
attributes
name : String
number : Integer
address : String
end
class Vehicle
attributes
id : Integer
registrationState : State
licensePlateNumber : String
vehicleTypeCode : VehicleTypeCode
registrationLastMaintenanceDate : Date
expirationDate : Date
end
class RentalAgreement
attributes
number : Integer
rentalDate : Date
anticipatedDuration : Integer
depositPaid : Real
quotedDailyRate : Real
quotedRatePerMile : Real
end
class Truck < Vehicle
attributes
odometerReading : Integer
gasTankCapacity : Real
workingRadio : Boolean
mileage : Integer
end
abstract class Customer
attributes
name : String
address : String
poorRisk : Boolean
end
class Individual < Customer
attributes
homePhone : String
driverLicenseState : State
driverLicenseNumber : Integer
driverLicenseExpirationDate : Date
end
class Company < Customer
attributes
idNumber : Integer
end
association RentalOfficeVehicle between
RentalOffice [1] role homeOffice
Vehicle [*]
end
association RentalOfficeRentalAgreementOrigin between
RentalOffice [1] role originatingRentalOffice
RentalAgreement [*] role originatingAgreement
end
association RentalOfficeRentalAgreementDrop between
RentalOffice [1] role droppoffRentalOffice
RentalAgreement [*] role dropoffAgreement
end
association RentalAgreementVehicle between
RentalAgreement [*]
Vehicle [1]
end
association RentalAgreementCustomer between
RentalAgreement [*]
Customer [1]
end
constraints
context Truck inv positiveGasTankCapacity:
self.gasTankCapacity >= 0
context Truck inv positiveMileage:
self.mileage >= 0
context RentalAgreement inv positiveDepositPaid:
self.depositPaid >= 0
context RentalAgreement inv positiveQuotedDailyRate:
self.quotedDailyRate >= 0
context RentalAgreement inv positiveQuotedRatePerMile:
self.quotedRatePerMile >= 0 For the same category and model description, generate another instance that is structurally and semantically different from the previous ones Continue with the following description, creating the instance according to the syntax example and this specification:
In the picturesque city of Portland, Oregon, "Cascadia Rentals" provides efficient and reliable vehicle rental services to a mixture of eco-conscious locals and outdoorsy travelers. Nestled in the lively Pearl District, this rental office is noted for its dedication to sustainable transportation options and personalized customer service.
### RentalOffice Instance:
- **Name:** "Cascadia Rentals"
- **Number:** 560
- **Address:** "749 NW Portland St, Portland, OR 97209"
### Vehicle Instances:
1. **Truck:**
- **ID:** 6090
- **RegistrationState:** OREGON
- **LicensePlateNumber:** "OR3344"
- **VehicleTypeCode:** TRUCK
- **RegistrationLastMaintenanceDate:** "2023-11-01"
- **ExpirationDate:** "2024-11-01"
- **OdometerReading:** 35,000
- **GasTankCapacity:** 21.0
- **WorkingRadio:** True
- **Mileage:** 16
2. **Truck:**
- **ID:** 6091
- **RegistrationState:** CALIFORNIA
- **LicensePlateNumber:** "CA5588"
- **VehicleTypeCode:** TRUCK
- **RegistrationLastMaintenanceDate:** "2023-09-10"
- **ExpirationDate:** "2024-09-10"
- **OdometerReading:** 55,000
- **GasTankCapacity:** 27.5
- **WorkingRadio:** False
- **Mileage:** 14
3. **Covered Trailer:**
- **ID:** 7102
- **RegistrationState:** WASHINGTON
- **LicensePlateNumber:** "WA8923"
- **VehicleTypeCode:** COVERED_TRAILER
- **RegistrationLastMaintenanceDate:** "2023-08-22"
- **ExpirationDate:** "2024-08-22"
4. **Covered Trailer:**
- **ID:** 7110
- **RegistrationState:** IDAHO
- **LicensePlateNumber:** "ID1234"
- **VehicleTypeCode:** COVERED_TRAILER
- **RegistrationLastMaintenanceDate:** "2023-07-15"
- **ExpirationDate:** "2024-07-15"
### Customer Instances:
1. **Individual:**
- **Name:** "Liam Anderson"
- **Address:** "345 Elm St, Portland, OR 97210"
- **PoorRisk:** True
- **HomePhone:** "503-555-0377"
- **DriverLicenseState:** OREGON
- **DriverLicenseNumber:** 78904567
- **DriverLicenseExpirationDate:** "2026-09-19"
2. **Company:**
- **Name:** "Evergreen Adventures"
- **Address:** "112 Spruce Ave, Bend, OR 97702"
- **PoorRisk:** False
- **IdNumber:** 1015
3. **Company:**
- **Name:** "Sustainable Solutions LLC"
- **Address:** "678 Greenway Dr, Eugene, OR 97401"
- **PoorRisk:** True
- **IdNumber:** 3030
### RentalAgreement Instances:
1. **Rental Agreement for an Individual:**
- **Number:** 13004
- **RentalDate:** "2024-03-14"
- **AnticipatedDuration:** 3 (days)
- **DepositPaid:** 90.0
- **QuotedDailyRate:** 45.0
- **QuotedRatePerMile:** 0.50
- **OriginOffice:** "Cascadia Rentals"
- **DropOffOffice:** "Cascadia Rentals"
- **Vehicle:** Truck (ID: 6090)
- **Customer:** Individual (Liam Anderson)
2. **First Rental Agreement for Evergreen Adventures:**
- **Number:** 14007
- **RentalDate:** "2024-02-15"
- **AnticipatedDuration:** 10 (days)
- **DepositPaid:** 200.0
- **QuotedDailyRate:** 32.0
- **QuotedRatePerMile:** 0.25
- **OriginOffice:** "Cascadia Rentals"
- **DropOffOffice:** "Cascadia Rentals"
- **Vehicle:** Covered Trailer (ID: 7102)
- **Customer:** Company (Evergreen Adventures)
3. **Rental Agreement for Sustainable Solutions LLC:**
- **Number:** 15008
- **RentalDate:** "2024-04-05"
- **AnticipatedDuration:** 7 (days)
- **DepositPaid:** 150.0
- **QuotedDailyRate:** 28.0
- **QuotedRatePerMile:** 0.30
- **OriginOffice:** "Cascadia Rentals"
- **DropOffOffice:** "Cascadia Rentals"
- **Vehicle:** Covered Trailer (ID: 7110)
- **Customer:** Company (Sustainable Solutions LLC)
4. **Second Rental Agreement for Evergreen Adventures:**
- **Number:** 14009
- **RentalDate:** "2024-02-18"
- **AnticipatedDuration:** 14 (days)
- **DepositPaid:** 350.0
- **QuotedDailyRate:** 30.0
- **QuotedRatePerMile:** 0.40
- **OriginOffice:** "Cascadia Rentals"
- **DropOffOffice:** "Cascadia Rentals"
- **Vehicle:** Truck (ID: 6091)
- **Customer:** Company (Evergreen Adventures)
### Relationships:
- **RentalOfficeVehicle:**
- Cascadia Rentals manages Truck (ID: 6090), Truck (ID: 6091), Covered Trailer (ID: 7102), and Covered Trailer (ID: 7110).
- **RentalOfficeRentalAgreementOrigin:**
- Rental agreements 13004, 14007, 14009, and 15008 originate from Cascadia Rentals.
- **RentalOfficeRentalAgreementDrop:**
- Rental agreements 13004, 14007, 14009, and 15008 drop off at Cascadia Rentals.
- **RentalAgreementVehicle:**
- Rental agreement 13004 involves Truck (ID: 6090), rental agreement 14007 involves Covered Trailer (ID: 7102), rental agreement 15008 involves Covered Trailer (ID: 7110), and rental agreement 14009 involves Truck (ID: 6091).
- **RentalAgreementCustomer:**
- Rental agreement 13004 is associated with the individual Liam Anderson, rental agreements 14007 and 14009 are associated with Evergreen Adventures, and rental agreement 15008 is associated with Sustainable Solutions LLC. The last output is partially incorrect:
temp.soil> !truck6090.id := 6090
temp.soil> !truck6090.registrationState := #OR
<input>:1:0: generation of expression `#OR' failed, with following error:
<input>:1:32: Undefined enumeration literal `OR'.
temp.soil> !coveredTrailer7102.id := 7102
temp.soil> !coveredTrailer7102.registrationState := #WA
<input>:1:0: generation of expression `#WA' failed, with following error:
<input>:1:41: Undefined enumeration literal `WA'.
temp.soil> !coveredTrailer7110.id := 7110
temp.soil> !coveredTrailer7110.registrationState := #ID
<input>:1:0: generation of expression `#ID' failed, with following error:
<input>:1:41: Undefined enumeration literal `ID'.
temp.soil> !individualLiamAnderson.homePhone := '503-555-0377'
temp.soil> !individualLiamAnderson.driverLicenseState := #OR
<input>:1:0: generation of expression `#OR' failed, with following error:
<input>:1:46: Undefined enumeration literal `OR'.
Please provide the complete output corrected <domain_model>
model VehicleRental
dataType Date
operations
Date(date : String)
end
enum State {
AL,
AK,
AZ,
CA,
CO,
CT,
DE,
FL
}
enum VehicleTypeCode {
TRUCK,
TRUCK24,
TRUCK10,
COVERED_TRAILER,
OPEN_TRAILER
}
class RentalOffice
attributes
name : String
number : Integer
address : String
end
class Vehicle
attributes
id : Integer
registrationState : State
licensePlateNumber : String
vehicleTypeCode : VehicleTypeCode
registrationLastMaintenanceDate : Date
expirationDate : Date
end
class RentalAgreement
attributes
number : Integer
rentalDate : Date
anticipatedDuration : Integer
depositPaid : Real
quotedDailyRate : Real
quotedRatePerMile : Real
end
class Truck < Vehicle
attributes
odometerReading : Integer
gasTankCapacity : Real
workingRadio : Boolean
mileage : Integer
end
abstract class Customer
attributes
name : String
address : String
poorRisk : Boolean
end
class Individual < Customer
attributes
homePhone : String
driverLicenseState : State
driverLicenseNumber : Integer
driverLicenseExpirationDate : Date
end
class Company < Customer
attributes
idNumber : Integer
end
association RentalOfficeVehicle between
RentalOffice [1] role homeOffice
Vehicle [*]
end
association RentalOfficeRentalAgreementOrigin between
RentalOffice [1] role originatingRentalOffice
RentalAgreement [*] role originatingAgreement
end
association RentalOfficeRentalAgreementDrop between
RentalOffice [1] role droppoffRentalOffice
RentalAgreement [*] role dropoffAgreement
end
association RentalAgreementVehicle between
RentalAgreement [*]
Vehicle [1]
end
association RentalAgreementCustomer between
RentalAgreement [*]
Customer [1]
end
constraints
context Truck inv positiveGasTankCapacity:
self.gasTankCapacity >= 0
context Truck inv positiveMileage:
self.mileage >= 0
context RentalAgreement inv positiveDepositPaid:
self.depositPaid >= 0
context RentalAgreement inv positiveQuotedDailyRate:
self.quotedDailyRate >= 0
context RentalAgreement inv positiveQuotedRatePerMile:
self.quotedRatePerMile >= 0
</domain_model>
<object_model>
!new RentalOffice('officeCascadiaRentals')
!officeCascadiaRentals.name := 'Cascadia Rentals'
!officeCascadiaRentals.number := 560
!officeCascadiaRentals.address := '749 NW Portland St, Portland, OR 97209'
!new Truck('truck6090')
!truck6090.id := 6090
!truck6090.registrationState := #CA
!truck6090.licensePlateNumber := 'OR3344'
!truck6090.vehicleTypeCode := #TRUCK
!truck6090.registrationLastMaintenanceDate := Date('2023-11-01')
!truck6090.expirationDate := Date('2024-11-01')
!truck6090.odometerReading := 35000
!truck6090.gasTankCapacity := 21.0
!truck6090.workingRadio := true
!truck6090.mileage := 16
!new Truck('truck6091')
!truck6091.id := 6091
!truck6091.registrationState := #CA
!truck6091.licensePlateNumber := 'CA5588'
!truck6091.vehicleTypeCode := #TRUCK
!truck6091.registrationLastMaintenanceDate := Date('2023-09-10')
!truck6091.expirationDate := Date('2024-09-10')
!truck6091.odometerReading := 55000
!truck6091.gasTankCapacity := 27.5
!truck6091.workingRadio := false
!truck6091.mileage := 14
!new Vehicle('coveredTrailer7102')
!coveredTrailer7102.id := 7102
!coveredTrailer7102.registrationState := #CA
!coveredTrailer7102.licensePlateNumber := 'WA8923'
!coveredTrailer7102.vehicleTypeCode := #COVERED_TRAILER
!coveredTrailer7102.registrationLastMaintenanceDate := Date('2023-08-22')
!coveredTrailer7102.expirationDate := Date('2024-08-22')
!new Vehicle('coveredTrailer7110')
!coveredTrailer7110.id := 7110
!coveredTrailer7110.registrationState := #CA
!coveredTrailer7110.licensePlateNumber := 'ID1234'
!coveredTrailer7110.vehicleTypeCode := #COVERED_TRAILER
!coveredTrailer7110.registrationLastMaintenanceDate := Date('2023-07-15')
!coveredTrailer7110.expirationDate := Date('2024-07-15')
!new Individual('individualLiamAnderson')
!individualLiamAnderson.name := 'Liam Anderson'
!individualLiamAnderson.address := '345 Elm St, Portland, OR 97210'
!individualLiamAnderson.poorRisk := true
!individualLiamAnderson.homePhone := '503-555-0377'
!individualLiamAnderson.driverLicenseState := #CA
!individualLiamAnderson.driverLicenseNumber := 78904567
!individualLiamAnderson.driverLicenseExpirationDate := Date('2026-09-19')
!new Company('companyEvergreenAdventures')
!companyEvergreenAdventures.name := 'Evergreen Adventures'
!companyEvergreenAdventures.address := '112 Spruce Ave, Bend, OR 97702'
!companyEvergreenAdventures.poorRisk := false
!companyEvergreenAdventures.idNumber := 1015
!new Company('companySustainableSolutionsLLC')
!companySustainableSolutionsLLC.name := 'Sustainable Solutions LLC'
!companySustainableSolutionsLLC.address := '678 Greenway Dr, Eugene, OR 97401'
!companySustainableSolutionsLLC.poorRisk := true
!companySustainableSolutionsLLC.idNumber := 3030
!new RentalAgreement('rentalAgreement13004')
!rentalAgreement13004.number := 13004
!rentalAgreement13004.rentalDate := Date('2024-03-14')
!rentalAgreement13004.anticipatedDuration := 3
!rentalAgreement13004.depositPaid := 90.0
!rentalAgreement13004.quotedDailyRate := 45.0
!rentalAgreement13004.quotedRatePerMile := 0.50
!new RentalAgreement('rentalAgreement14007')
!rentalAgreement14007.number := 14007
!rentalAgreement14007.rentalDate := Date('2024-02-15')
!rentalAgreement14007.anticipatedDuration := 10
!rentalAgreement14007.depositPaid := 200.0
!rentalAgreement14007.quotedDailyRate := 32.0
!rentalAgreement14007.quotedRatePerMile := 0.25
!new RentalAgreement('rentalAgreement15008')
!rentalAgreement15008.number := 15008
!rentalAgreement15008.rentalDate := Date('2024-04-05')
!rentalAgreement15008.anticipatedDuration := 7
!rentalAgreement15008.depositPaid := 150.0
!rentalAgreement15008.quotedDailyRate := 28.0
!rentalAgreement15008.quotedRatePerMile := 0.30
!new RentalAgreement('rentalAgreement14009')
!rentalAgreement14009.number := 14009
!rentalAgreement14009.rentalDate := Date('2024-02-18')
!rentalAgreement14009.anticipatedDuration := 14
!rentalAgreement14009.depositPaid := 350.0
!rentalAgreement14009.quotedDailyRate := 30.0
!rentalAgreement14009.quotedRatePerMile := 0.40
!insert (officeCascadiaRentals, truck6090) into RentalOfficeVehicle
!insert (officeCascadiaRentals, truck6091) into RentalOfficeVehicle
!insert (officeCascadiaRentals, coveredTrailer7102) into RentalOfficeVehicle
!insert (officeCascadiaRentals, coveredTrailer7110) into RentalOfficeVehicle
!insert (officeCascadiaRentals, rentalAgreement13004) into RentalOfficeRentalAgreementOrigin
!insert (officeCascadiaRentals, rentalAgreement14007) into RentalOfficeRentalAgreementOrigin
!insert (officeCascadiaRentals, rentalAgreement15008) into RentalOfficeRentalAgreementOrigin
!insert (officeCascadiaRentals, rentalAgreement14009) into RentalOfficeRentalAgreementOrigin
!insert (officeCascadiaRentals, rentalAgreement13004) into RentalOfficeRentalAgreementDrop
!insert (officeCascadiaRentals, rentalAgreement14007) into RentalOfficeRentalAgreementDrop
!insert (officeCascadiaRentals, rentalAgreement15008) into RentalOfficeRentalAgreementDrop
!insert (officeCascadiaRentals, rentalAgreement14009) into RentalOfficeRentalAgreementDrop
!insert (rentalAgreement13004, truck6090) into RentalAgreementVehicle
!insert (rentalAgreement14007, coveredTrailer7102) into RentalAgreementVehicle
!insert (rentalAgreement15008, coveredTrailer7110) into RentalAgreementVehicle
!insert (rentalAgreement14009, truck6091) into RentalAgreementVehicle
!insert (rentalAgreement13004, individualLiamAnderson) into RentalAgreementCustomer
!insert (rentalAgreement14007, companyEvergreenAdventures) into RentalAgreementCustomer
!insert (rentalAgreement15008, companySustainableSolutionsLLC) into RentalAgreementCustomer
!insert (rentalAgreement14009, companyEvergreenAdventures) into RentalAgreementCustomer
</object_model> LLM as a Judge
The object model represents a highly plausible scenario. The instances properly reflect real-world values, such as accurate Oregon area codes (503) and zip codes for the cities listed. The chronological alignment of maintenance, expiration, and rental dates is completely logical, and combinations of durations, daily rates, and deposits are mathematically sound and standard for the rental industry. No physical or logical domain constraints are violated.
Metrics
Stats
Stats Breakdown of the total cost and elapsed time for generating the instances. - Elapsed Time = Console Time (ie. Processing Time + API Calls)
- Cost = (input tokens * input price) + (output tokens * output price)
- Elapsed Time = Console Time (ie. Processing Time + API Calls)
- Cost = (input tokens * input price) + (output tokens * output price)
| Total Cost | $0.39 |
Validation
Validation Measures the correctness of the instantiation using the USE check function. - Syntax = 1 - (Total Number of syntax errors [use check] / Total Number of lines [instance])
- Multiplicities = 1 - (Total Number of multiplicities errors [use check] / Total Number of relationships ([instance] !insert))
- Invariants = 1 - (Total Number of invariants errors [use check] / Total Number of invariants ([model] constraints))
- Syntax = 1 - (Total Number of syntax errors [use check] / Total Number of lines [instance])
- Multiplicities = 1 - (Total Number of multiplicities errors [use check] / Total Number of relationships ([instance] !insert))
- Invariants = 1 - (Total Number of invariants errors [use check] / Total Number of invariants ([model] constraints))
| Syntax | 0/106 |
| Multiplicities | 0/20 |
| Invariants | 0/5 |
Diversity
Diversity Measures the variability of the generated instances. Attributes (NumericEquals, StringEquals, StringLv): It identifies how much the LLM repeats specific values versus generating unique data points across instances (100%: Diverse, 0%: Repetitive). We group all generated attributes into bags (numeric and string) and then perform pairwise comparisons between every element to obtain. Structure (GED): Measures the Graph Edit Distance (GED) similarity between instances. Distribution (Shannon): Measures the entropy and evenness (balanced distribution) of the generated enum values. - NumericEquals = Total number of numeric attribute pairs with different values / Total number of possible pairs (n * (n - 1) / 2)
- StringEquals = Total number of string attribute pairs that are NOT exactly identical / Total number of possible pairs (n * (n - 1) / 2)
- StringLv = Sum of (Levenshtein Distance(a, b) / max(length(a), length(b))) for all string pairs / Total number of possible pairs (n * (n - 1) / 2)
- GED = Similarity = 1 - (GED / (0.5 * (GED_to_empty_A + GED_to_empty_B))). 1 = red = identical graphs, <=0.5 = green = different graphs. We consider as edit operations: Nodes, Edges, Node_Labels and Edge_Labels [https://github.com/a-coman/ged]
- Shannon (Active) = Entropy / log2(Number of unique groups actually generated). Measures how evenly the generated values are distributed, considering only the categories the LLM actually used.
- Shannon (All) = Entropy / log2(Total number of valid groups defined in the model). Measures how evenly the generated values are distributed against the full spectrum of all possible valid options defined in the .use file.
- NumericEquals = Total number of numeric attribute pairs with different values / Total number of possible pairs (n * (n - 1) / 2)
- StringEquals = Total number of string attribute pairs that are NOT exactly identical / Total number of possible pairs (n * (n - 1) / 2)
- StringLv = Sum of (Levenshtein Distance(a, b) / max(length(a), length(b))) for all string pairs / Total number of possible pairs (n * (n - 1) / 2)
- GED = Similarity = 1 - (GED / (0.5 * (GED_to_empty_A + GED_to_empty_B))). 1 = red = identical graphs, <=0.5 = green = different graphs. We consider as edit operations: Nodes, Edges, Node_Labels and Edge_Labels [https://github.com/a-coman/ged]
- Shannon (Active) = Entropy / log2(Number of unique groups actually generated). Measures how evenly the generated values are distributed, considering only the categories the LLM actually used.
- Shannon (All) = Entropy / log2(Total number of valid groups defined in the model). Measures how evenly the generated values are distributed against the full spectrum of all possible valid options defined in the .use file.
| Numeric | 99.8% |
| String Equals | 100.0% |
| String LV | 89.9% |
| Shannon (Active) | 0.000 ± 0.000 |
| Shannon (All) | 0.000 ± 0.000 |
Coverage
Model Coverage Measures the breadth of the instantiation. It answers: "How much of the structural blueprint (the model) was used?" - Classes = Total Unique Classes instantiated (!new) in the .soil / Total Number of classes (class) in the model .use
- Attributes = Total Unique Attributes instantiated (!Class.Attribute or !set) in the .soil / Total Number of attributes (attributes) in the model .use
- Relationships = Total Unique Relationships instantiated (!insert) in the .soil / Total Number of relationships (association, composition, aggregation) in the model .use
- Classes = Total Unique Classes instantiated (!new) in the .soil / Total Number of classes (class) in the model .use
- Attributes = Total Unique Attributes instantiated (!Class.Attribute or !set) in the .soil / Total Number of attributes (attributes) in the model .use
- Relationships = Total Unique Relationships instantiated (!insert) in the .soil / Total Number of relationships (association, composition, aggregation) in the model .use
| Classes | 100.0% |
| Attributes | 100.0% |
| Relationships | 100.0% |
Instantiation
Instance Instantiation Measures the depth or density of the data. It answers: "Of the objects the LLM decided to create, how many of their available 'slots' did it fill?" - Classes = Total Number of classes (!new) in the instance / Total possible that could have been instantiated (infinity)
- Attributes = Total Number of attributes (!Class.Attribute or !set) in the instance / Total possible that could have been instantiated (sum(number of classes instantiated of that type * Class.Attributes))
- Relationships = Total Number of relationships (!insert) in the instance / Total possible that could have been instantiated (infinity)
- Classes = Total Number of classes (!new) in the instance / Total possible that could have been instantiated (infinity)
- Attributes = Total Number of attributes (!Class.Attribute or !set) in the instance / Total possible that could have been instantiated (sum(number of classes instantiated of that type * Class.Attributes))
- Relationships = Total Number of relationships (!insert) in the instance / Total possible that could have been instantiated (infinity)
| Classes | 12/∞ |
| Attributes | 74/74 |
| Relationships | 20/∞ |
Viewer
!new RentalOffice('officeMetroShuttleRentals')
!officeMetroShuttleRentals.name := 'Metropolitan Shuttle Rentals'
!officeMetroShuttleRentals.number := 505
!officeMetroShuttleRentals.address := '1100 Urban Center Blvd, Metroville, NY 10001'
!new Vehicle('coveredTrailer90123')
!coveredTrailer90123.id := 90123
!coveredTrailer90123.registrationState := #CA
!coveredTrailer90123.licensePlateNumber := 'NY-567-UVW'
!coveredTrailer90123.vehicleTypeCode := #COVERED_TRAILER
!coveredTrailer90123.registrationLastMaintenanceDate := Date('2023-09-10')
!coveredTrailer90123.expirationDate := Date('2024-09-10')
!new Truck('truck90124')
!truck90124.id := 90124
!truck90124.registrationState := #CA
!truck90124.licensePlateNumber := 'NY-678-XYZ'
!truck90124.vehicleTypeCode := #TRUCK
!truck90124.registrationLastMaintenanceDate := Date('2023-10-15')
!truck90124.expirationDate := Date('2024-10-15')
!truck90124.odometerReading := 75000
!truck90124.gasTankCapacity := 70.0
!truck90124.workingRadio := true
!truck90124.mileage := 8
!new Individual('individualUrbanJohnson')
!individualUrbanJohnson.name := 'Urban Johnson'
!individualUrbanJohnson.address := '450 Cityscape Rd, Newtown, NJ 07601'
!individualUrbanJohnson.poorRisk := true
!individualUrbanJohnson.homePhone := '+1-201-555-0123'
!individualUrbanJohnson.driverLicenseState := #CA
!individualUrbanJohnson.driverLicenseNumber := 1456789012
!individualUrbanJohnson.driverLicenseExpirationDate := Date('2024-11-01')
!new Company('companyCityLogisticsPartners')
!companyCityLogisticsPartners.name := 'City Logistics Partners'
!companyCityLogisticsPartners.address := '902 Business Park, Suburbia, NJ 07083'
!companyCityLogisticsPartners.poorRisk := false
!companyCityLogisticsPartners.idNumber := 1122334455
!new RentalAgreement('rentalAgreement5009')
!rentalAgreement5009.number := 5009
!rentalAgreement5009.rentalDate := Date('2025-03-15')
!rentalAgreement5009.anticipatedDuration := 7
!rentalAgreement5009.depositPaid := 200.0
!rentalAgreement5009.quotedDailyRate := 90.0
!rentalAgreement5009.quotedRatePerMile := 2.2
!new RentalAgreement('rentalAgreement5010')
!rentalAgreement5010.number := 5010
!rentalAgreement5010.rentalDate := Date('2025-10-01')
!rentalAgreement5010.anticipatedDuration := 15
!rentalAgreement5010.depositPaid := 1200.0
!rentalAgreement5010.quotedDailyRate := 85.0
!rentalAgreement5010.quotedRatePerMile := 1.5
!insert (officeMetroShuttleRentals, coveredTrailer90123) into RentalOfficeVehicle
!insert (officeMetroShuttleRentals, truck90124) into RentalOfficeVehicle
!insert (officeMetroShuttleRentals, rentalAgreement5009) into RentalOfficeRentalAgreementOrigin
!insert (officeMetroShuttleRentals, rentalAgreement5010) into RentalOfficeRentalAgreementOrigin
!insert (officeMetroShuttleRentals, rentalAgreement5009) into RentalOfficeRentalAgreementDrop
!insert (officeMetroShuttleRentals, rentalAgreement5010) into RentalOfficeRentalAgreementDrop
!insert (rentalAgreement5009, coveredTrailer90123) into RentalAgreementVehicle
!insert (rentalAgreement5010, truck90124) into RentalAgreementVehicle
!insert (rentalAgreement5009, individualUrbanJohnson) into RentalAgreementCustomer
!insert (rentalAgreement5010, companyCityLogisticsPartners) into RentalAgreementCustomer model VehicleRental
dataType Date
operations
Date(date : String)
end
enum State {
AL,
AK,
AZ,
CA,
CO,
CT,
DE,
FL
}
enum VehicleTypeCode {
TRUCK,
TRUCK24,
TRUCK10,
COVERED_TRAILER,
OPEN_TRAILER
}
class RentalOffice
attributes
name : String
number : Integer
address : String
end
class Vehicle
attributes
id : Integer
registrationState : State
licensePlateNumber : String
vehicleTypeCode : VehicleTypeCode
registrationLastMaintenanceDate : Date
expirationDate : Date
end
class RentalAgreement
attributes
number : Integer
rentalDate : Date
anticipatedDuration : Integer
depositPaid : Real
quotedDailyRate : Real
quotedRatePerMile : Real
end
class Truck < Vehicle
attributes
odometerReading : Integer
gasTankCapacity : Real
workingRadio : Boolean
mileage : Integer
end
abstract class Customer
attributes
name : String
address : String
poorRisk : Boolean
end
class Individual < Customer
attributes
homePhone : String
driverLicenseState : State
driverLicenseNumber : Integer
driverLicenseExpirationDate : Date
end
class Company < Customer
attributes
idNumber : Integer
end
association RentalOfficeVehicle between
RentalOffice [1] role homeOffice
Vehicle [*]
end
association RentalOfficeRentalAgreementOrigin between
RentalOffice [1] role originatingRentalOffice
RentalAgreement [*] role originatingAgreement
end
association RentalOfficeRentalAgreementDrop between
RentalOffice [1] role droppoffRentalOffice
RentalAgreement [*] role dropoffAgreement
end
association RentalAgreementVehicle between
RentalAgreement [*]
Vehicle [1]
end
association RentalAgreementCustomer between
RentalAgreement [*]
Customer [1]
end
constraints
context Truck inv positiveGasTankCapacity:
self.gasTankCapacity >= 0
context Truck inv positiveMileage:
self.mileage >= 0
context RentalAgreement inv positiveDepositPaid:
self.depositPaid >= 0
context RentalAgreement inv positiveQuotedDailyRate:
self.quotedDailyRate >= 0
context RentalAgreement inv positiveQuotedRatePerMile:
self.quotedRatePerMile >= 0 You are tasked with analyzing conceptual models represented as class diagrams and expressed in the UML-based specification environment using its native syntax. You must adhere to the following requirements: - Use very clear language. - Do not overexplain, be concise. - Multiplicities must be very clear and easy to understand. You should follow the structure and requirements below: ## Description Start by explaining the overall structure and purpose of the model. ### Components Break down the components of the model (i.e., classes and attributes), describing each, their type and purpose. ## Relationships Describe the relationships between the components of the model, dependencies and multiplicities (i.e., minimum and maximum number of instances of one class that can be associated with instances of another class). Describe the multiplicities at both ends of each association. ## Invariants Define the invariants that apply to the model (i.e., those constraints that must be fulfilled). Your task is to generate a complete and diverse instance, in plain English, for a given category and based on a provided conceptual model description. The instance must adhere to these requirements: - Be self-contained: Include all required attributes, relationships, and related entities in full detail. - Conform to the model: Fulfill the constraints, multiplicities, relationships, and attributes defined in the class diagram model. - Understand the context: Ensure that its attributes and relationships are relevant. - Avoid duplication of instances: Take into consideration those instances previously built to avoid redundancy. - Semantic diversity: From a semantic point of view, incorporate varied scenarios, including regional, linguistic, or cultural differences. - Structural diversity: Include instances with different numbers of elements, different numbers of relationships and complexity, and create varied examples by changing entity attributes. You are tasked with creating instances of a conceptual model in the UML-based Specification Environment (USE). You will receive: 1. The UML class diagram that the instance follows. 2. A sample syntax of instances creation. 3. A description of the instance that needs to be created. Your goal is to generate these instances based on the provided description, adhering strictly to these requirements: - The output must be in plain text, with no additional comments, descriptions, or explanations. - Ensure that the created instance adheres to the provided description. - Follow the syntax sample provided, without deviation. - Take into account previously created instances to avoid using duplicate naming. <role>
You are an expert software and system modeler. You are able to assess the semantic quality of object models that have been created to conform to a domain model. The models are defined in USE (UML-based Specification Environment) and OCL (Object Constraint Language).
Your primary capability is "Semantic Reality Checking". You do not just check for syntactic correctness; you check for real-world plausibility and logical consistency within a given domain.
</role>
<context>
The user will provide two types of content:
1. **Domain Model (.use)**: A class diagram definition including classes, attributes, enums, relationships, multiplicities and roles.
2. **Object Model (.soil)**: An object model. This object model can be seen as a script composed of instructions for the creation of objects, relationships and setting attribute values (snapshot).
Your goal is to act as a judge to determine if the object model represents a **REALISTIC** scenario based on the domain model and common sense real-world logic.
</context>
<definitions>
- **Realistic**: The object model is syntactically correct AND semantically plausible (e.g., A 'Person' has an age between 0 and 120; a 'Car' has a positive price).
- **Unrealistic**: The object model contains contradictions, impossible physical values, or nonsensical relationships (e.g., A 'Person' is their own father; a 'Product' has a negative weight).
- **Doubtful**: You cannot determine whether the object model is realistic or not.
</definitions>
<instructions>
Follow this thinking process strictly before generating the final output:
1. **Analyze the Domain (.use)**: Understand the classes and what they represent in the real world.
2. **Analyze the Instances (.soil)**: Map the created objects to their classes. Look at the specific values assigned to attributes and the relationships created between objects.
3. **Evaluate Semantics**:
- Apply "Common Sense Knowledge" to the attribute values.
- Check cardinality and relationship logic beyond simple OCL constraints.
- Identify any outliers or logical fallacies.
4. **Determine Verdict**: Select one of the defined labels (Realistic/Unrealistic/Doubtful).
</instructions>
<constraints>
- **Tone**: Objective, Analytical, Technical.
- **Verbosity**: Low. Be direct.
- **Reasoning**: The "Why" section must be concise and specific, citing variable names, objects, or relationships when possible.
- Do not output the internal thinking process. Only output the final formatted result.
</constraints>
<output_format>
Structure your response exactly as follows:
**Response**: [Realistic | Unrealistic | Doubtful]
**Why**: [Concise explanation of your reasoning. If Unrealistic, specify the exact objects, values or relationships that break realism.]
</output_format>
<examples>
Example 1:
Input:
<domain_model>
class Person
attributes
age: Integer
end
class Pet
attributes
name: String
end
association Ownership between
Person [1] role owner
Pet [*] role pets
end
</domain_model>
<object_model>
!new Person('p1')
!p1.age := 250
!new Pet('pet1')
!pet1.name := 'Luna'
… 1.000 more pets creation …
!pet1000.name := 'Max'
!insert (p1, pet1) into Ownership
…1.000 more pets associated with p1 …
!insert (p1, pet1000) into Ownership
</object_model>
Output:
**Response**: Unrealistic
**Why**: The object 'p1' of class 'Person' has an age of 250, which exceeds the biologically plausible lifespan of a human. Although it is not plausible that 1 same person owns 1.000 pets.
Example 2:
Input:
<domain_model>
class Car
attributes
brand: String
end
class Person
attributes
name: String
end
association Ownership between
Person [1] role owner
Car [*] role cars
end
</domain_model>
<object_model>
!new Person('p1')
!p1.age := 19
!new Car('c1')
!c1.brand := 'Toyota'
!insert (p1, c1) into Ownership
</object_model>
Output:
**Response**: Realistic
**Why**: The object 'c1' has a valid, recognized real-world car brand assigned, and its plausible that a teenager has only one car.
Example 3:
Input:
<domain_model>
class Component
attributes
setting_val: Integer
config_mode: String
end
</domain_model>
<object_model>
!new Component('c1')
!c1.setting_val := 8080
!c1.config_mode := 'Legacy'
</object_model>
Output:
**Response**: Doubtful
**Why**: The class 'Component' and attribute 'setting_val' are generic and lack specific real-world semantic context. Without knowing what specific physical or software system this represents, it is impossible to determine if '8080' is a realistic value or an outlier.
</examples> Analyze the following UML class diagram:
model VehicleRental
dataType Date
operations
Date(date : String)
end
enum State {
AL,
AK,
AZ,
CA,
CO,
CT,
DE,
FL
}
enum VehicleTypeCode {
TRUCK,
TRUCK24,
TRUCK10,
COVERED_TRAILER,
OPEN_TRAILER
}
class RentalOffice
attributes
name : String
number : Integer
address : String
end
class Vehicle
attributes
id : Integer
registrationState : State
licensePlateNumber : String
vehicleTypeCode : VehicleTypeCode
registrationLastMaintenanceDate : Date
expirationDate : Date
end
class RentalAgreement
attributes
number : Integer
rentalDate : Date
anticipatedDuration : Integer
depositPaid : Real
quotedDailyRate : Real
quotedRatePerMile : Real
end
class Truck < Vehicle
attributes
odometerReading : Integer
gasTankCapacity : Real
workingRadio : Boolean
mileage : Integer
end
abstract class Customer
attributes
name : String
address : String
poorRisk : Boolean
end
class Individual < Customer
attributes
homePhone : String
driverLicenseState : State
driverLicenseNumber : Integer
driverLicenseExpirationDate : Date
end
class Company < Customer
attributes
idNumber : Integer
end
association RentalOfficeVehicle between
RentalOffice [1] role homeOffice
Vehicle [*]
end
association RentalOfficeRentalAgreementOrigin between
RentalOffice [1] role originatingRentalOffice
RentalAgreement [*] role originatingAgreement
end
association RentalOfficeRentalAgreementDrop between
RentalOffice [1] role droppoffRentalOffice
RentalAgreement [*] role dropoffAgreement
end
association RentalAgreementVehicle between
RentalAgreement [*]
Vehicle [1]
end
association RentalAgreementCustomer between
RentalAgreement [*]
Customer [1]
end
constraints
context Truck inv positiveGasTankCapacity:
self.gasTankCapacity >= 0
context Truck inv positiveMileage:
self.mileage >= 0
context RentalAgreement inv positiveDepositPaid:
self.depositPaid >= 0
context RentalAgreement inv positiveQuotedDailyRate:
self.quotedDailyRate >= 0
context RentalAgreement inv positiveQuotedRatePerMile:
self.quotedRatePerMile >= 0 For the same category and model description, generate another instance that is structurally and semantically different from the previous ones Continue with the following description, creating the instance according to the syntax example and this specification:
## Edge Case: Urban-Suburban Shuttle Services with Non-Standard Drop Points
### RentalOffice
#### Office5
- **name**: "Metropolitan Shuttle Rentals"
- **number**: 505
- **address**: "1100 Urban Center Blvd, Metroville, NY 10001"
### Vehicles
#### Vehicle6 (Covered Trailer)
- **id**: 90123
- **registrationState**: New York
- **licensePlateNumber**: "NY-567-UVW"
- **vehicleTypeCode**: COVERED_TRAILER
- **registrationLastMaintenanceDate**: "2023-09-10"
- **expirationDate**: "2024-09-10"
#### Vehicle7 (Truck)
- **id**: 90124
- **registrationState**: New York
- **licensePlateNumber**: "NY-678-XYZ"
- **vehicleTypeCode**: TRUCK
- **registrationLastMaintenanceDate**: "2023-10-15"
- **expirationDate**: "2024-10-15"
- **odometerReading**: 75000 (moderate usage reflective of city commuting)
- **gasTankCapacity**: 70.0 (optimized for frequent short hops)
- **workingRadio**: True
- **mileage**: 8 (adaptive for short but frequent urban trips)
### Customers
#### Individual5
- **name**: "Urban Johnson"
- **address**: "450 Cityscape Rd, Newtown, NJ 07601"
- **poorRisk**: True (due to frequent relocations for jobs, independent contractor)
- **homePhone**: "+1-201-555-0123"
- **driverLicenseState**: New Jersey
- **driverLicenseNumber**: 1456789012
- **driverLicenseExpirationDate**: "2024-11-01"
#### Company5
- **name**: "City Logistics Partners"
- **address**: "902 Business Park, Suburbia, NJ 07083"
- **poorRisk**: False (established logistics service provider)
- **idNumber**: 1122334455
### RentalAgreements
#### Agreement9
- **number**: 5009
- **rentalDate**: "2025-03-15"
- **anticipatedDuration**: 7 (short term, for localized project support)
- **depositPaid**: 200.0 (minimal due to local familiarity)
- **quotedDailyRate**: 90.0 (urban operational rate)
- **quotedRatePerMile**: 2.2 (rate accommodates local delivery operations)
- **originatingOffice**: Office5
- **dropOffOffice**: Office5
- **vehicle**: Vehicle6
- **customer**: Individual5
#### Agreement10
- **number**: 5010
- **rentalDate**: "2025-10-01"
- **anticipatedDuration**: 15 (mid-term for a suburban logistics project)
- **depositPaid**: 1200.0 (medium risk assessment for business logistics)
- **quotedDailyRate**: 85.0 (corporate advantage rate)
- **quotedRatePerMile**: 1.5 (encourages company logistics management)
- **originatingOffice**: Offsite location (outskirts)
- **dropOffOffice**: Office5
- **vehicle**: Vehicle7
- **customer**: Company5
### Explanation
This edge case introduces:
- A rental operation tailored to serve both urban shuttling and suburban logistics, demonstrating a seamless transition service that bridges city logistics needs with fast-paced city lifestyles.
- A Covered Trailer rental for an Individual, whose frequent relocations pose an unusual risk evaluation due to his independent contracting works.
- Structurally distinct due to the inclusion of an offsite pick-up location for the company, reflecting flexible logistical solutions and dynamic rental office operations that can extend beyond predefined office boundaries.
- The agreements illustrate complex scheduling and strategic resource allocation, showing urban-centric offerings that highlight the contrast between personal independent use and professional logistics-based services.
- The focus on urban and suburban connectivity provides a unique perspective on how rental services can innovate to cater to varied demands, balancing risks associated with two dissimilar customer needs within a bustling metropolitan framework. The last output is partially incorrect:
temp.soil> !coveredTrailer90123.id := 90123
temp.soil> !coveredTrailer90123.registrationState := #NY
<input>:1:0: generation of expression `#NY' failed, with following error:
<input>:1:42: Undefined enumeration literal `NY'.
temp.soil> !truck90124.id := 90124
temp.soil> !truck90124.registrationState := #NY
<input>:1:0: generation of expression `#NY' failed, with following error:
<input>:1:33: Undefined enumeration literal `NY'.
temp.soil> !individualUrbanJohnson.homePhone := '+1-201-555-0123'
temp.soil> !individualUrbanJohnson.driverLicenseState := #NJ
<input>:1:0: generation of expression `#NJ' failed, with following error:
<input>:1:46: Undefined enumeration literal `NJ'.
Please provide the complete output corrected The last output is partially incorrect:
checking structure...
Multiplicity constraint violation in association `RentalOfficeRentalAgreementOrigin':
Object `rentalAgreement5010' of class `RentalAgreement' is connected to 0 objects of class `RentalOffice'
at association end `originatingRentalOffice' but the multiplicity is specified as `1'.
Please provide the complete output corrected <domain_model>
model VehicleRental
dataType Date
operations
Date(date : String)
end
enum State {
AL,
AK,
AZ,
CA,
CO,
CT,
DE,
FL
}
enum VehicleTypeCode {
TRUCK,
TRUCK24,
TRUCK10,
COVERED_TRAILER,
OPEN_TRAILER
}
class RentalOffice
attributes
name : String
number : Integer
address : String
end
class Vehicle
attributes
id : Integer
registrationState : State
licensePlateNumber : String
vehicleTypeCode : VehicleTypeCode
registrationLastMaintenanceDate : Date
expirationDate : Date
end
class RentalAgreement
attributes
number : Integer
rentalDate : Date
anticipatedDuration : Integer
depositPaid : Real
quotedDailyRate : Real
quotedRatePerMile : Real
end
class Truck < Vehicle
attributes
odometerReading : Integer
gasTankCapacity : Real
workingRadio : Boolean
mileage : Integer
end
abstract class Customer
attributes
name : String
address : String
poorRisk : Boolean
end
class Individual < Customer
attributes
homePhone : String
driverLicenseState : State
driverLicenseNumber : Integer
driverLicenseExpirationDate : Date
end
class Company < Customer
attributes
idNumber : Integer
end
association RentalOfficeVehicle between
RentalOffice [1] role homeOffice
Vehicle [*]
end
association RentalOfficeRentalAgreementOrigin between
RentalOffice [1] role originatingRentalOffice
RentalAgreement [*] role originatingAgreement
end
association RentalOfficeRentalAgreementDrop between
RentalOffice [1] role droppoffRentalOffice
RentalAgreement [*] role dropoffAgreement
end
association RentalAgreementVehicle between
RentalAgreement [*]
Vehicle [1]
end
association RentalAgreementCustomer between
RentalAgreement [*]
Customer [1]
end
constraints
context Truck inv positiveGasTankCapacity:
self.gasTankCapacity >= 0
context Truck inv positiveMileage:
self.mileage >= 0
context RentalAgreement inv positiveDepositPaid:
self.depositPaid >= 0
context RentalAgreement inv positiveQuotedDailyRate:
self.quotedDailyRate >= 0
context RentalAgreement inv positiveQuotedRatePerMile:
self.quotedRatePerMile >= 0
</domain_model>
<object_model>
!new RentalOffice('officeMetroShuttleRentals')
!officeMetroShuttleRentals.name := 'Metropolitan Shuttle Rentals'
!officeMetroShuttleRentals.number := 505
!officeMetroShuttleRentals.address := '1100 Urban Center Blvd, Metroville, NY 10001'
!new Vehicle('coveredTrailer90123')
!coveredTrailer90123.id := 90123
!coveredTrailer90123.registrationState := #CA
!coveredTrailer90123.licensePlateNumber := 'NY-567-UVW'
!coveredTrailer90123.vehicleTypeCode := #COVERED_TRAILER
!coveredTrailer90123.registrationLastMaintenanceDate := Date('2023-09-10')
!coveredTrailer90123.expirationDate := Date('2024-09-10')
!new Truck('truck90124')
!truck90124.id := 90124
!truck90124.registrationState := #CA
!truck90124.licensePlateNumber := 'NY-678-XYZ'
!truck90124.vehicleTypeCode := #TRUCK
!truck90124.registrationLastMaintenanceDate := Date('2023-10-15')
!truck90124.expirationDate := Date('2024-10-15')
!truck90124.odometerReading := 75000
!truck90124.gasTankCapacity := 70.0
!truck90124.workingRadio := true
!truck90124.mileage := 8
!new Individual('individualUrbanJohnson')
!individualUrbanJohnson.name := 'Urban Johnson'
!individualUrbanJohnson.address := '450 Cityscape Rd, Newtown, NJ 07601'
!individualUrbanJohnson.poorRisk := true
!individualUrbanJohnson.homePhone := '+1-201-555-0123'
!individualUrbanJohnson.driverLicenseState := #CA
!individualUrbanJohnson.driverLicenseNumber := 1456789012
!individualUrbanJohnson.driverLicenseExpirationDate := Date('2024-11-01')
!new Company('companyCityLogisticsPartners')
!companyCityLogisticsPartners.name := 'City Logistics Partners'
!companyCityLogisticsPartners.address := '902 Business Park, Suburbia, NJ 07083'
!companyCityLogisticsPartners.poorRisk := false
!companyCityLogisticsPartners.idNumber := 1122334455
!new RentalAgreement('rentalAgreement5009')
!rentalAgreement5009.number := 5009
!rentalAgreement5009.rentalDate := Date('2025-03-15')
!rentalAgreement5009.anticipatedDuration := 7
!rentalAgreement5009.depositPaid := 200.0
!rentalAgreement5009.quotedDailyRate := 90.0
!rentalAgreement5009.quotedRatePerMile := 2.2
!new RentalAgreement('rentalAgreement5010')
!rentalAgreement5010.number := 5010
!rentalAgreement5010.rentalDate := Date('2025-10-01')
!rentalAgreement5010.anticipatedDuration := 15
!rentalAgreement5010.depositPaid := 1200.0
!rentalAgreement5010.quotedDailyRate := 85.0
!rentalAgreement5010.quotedRatePerMile := 1.5
!insert (officeMetroShuttleRentals, coveredTrailer90123) into RentalOfficeVehicle
!insert (officeMetroShuttleRentals, truck90124) into RentalOfficeVehicle
!insert (officeMetroShuttleRentals, rentalAgreement5009) into RentalOfficeRentalAgreementOrigin
!insert (officeMetroShuttleRentals, rentalAgreement5010) into RentalOfficeRentalAgreementOrigin
!insert (officeMetroShuttleRentals, rentalAgreement5009) into RentalOfficeRentalAgreementDrop
!insert (officeMetroShuttleRentals, rentalAgreement5010) into RentalOfficeRentalAgreementDrop
!insert (rentalAgreement5009, coveredTrailer90123) into RentalAgreementVehicle
!insert (rentalAgreement5010, truck90124) into RentalAgreementVehicle
!insert (rentalAgreement5009, individualUrbanJohnson) into RentalAgreementCustomer
!insert (rentalAgreement5010, companyCityLogisticsPartners) into RentalAgreementCustomer
</object_model> LLM as a Judge
1. Vehicles are being rented after their registration has expired: `coveredTrailer90123` and `truck90124` have `expirationDate`s in 2024, but are assigned to `RentalAgreement`s in 2025. 2. The customer `individualUrbanJohnson` is entering a rental agreement on 2025-03-15, but their `driverLicenseExpirationDate` is 2024-11-01 (expired). 3. There is a geographical mismatch: vehicles `coveredTrailer90123` and `truck90124` have a `registrationState` of `#CA` (California), but their `licensePlateNumber`s start with a "NY-" prefix.
Metrics
Stats
Stats Breakdown of the total cost and elapsed time for generating the instances. - Elapsed Time = Console Time (ie. Processing Time + API Calls)
- Cost = (input tokens * input price) + (output tokens * output price)
- Elapsed Time = Console Time (ie. Processing Time + API Calls)
- Cost = (input tokens * input price) + (output tokens * output price)
| Total Cost | $0.57 |
Validation
Validation Measures the correctness of the instantiation using the USE check function. - Syntax = 1 - (Total Number of syntax errors [use check] / Total Number of lines [instance])
- Multiplicities = 1 - (Total Number of multiplicities errors [use check] / Total Number of relationships ([instance] !insert))
- Invariants = 1 - (Total Number of invariants errors [use check] / Total Number of invariants ([model] constraints))
- Syntax = 1 - (Total Number of syntax errors [use check] / Total Number of lines [instance])
- Multiplicities = 1 - (Total Number of multiplicities errors [use check] / Total Number of relationships ([instance] !insert))
- Invariants = 1 - (Total Number of invariants errors [use check] / Total Number of invariants ([model] constraints))
| Syntax | 0/59 |
| Multiplicities | 0/10 |
| Invariants | 0/5 |
Diversity
Diversity Measures the variability of the generated instances. Attributes (NumericEquals, StringEquals, StringLv): It identifies how much the LLM repeats specific values versus generating unique data points across instances (100%: Diverse, 0%: Repetitive). We group all generated attributes into bags (numeric and string) and then perform pairwise comparisons between every element to obtain. Structure (GED): Measures the Graph Edit Distance (GED) similarity between instances. Distribution (Shannon): Measures the entropy and evenness (balanced distribution) of the generated enum values. - NumericEquals = Total number of numeric attribute pairs with different values / Total number of possible pairs (n * (n - 1) / 2)
- StringEquals = Total number of string attribute pairs that are NOT exactly identical / Total number of possible pairs (n * (n - 1) / 2)
- StringLv = Sum of (Levenshtein Distance(a, b) / max(length(a), length(b))) for all string pairs / Total number of possible pairs (n * (n - 1) / 2)
- GED = Similarity = 1 - (GED / (0.5 * (GED_to_empty_A + GED_to_empty_B))). 1 = red = identical graphs, <=0.5 = green = different graphs. We consider as edit operations: Nodes, Edges, Node_Labels and Edge_Labels [https://github.com/a-coman/ged]
- Shannon (Active) = Entropy / log2(Number of unique groups actually generated). Measures how evenly the generated values are distributed, considering only the categories the LLM actually used.
- Shannon (All) = Entropy / log2(Total number of valid groups defined in the model). Measures how evenly the generated values are distributed against the full spectrum of all possible valid options defined in the .use file.
- NumericEquals = Total number of numeric attribute pairs with different values / Total number of possible pairs (n * (n - 1) / 2)
- StringEquals = Total number of string attribute pairs that are NOT exactly identical / Total number of possible pairs (n * (n - 1) / 2)
- StringLv = Sum of (Levenshtein Distance(a, b) / max(length(a), length(b))) for all string pairs / Total number of possible pairs (n * (n - 1) / 2)
- GED = Similarity = 1 - (GED / (0.5 * (GED_to_empty_A + GED_to_empty_B))). 1 = red = identical graphs, <=0.5 = green = different graphs. We consider as edit operations: Nodes, Edges, Node_Labels and Edge_Labels [https://github.com/a-coman/ged]
- Shannon (Active) = Entropy / log2(Number of unique groups actually generated). Measures how evenly the generated values are distributed, considering only the categories the LLM actually used.
- Shannon (All) = Entropy / log2(Total number of valid groups defined in the model). Measures how evenly the generated values are distributed against the full spectrum of all possible valid options defined in the .use file.
| Numeric | 100.0% |
| String Equals | 100.0% |
| String LV | 89.4% |
| Shannon (Active) | 0.000 ± 0.000 |
| Shannon (All) | 0.000 ± 0.000 |
Coverage
Model Coverage Measures the breadth of the instantiation. It answers: "How much of the structural blueprint (the model) was used?" - Classes = Total Unique Classes instantiated (!new) in the .soil / Total Number of classes (class) in the model .use
- Attributes = Total Unique Attributes instantiated (!Class.Attribute or !set) in the .soil / Total Number of attributes (attributes) in the model .use
- Relationships = Total Unique Relationships instantiated (!insert) in the .soil / Total Number of relationships (association, composition, aggregation) in the model .use
- Classes = Total Unique Classes instantiated (!new) in the .soil / Total Number of classes (class) in the model .use
- Attributes = Total Unique Attributes instantiated (!Class.Attribute or !set) in the .soil / Total Number of attributes (attributes) in the model .use
- Relationships = Total Unique Relationships instantiated (!insert) in the .soil / Total Number of relationships (association, composition, aggregation) in the model .use
| Classes | 100.0% |
| Attributes | 100.0% |
| Relationships | 100.0% |
Instantiation
Instance Instantiation Measures the depth or density of the data. It answers: "Of the objects the LLM decided to create, how many of their available 'slots' did it fill?" - Classes = Total Number of classes (!new) in the instance / Total possible that could have been instantiated (infinity)
- Attributes = Total Number of attributes (!Class.Attribute or !set) in the instance / Total possible that could have been instantiated (sum(number of classes instantiated of that type * Class.Attributes))
- Relationships = Total Number of relationships (!insert) in the instance / Total possible that could have been instantiated (infinity)
- Classes = Total Number of classes (!new) in the instance / Total possible that could have been instantiated (infinity)
- Attributes = Total Number of attributes (!Class.Attribute or !set) in the instance / Total possible that could have been instantiated (sum(number of classes instantiated of that type * Class.Attributes))
- Relationships = Total Number of relationships (!insert) in the instance / Total possible that could have been instantiated (infinity)
| Classes | 7/∞ |
| Attributes | 42/42 |
| Relationships | 10/∞ |
Viewer
!new RentalOffice('officeNYCUptownDepot')
!officeNYCUptownDepot.name := 'New York City Uptown Depot'
!officeNYCUptownDepot.number := 505
!officeNYCUptownDepot.address := '252 Broadway, New York, NY'
!new Truck('truck7005')
!truck7005.id := 7005
!truck7005.registrationState := #CA
!truck7005.licensePlateNumber := 'NY4455IJ'
!truck7005.vehicleTypeCode := #TRUCK
!truck7005.odometerReading := 50456
!truck7005.gasTankCapacity := 20.5
!truck7005.workingRadio := true
!truck7005.mileage := 12
!truck7005.registrationLastMaintenanceDate := Date('2024-01-05')
!truck7005.expirationDate := Date('2023-12-31')
!new Individual('individualDerekColeman')
!individualDerekColeman.name := 'Derek Coleman'
!individualDerekColeman.address := '123 Harlem Ave, New York, NY'
!individualDerekColeman.poorRisk := true
!individualDerekColeman.homePhone := '(212) 555-7890'
!individualDerekColeman.driverLicenseState := #CA
!individualDerekColeman.driverLicenseNumber := 76543210
!individualDerekColeman.driverLicenseExpirationDate := Date('2023-11-30')
!new RentalAgreement('rentalAgreement9006')
!rentalAgreement9006.number := 9006
!rentalAgreement9006.rentalDate := Date('2023-11-25')
!rentalAgreement9006.anticipatedDuration := 10
!rentalAgreement9006.depositPaid := 50.0
!rentalAgreement9006.quotedDailyRate := 100.0
!rentalAgreement9006.quotedRatePerMile := 0.40
!insert (officeNYCUptownDepot, truck7005) into RentalOfficeVehicle
!insert (officeNYCUptownDepot, rentalAgreement9006) into RentalOfficeRentalAgreementOrigin
!insert (officeNYCUptownDepot, rentalAgreement9006) into RentalOfficeRentalAgreementDrop
!insert (rentalAgreement9006, truck7005) into RentalAgreementVehicle
!insert (rentalAgreement9006, individualDerekColeman) into RentalAgreementCustomer model VehicleRental
dataType Date
operations
Date(date : String)
end
enum State {
AL,
AK,
AZ,
CA,
CO,
CT,
DE,
FL
}
enum VehicleTypeCode {
TRUCK,
TRUCK24,
TRUCK10,
COVERED_TRAILER,
OPEN_TRAILER
}
class RentalOffice
attributes
name : String
number : Integer
address : String
end
class Vehicle
attributes
id : Integer
registrationState : State
licensePlateNumber : String
vehicleTypeCode : VehicleTypeCode
registrationLastMaintenanceDate : Date
expirationDate : Date
end
class RentalAgreement
attributes
number : Integer
rentalDate : Date
anticipatedDuration : Integer
depositPaid : Real
quotedDailyRate : Real
quotedRatePerMile : Real
end
class Truck < Vehicle
attributes
odometerReading : Integer
gasTankCapacity : Real
workingRadio : Boolean
mileage : Integer
end
abstract class Customer
attributes
name : String
address : String
poorRisk : Boolean
end
class Individual < Customer
attributes
homePhone : String
driverLicenseState : State
driverLicenseNumber : Integer
driverLicenseExpirationDate : Date
end
class Company < Customer
attributes
idNumber : Integer
end
association RentalOfficeVehicle between
RentalOffice [1] role homeOffice
Vehicle [*]
end
association RentalOfficeRentalAgreementOrigin between
RentalOffice [1] role originatingRentalOffice
RentalAgreement [*] role originatingAgreement
end
association RentalOfficeRentalAgreementDrop between
RentalOffice [1] role droppoffRentalOffice
RentalAgreement [*] role dropoffAgreement
end
association RentalAgreementVehicle between
RentalAgreement [*]
Vehicle [1]
end
association RentalAgreementCustomer between
RentalAgreement [*]
Customer [1]
end
constraints
context Truck inv positiveGasTankCapacity:
self.gasTankCapacity >= 0
context Truck inv positiveMileage:
self.mileage >= 0
context RentalAgreement inv positiveDepositPaid:
self.depositPaid >= 0
context RentalAgreement inv positiveQuotedDailyRate:
self.quotedDailyRate >= 0
context RentalAgreement inv positiveQuotedRatePerMile:
self.quotedRatePerMile >= 0 You are tasked with analyzing conceptual models represented as class diagrams and expressed in the UML-based specification environment using its native syntax. You must adhere to the following requirements: - Use very clear language. - Do not overexplain, be concise. - Multiplicities must be very clear and easy to understand. You should follow the structure and requirements below: ## Description Start by explaining the overall structure and purpose of the model. ### Components Break down the components of the model (i.e., classes and attributes), describing each, their type and purpose. ## Relationships Describe the relationships between the components of the model, dependencies and multiplicities (i.e., minimum and maximum number of instances of one class that can be associated with instances of another class). Describe the multiplicities at both ends of each association. ## Invariants Define the invariants that apply to the model (i.e., those constraints that must be fulfilled). Your task is to generate a complete and diverse instance, in plain English, for a given category and based on a provided conceptual model description. The instance must adhere to these requirements: - Be self-contained: Include all required attributes, relationships, and related entities in full detail. - Conform to the model: Fulfill the constraints, multiplicities, relationships, and attributes defined in the class diagram model. - Understand the context: Ensure that its attributes and relationships are relevant. - Avoid duplication of instances: Take into consideration those instances previously built to avoid redundancy. - Semantic diversity: From a semantic point of view, incorporate varied scenarios, including regional, linguistic, or cultural differences. - Structural diversity: Include instances with different numbers of elements, different numbers of relationships and complexity, and create varied examples by changing entity attributes. You are tasked with creating instances of a conceptual model in the UML-based Specification Environment (USE). You will receive: 1. The UML class diagram that the instance follows. 2. A sample syntax of instances creation. 3. A description of the instance that needs to be created. Your goal is to generate these instances based on the provided description, adhering strictly to these requirements: - The output must be in plain text, with no additional comments, descriptions, or explanations. - Ensure that the created instance adheres to the provided description. - Follow the syntax sample provided, without deviation. - Take into account previously created instances to avoid using duplicate naming. <role>
You are an expert software and system modeler. You are able to assess the semantic quality of object models that have been created to conform to a domain model. The models are defined in USE (UML-based Specification Environment) and OCL (Object Constraint Language).
Your primary capability is "Semantic Reality Checking". You do not just check for syntactic correctness; you check for real-world plausibility and logical consistency within a given domain.
</role>
<context>
The user will provide two types of content:
1. **Domain Model (.use)**: A class diagram definition including classes, attributes, enums, relationships, multiplicities and roles.
2. **Object Model (.soil)**: An object model. This object model can be seen as a script composed of instructions for the creation of objects, relationships and setting attribute values (snapshot).
Your goal is to act as a judge to determine if the object model represents a **REALISTIC** scenario based on the domain model and common sense real-world logic.
</context>
<definitions>
- **Realistic**: The object model is syntactically correct AND semantically plausible (e.g., A 'Person' has an age between 0 and 120; a 'Car' has a positive price).
- **Unrealistic**: The object model contains contradictions, impossible physical values, or nonsensical relationships (e.g., A 'Person' is their own father; a 'Product' has a negative weight).
- **Doubtful**: You cannot determine whether the object model is realistic or not.
</definitions>
<instructions>
Follow this thinking process strictly before generating the final output:
1. **Analyze the Domain (.use)**: Understand the classes and what they represent in the real world.
2. **Analyze the Instances (.soil)**: Map the created objects to their classes. Look at the specific values assigned to attributes and the relationships created between objects.
3. **Evaluate Semantics**:
- Apply "Common Sense Knowledge" to the attribute values.
- Check cardinality and relationship logic beyond simple OCL constraints.
- Identify any outliers or logical fallacies.
4. **Determine Verdict**: Select one of the defined labels (Realistic/Unrealistic/Doubtful).
</instructions>
<constraints>
- **Tone**: Objective, Analytical, Technical.
- **Verbosity**: Low. Be direct.
- **Reasoning**: The "Why" section must be concise and specific, citing variable names, objects, or relationships when possible.
- Do not output the internal thinking process. Only output the final formatted result.
</constraints>
<output_format>
Structure your response exactly as follows:
**Response**: [Realistic | Unrealistic | Doubtful]
**Why**: [Concise explanation of your reasoning. If Unrealistic, specify the exact objects, values or relationships that break realism.]
</output_format>
<examples>
Example 1:
Input:
<domain_model>
class Person
attributes
age: Integer
end
class Pet
attributes
name: String
end
association Ownership between
Person [1] role owner
Pet [*] role pets
end
</domain_model>
<object_model>
!new Person('p1')
!p1.age := 250
!new Pet('pet1')
!pet1.name := 'Luna'
… 1.000 more pets creation …
!pet1000.name := 'Max'
!insert (p1, pet1) into Ownership
…1.000 more pets associated with p1 …
!insert (p1, pet1000) into Ownership
</object_model>
Output:
**Response**: Unrealistic
**Why**: The object 'p1' of class 'Person' has an age of 250, which exceeds the biologically plausible lifespan of a human. Although it is not plausible that 1 same person owns 1.000 pets.
Example 2:
Input:
<domain_model>
class Car
attributes
brand: String
end
class Person
attributes
name: String
end
association Ownership between
Person [1] role owner
Car [*] role cars
end
</domain_model>
<object_model>
!new Person('p1')
!p1.age := 19
!new Car('c1')
!c1.brand := 'Toyota'
!insert (p1, c1) into Ownership
</object_model>
Output:
**Response**: Realistic
**Why**: The object 'c1' has a valid, recognized real-world car brand assigned, and its plausible that a teenager has only one car.
Example 3:
Input:
<domain_model>
class Component
attributes
setting_val: Integer
config_mode: String
end
</domain_model>
<object_model>
!new Component('c1')
!c1.setting_val := 8080
!c1.config_mode := 'Legacy'
</object_model>
Output:
**Response**: Doubtful
**Why**: The class 'Component' and attribute 'setting_val' are generic and lack specific real-world semantic context. Without knowing what specific physical or software system this represents, it is impossible to determine if '8080' is a realistic value or an outlier.
</examples> Analyze the following UML class diagram:
model VehicleRental
dataType Date
operations
Date(date : String)
end
enum State {
AL,
AK,
AZ,
CA,
CO,
CT,
DE,
FL
}
enum VehicleTypeCode {
TRUCK,
TRUCK24,
TRUCK10,
COVERED_TRAILER,
OPEN_TRAILER
}
class RentalOffice
attributes
name : String
number : Integer
address : String
end
class Vehicle
attributes
id : Integer
registrationState : State
licensePlateNumber : String
vehicleTypeCode : VehicleTypeCode
registrationLastMaintenanceDate : Date
expirationDate : Date
end
class RentalAgreement
attributes
number : Integer
rentalDate : Date
anticipatedDuration : Integer
depositPaid : Real
quotedDailyRate : Real
quotedRatePerMile : Real
end
class Truck < Vehicle
attributes
odometerReading : Integer
gasTankCapacity : Real
workingRadio : Boolean
mileage : Integer
end
abstract class Customer
attributes
name : String
address : String
poorRisk : Boolean
end
class Individual < Customer
attributes
homePhone : String
driverLicenseState : State
driverLicenseNumber : Integer
driverLicenseExpirationDate : Date
end
class Company < Customer
attributes
idNumber : Integer
end
association RentalOfficeVehicle between
RentalOffice [1] role homeOffice
Vehicle [*]
end
association RentalOfficeRentalAgreementOrigin between
RentalOffice [1] role originatingRentalOffice
RentalAgreement [*] role originatingAgreement
end
association RentalOfficeRentalAgreementDrop between
RentalOffice [1] role droppoffRentalOffice
RentalAgreement [*] role dropoffAgreement
end
association RentalAgreementVehicle between
RentalAgreement [*]
Vehicle [1]
end
association RentalAgreementCustomer between
RentalAgreement [*]
Customer [1]
end
constraints
context Truck inv positiveGasTankCapacity:
self.gasTankCapacity >= 0
context Truck inv positiveMileage:
self.mileage >= 0
context RentalAgreement inv positiveDepositPaid:
self.depositPaid >= 0
context RentalAgreement inv positiveQuotedDailyRate:
self.quotedDailyRate >= 0
context RentalAgreement inv positiveQuotedRatePerMile:
self.quotedRatePerMile >= 0 For the same category and model description, generate another instance that is structurally and semantically different from the previous ones Continue with the following description, creating the instance according to the syntax example and this specification:
## Scenario: Overconstraint Detection in VehicleRental System
### Rental Office
- **Name:** New York City Uptown Depot
- **Number:** 505
- **Address:** 252 Broadway, New York, NY
### Vehicles
#### Truck (Misaligned Maintenance and Registration Dates)
- **ID:** 7005
- **Registration State:** New York
- **License Plate Number:** NY4455IJ
- **Vehicle Type Code:** TRUCK
- **Odometer Reading:** 50,456 miles
- **Gas Tank Capacity:** 20.5 gallons
- **Working Radio:** True
- **Mileage:** 12 miles per gallon
- **Registration Last Maintenance Date:** 2024-01-05 (Future date violation)
- **Expiration Date:** 2023-12-31
### Customers
#### Individual (High Risk Violation)
- **Name:** Derek Coleman
- **Address:** 123 Harlem Ave, New York, NY
- **Poor Risk:** True
- **Home Phone:** (212) 555-7890
- **Driver License State:** New York
- **Driver License Number:** 76543210
- **Driver License Expiration Date:** 2023-11-30
### Rental Agreements
#### High-Risk Factor Overlook and Future Maintenance Error
- **Number:** 9006
- **Rental Date:** 2023-11-25
- **Anticipated Duration:** 10 days
- **Deposit Paid:** 50.00 (Unusually low for a high-risk customer)
- **Quoted Daily Rate:** 100.00
- **Quoted Rate Per Mile:** 0.40
### Relationships
- **RentalOfficeVehicle:**
- Rental Office: New York City Uptown Depot
- Vehicle: Truck with ID 7005
- **RentalOfficeRentalAgreementOrigin:**
- Rental Office: New York City Uptown Depot
- Rental Agreement: Number 9006
- **RentalOfficeRentalAgreementDrop:**
- Rental Office: New York City Uptown Depot
- Rental Agreement: Number 9006
- **RentalAgreementVehicle:**
- Rental Agreement: Number 9006
- Vehicle: Truck with ID 7005
- **RentalAgreementCustomer:**
- Rental Agreement: Number 9006
- Customer: Derek Coleman
### Description of Overconstraint
In this instance, the vehicle’s maintenance date is erroneously set to a future date relative to its registration expiration, defying logic as scheduled maintenance cannot precede known registration deadlines. It showcases how discrepancies in maintenance scheduling can signal unrealistic operational scenarios that do not conform to practical vehicle rental cycles. Additionally, renting to a high-risk customer with infeasibly low deposit escalates the violation, prompting a critical analysis of risk management policies - highlighting constraints which, if overly lenient in practice, expose businesses to financial exposure contrary to their risk assessments. This example encourages the system to enforce realistic policy and maintenance oversight in rental contracts. The last output is partially incorrect:
temp.soil> !truck7005.id := 7005
temp.soil> !truck7005.registrationState := #NY
<input>:1:0: generation of expression `#NY' failed, with following error:
<input>:1:32: Undefined enumeration literal `NY'.
temp.soil> !individualDerekColeman.homePhone := '(212) 555-7890'
temp.soil> !individualDerekColeman.driverLicenseState := #NY
<input>:1:0: generation of expression `#NY' failed, with following error:
<input>:1:46: Undefined enumeration literal `NY'.
Please provide the complete output corrected <domain_model>
model VehicleRental
dataType Date
operations
Date(date : String)
end
enum State {
AL,
AK,
AZ,
CA,
CO,
CT,
DE,
FL
}
enum VehicleTypeCode {
TRUCK,
TRUCK24,
TRUCK10,
COVERED_TRAILER,
OPEN_TRAILER
}
class RentalOffice
attributes
name : String
number : Integer
address : String
end
class Vehicle
attributes
id : Integer
registrationState : State
licensePlateNumber : String
vehicleTypeCode : VehicleTypeCode
registrationLastMaintenanceDate : Date
expirationDate : Date
end
class RentalAgreement
attributes
number : Integer
rentalDate : Date
anticipatedDuration : Integer
depositPaid : Real
quotedDailyRate : Real
quotedRatePerMile : Real
end
class Truck < Vehicle
attributes
odometerReading : Integer
gasTankCapacity : Real
workingRadio : Boolean
mileage : Integer
end
abstract class Customer
attributes
name : String
address : String
poorRisk : Boolean
end
class Individual < Customer
attributes
homePhone : String
driverLicenseState : State
driverLicenseNumber : Integer
driverLicenseExpirationDate : Date
end
class Company < Customer
attributes
idNumber : Integer
end
association RentalOfficeVehicle between
RentalOffice [1] role homeOffice
Vehicle [*]
end
association RentalOfficeRentalAgreementOrigin between
RentalOffice [1] role originatingRentalOffice
RentalAgreement [*] role originatingAgreement
end
association RentalOfficeRentalAgreementDrop between
RentalOffice [1] role droppoffRentalOffice
RentalAgreement [*] role dropoffAgreement
end
association RentalAgreementVehicle between
RentalAgreement [*]
Vehicle [1]
end
association RentalAgreementCustomer between
RentalAgreement [*]
Customer [1]
end
constraints
context Truck inv positiveGasTankCapacity:
self.gasTankCapacity >= 0
context Truck inv positiveMileage:
self.mileage >= 0
context RentalAgreement inv positiveDepositPaid:
self.depositPaid >= 0
context RentalAgreement inv positiveQuotedDailyRate:
self.quotedDailyRate >= 0
context RentalAgreement inv positiveQuotedRatePerMile:
self.quotedRatePerMile >= 0
</domain_model>
<object_model>
!new RentalOffice('officeNYCUptownDepot')
!officeNYCUptownDepot.name := 'New York City Uptown Depot'
!officeNYCUptownDepot.number := 505
!officeNYCUptownDepot.address := '252 Broadway, New York, NY'
!new Truck('truck7005')
!truck7005.id := 7005
!truck7005.registrationState := #CA
!truck7005.licensePlateNumber := 'NY4455IJ'
!truck7005.vehicleTypeCode := #TRUCK
!truck7005.odometerReading := 50456
!truck7005.gasTankCapacity := 20.5
!truck7005.workingRadio := true
!truck7005.mileage := 12
!truck7005.registrationLastMaintenanceDate := Date('2024-01-05')
!truck7005.expirationDate := Date('2023-12-31')
!new Individual('individualDerekColeman')
!individualDerekColeman.name := 'Derek Coleman'
!individualDerekColeman.address := '123 Harlem Ave, New York, NY'
!individualDerekColeman.poorRisk := true
!individualDerekColeman.homePhone := '(212) 555-7890'
!individualDerekColeman.driverLicenseState := #CA
!individualDerekColeman.driverLicenseNumber := 76543210
!individualDerekColeman.driverLicenseExpirationDate := Date('2023-11-30')
!new RentalAgreement('rentalAgreement9006')
!rentalAgreement9006.number := 9006
!rentalAgreement9006.rentalDate := Date('2023-11-25')
!rentalAgreement9006.anticipatedDuration := 10
!rentalAgreement9006.depositPaid := 50.0
!rentalAgreement9006.quotedDailyRate := 100.0
!rentalAgreement9006.quotedRatePerMile := 0.40
!insert (officeNYCUptownDepot, truck7005) into RentalOfficeVehicle
!insert (officeNYCUptownDepot, rentalAgreement9006) into RentalOfficeRentalAgreementOrigin
!insert (officeNYCUptownDepot, rentalAgreement9006) into RentalOfficeRentalAgreementDrop
!insert (rentalAgreement9006, truck7005) into RentalAgreementVehicle
!insert (rentalAgreement9006, individualDerekColeman) into RentalAgreementCustomer
</object_model> LLM as a Judge
The object 'individualDerekColeman' has a 'driverLicenseExpirationDate' of '2023-11-30', which occurs directly in the middle of their 10-day rental period starting on '2023-11-25'. Real-world rental companies do not rent vehicles to drivers whose license will expire before the return date. Additionally, 'truck7005' contradictorily specifies a California registration state (#CA) but a New York license plate string ('NY4455IJ').
Metrics
Stats
Stats Breakdown of the total cost and elapsed time for generating the instances. - Elapsed Time = Console Time (ie. Processing Time + API Calls)
- Cost = (input tokens * input price) + (output tokens * output price)
- Elapsed Time = Console Time (ie. Processing Time + API Calls)
- Cost = (input tokens * input price) + (output tokens * output price)
| Total Cost | $0.30 |
Validation
Validation Measures the correctness of the instantiation using the USE check function. - Syntax = 1 - (Total Number of syntax errors [use check] / Total Number of lines [instance])
- Multiplicities = 1 - (Total Number of multiplicities errors [use check] / Total Number of relationships ([instance] !insert))
- Invariants = 1 - (Total Number of invariants errors [use check] / Total Number of invariants ([model] constraints))
- Syntax = 1 - (Total Number of syntax errors [use check] / Total Number of lines [instance])
- Multiplicities = 1 - (Total Number of multiplicities errors [use check] / Total Number of relationships ([instance] !insert))
- Invariants = 1 - (Total Number of invariants errors [use check] / Total Number of invariants ([model] constraints))
| Syntax | 0/35 |
| Multiplicities | 0/5 |
| Invariants | 0/5 |
Diversity
Diversity Measures the variability of the generated instances. Attributes (NumericEquals, StringEquals, StringLv): It identifies how much the LLM repeats specific values versus generating unique data points across instances (100%: Diverse, 0%: Repetitive). We group all generated attributes into bags (numeric and string) and then perform pairwise comparisons between every element to obtain. Structure (GED): Measures the Graph Edit Distance (GED) similarity between instances. Distribution (Shannon): Measures the entropy and evenness (balanced distribution) of the generated enum values. - NumericEquals = Total number of numeric attribute pairs with different values / Total number of possible pairs (n * (n - 1) / 2)
- StringEquals = Total number of string attribute pairs that are NOT exactly identical / Total number of possible pairs (n * (n - 1) / 2)
- StringLv = Sum of (Levenshtein Distance(a, b) / max(length(a), length(b))) for all string pairs / Total number of possible pairs (n * (n - 1) / 2)
- GED = Similarity = 1 - (GED / (0.5 * (GED_to_empty_A + GED_to_empty_B))). 1 = red = identical graphs, <=0.5 = green = different graphs. We consider as edit operations: Nodes, Edges, Node_Labels and Edge_Labels [https://github.com/a-coman/ged]
- Shannon (Active) = Entropy / log2(Number of unique groups actually generated). Measures how evenly the generated values are distributed, considering only the categories the LLM actually used.
- Shannon (All) = Entropy / log2(Total number of valid groups defined in the model). Measures how evenly the generated values are distributed against the full spectrum of all possible valid options defined in the .use file.
- NumericEquals = Total number of numeric attribute pairs with different values / Total number of possible pairs (n * (n - 1) / 2)
- StringEquals = Total number of string attribute pairs that are NOT exactly identical / Total number of possible pairs (n * (n - 1) / 2)
- StringLv = Sum of (Levenshtein Distance(a, b) / max(length(a), length(b))) for all string pairs / Total number of possible pairs (n * (n - 1) / 2)
- GED = Similarity = 1 - (GED / (0.5 * (GED_to_empty_A + GED_to_empty_B))). 1 = red = identical graphs, <=0.5 = green = different graphs. We consider as edit operations: Nodes, Edges, Node_Labels and Edge_Labels [https://github.com/a-coman/ged]
- Shannon (Active) = Entropy / log2(Number of unique groups actually generated). Measures how evenly the generated values are distributed, considering only the categories the LLM actually used.
- Shannon (All) = Entropy / log2(Total number of valid groups defined in the model). Measures how evenly the generated values are distributed against the full spectrum of all possible valid options defined in the .use file.
| Numeric | 100.0% |
| String Equals | 100.0% |
| String LV | 86.8% |
| Shannon (Active) | 0.000 ± 0.000 |
| Shannon (All) | 0.000 ± 0.000 |
Coverage
Model Coverage Measures the breadth of the instantiation. It answers: "How much of the structural blueprint (the model) was used?" - Classes = Total Unique Classes instantiated (!new) in the .soil / Total Number of classes (class) in the model .use
- Attributes = Total Unique Attributes instantiated (!Class.Attribute or !set) in the .soil / Total Number of attributes (attributes) in the model .use
- Relationships = Total Unique Relationships instantiated (!insert) in the .soil / Total Number of relationships (association, composition, aggregation) in the model .use
- Classes = Total Unique Classes instantiated (!new) in the .soil / Total Number of classes (class) in the model .use
- Attributes = Total Unique Attributes instantiated (!Class.Attribute or !set) in the .soil / Total Number of attributes (attributes) in the model .use
- Relationships = Total Unique Relationships instantiated (!insert) in the .soil / Total Number of relationships (association, composition, aggregation) in the model .use
| Classes | 66.7% |
| Attributes | 72.2% |
| Relationships | 100.0% |
Uncovered Items 12
Show all 10 attributes
Instantiation
Instance Instantiation Measures the depth or density of the data. It answers: "Of the objects the LLM decided to create, how many of their available 'slots' did it fill?" - Classes = Total Number of classes (!new) in the instance / Total possible that could have been instantiated (infinity)
- Attributes = Total Number of attributes (!Class.Attribute or !set) in the instance / Total possible that could have been instantiated (sum(number of classes instantiated of that type * Class.Attributes))
- Relationships = Total Number of relationships (!insert) in the instance / Total possible that could have been instantiated (infinity)
- Classes = Total Number of classes (!new) in the instance / Total possible that could have been instantiated (infinity)
- Attributes = Total Number of attributes (!Class.Attribute or !set) in the instance / Total possible that could have been instantiated (sum(number of classes instantiated of that type * Class.Attributes))
- Relationships = Total Number of relationships (!insert) in the instance / Total possible that could have been instantiated (infinity)
| Classes | 4/∞ |
| Attributes | 26/26 |
| Relationships | 5/∞ |