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Using UML for Modeling Procedural Legal Rules

This document describes research on using the Unified Modeling Language (UML) to model procedural legal rules, as demonstrated through a study of Luxembourg's tax law. Key points: - Researchers conducted a grounded theory study of Luxembourg tax law articles to identify common meta-concepts like decisions and operations. - They developed a UML profile customized for modeling legal rules and capturing information requirements. This profile stereotypes activity modeling elements and includes consistency constraints. - The profile is demonstrated by modeling an example article on commuting expense deductions using decisions, operations, and other concepts from the profile. Iterations and nested calculations are also represented.

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Using UML for Modeling Procedural Legal Rules Approach and a Study of Luxembourg’s Tax Law! Ghanem Soltana Elizabeta Fourneret Morayo Adedjouma ! Mehrdad Sabetzadeh Lionel Briand SsoftwareV verificVation & va.lidlaution University of Luxembourg, Luxembourg!
How did this work come about? • Collaboration with Government of Luxembourg • CTIE: Government’s IT Centre • ACD: Tax Administration Department • New tax system under development • System needs to be compliant with the law 2
Focus of the talk:! What needs to be modeled? Yes No Context and motivation 3 Test cases Actual software system ✗ Traces to Traces to Input to Input to Analyzable interpretation of the law Actual result Simulated result Generates Results match? Impact of fiscal decisions Simulates What language to use? What methodology to apply? Tax Law
Related work • Dutch legislation: UML Class Diagrams + OCL [van Engers et al., 2001] • US Internal Revenue Code: ontologies [Melz et al., 2004] • US healthcare: rule-based framework [Breaux, 2009] 4
What are the differences? • Modeling procedural & administrative aspects ! ! ! ! •Support for automated verification in various form ! 5
Research steps 2. Build UML profile 6 3. Use profile for transforming models • What information content should we expect? • What are the complexity factors? • Explicit means for capturing information requirements • Basis for modeling methodology • Reuse existing automation techniques • Solvers for testing • MATLAB for simulation 1. Conduct grounded theory study
What does the tax law look like? • Legal framework composed of legislation, regulations, and circulars ! Art. 105bis […]The commuting expenses deduction (FD) is defined as a function over the distance between the principal town of the municipality on whose territory the taxpayer's home is located and the place of taxpayer’s work. The distance is measured in units of distance expressing the kilometric distance between [principal] towns. A ministerial regulation provides these distances. ! The amount of the deduction is calculated as follows: If the distance exceeds 4 units but is less than 30 units, the deduction is € 99 per unit of distance. The first 4 units does not trigger any deduction and the deduction for a distance exceeding 30 units is limited to € 2,574. • Framework has prescriptive nature Procedure for calculating FD deduction 7 {{ Legal concepts definition
Meta-concepts in prescriptive laws ! Grounded theory coding of 16 articles from Luxembourg’s Income Tax Law Art. 105bis […]The commuting expenses deduction (FD) is defined as a function over the distance between the principal town of the municipality on whose territory the taxpayer's home is located and the place of taxpayer’s work. The distance is measured in units of distance expressing the kilometric distance between [principal] towns. A ministerial regulation provides these distances. ! The amount of the deduction is calculated as follows: If the distance exceeds 4 units but is less than 30 units, the deduction is € 99 per unit of distance. The first 4 units does not trigger any deduction and the deduction for a distance exceeding 30 units is limited to € 2,574. 8 Decision Operation
Information requirements (1) 9 Datatype Set Distance 1 Traceability Package Legal Text Legal Agent Record Information Source 1..* 0..1 Process Package Data Object 1..* produces as output Step 1..* has as input * 0..1 is derived from originates from Datatype Package Numeric String Boolean Domain Object Age Percentage Unit Monetary Value Decision Operation Date ▶ ▲ ▶ ▲ Legal Rule
Information requirements (2) * 1 10 Datatype Set Distance Traceability Package Legal Text Legal Agent Record Information Source 1..* 0..1 Process Package Data Object 1..* produces as output Step 1..* has as input * 0..1 has as type Datatype Package Numeric String Boolean Domain Object Age Percentage Unit Monetary Value Decision Operation Date ▲ ▲ Legal Rule ▶
Information requirements (3) * 1 11 Datatype Set Distance Traceability Package Legal Text Legal Agent Record Information Source 1..* 0..1 Process Package 1..* has as type Data Object 1..* produces as output Step 1..* has as input * 0..1 is derived from originates from Datatype Package Numeric String Boolean Domain Object Age Percentage Unit Monetary Value Decision Operation Date ▶ ▲ ▶ ▲ Legal Rule ▶ 1
OCL complexity factors (1) 12 Numerous branches! ! ! Art. 2 Individuals are considered resident taxpayers if they have their address in the Grand Duchy. Individuals are considered non-resident taxpayers if they do not reside in the Grand Duchy but have a local income within the definition of Article 156. context TaxPayer inv ResidentialStatus: let hasLocalAddress:Boolean = self.addresses! select(a:Address | a.country = Country::LU) !notEmpty() in if hasLocalAddress then self.oclIsTypeOf(ResidentTaxPayer) else let hasLocalIncomes:Boolean = self.incomes! select(i:Income | i.oclIsTypeOf(LocalIncome)) !notEmpty() in if hasLocalIncome then self.oclIsTypeOf(NonResidentTaxPayer) else false endif endif
OCL complexity factors (2) Art. 127 […]. An eligible dependent is a person who lives in the same household as the taxpayer but is not taxpayer himself. Only dependent receiving some allowances from the government are eligible. self.taxPayerDependents!select(dependent:Person | not dependent.oclIsTypeOf(TaxPayer) and dependent.addresses!intersection(self.addresses)!notEmpty() and dependent.allowances.amount!sum>0) 13 Lengthy navigations! ! !
OCL complexity factors (3) Art. 127bis On request, the taxpayer gets a deduction for extraordinary expenses for children care. When children under the age of twenty-one are maintained and educated mostly by the taxpayer, the total amount of all expenses dedicated to these children is considered as extraordinary expenses. However, extraordinary expenses defined by the current article must not exceed 3.480 euros per year and per child […] 14 Nested iterations context TaxPayer inv CE3: let tax year:Date = self.tax year, incomes:Set(Income) = self.incomes! select(i:Income | i.year = tax year), dependents:Set(Dependent) = self.dependents! select(d:Dependent | d.age < 21 ) in incomes!forAll(inc:Income | dependents!forAll(dep:Dependent | let total expenses:MonetaryValue = inc.expenses! select(exp:Expense | exp.beneficiary = dep)!sum() in if total expenses < 3480 then total expenses = inc.getCE3(tax year).amount else inc.getCE3(tax year).amount = 3480 endif))
2. Build UML profile 15 3. Use profile for transforming models Background: UML Profiles are a standard mechanism to extend UML with domain-specific modeling concepts • What information content should we expect? • What are the complexity factors? • Explicit means for capturing information requirements • Basis for modeling methodology • Reuse existing automation techniques • Solvers for testing • MATLAB for simulation 1. Conduct grounded theory study
Characteristics of our profile Our UML profile: ! • Customizes the activity modeling fragment of UML ! ! • Provides stereotypes for capturing information 16 requirements ! ! • Has built-in consistency constraints to ensure correct use of the profile ! ! !
Profile illustrated on an example Art. 105bis […]The commuting expenses deduction (FD) is defined as a function over the distance between the principal town of the municipality on whose territory the taxpayer's home is located and the place of taxpayer’s work. The distance is measured in units of distance expressing the kilometric distance between [principal] towns. A ministerial regulation provides these distances. ! The amount of the deduction is calculated as follows: If the distance exceeds 4 units but is less than 30 units, the deduction is € 99 per unit of distance. The first 4 units does not trigger any deduction and the deduction for a distance exceeding 30 units is limited to € 2,574. 17
OCL context «rule» «context» TaxPayer 18
Decisions and operations (1) «rule» «context» TaxPayer «intermediate» expected_amount : MonetaryValue 19 «assert» Check correctness of deduction granted to taxpayer «calculate» No deduction no (false) «decision» distance > minimal_distance «statement» actual_amount = expected_amount «formula» 0 (zero)
Decisions and operations (2) «rule» «context» TaxPayer distance > minimal_distance distance < maximal_distance «calculate» Normal rate per unit for declared distance «intermediate» expected_amount : MonetaryValue 20 «assert» Check correctness of prorata_period * flat_rate * distance deduction granted to taxpayer «calculate» No deduction «formula» yes (true) yes (true) no (false) «decision» «decision» «statement» actual_amount = expected_amount «formula» 0 (zero)
Decisions and operations (3) «rule» «context» TaxPayer distance > minimal_distance distance < maximal_distance «calculate» Normal rate per unit for declared distance «intermediate» expected_amount 21 no (false) : MonetaryValue «assert» Check correctness of prorata_period * flat_rate * distance deduction granted to taxpayer «calculate» No deduction «calculate» Special flat rate for maximal distance «formula» yes (true) yes (true) no (false) «decision» «decision» prorata_period * maximal_flat_rate «statement» «formula» actual_amount = expected_amount «formula» 0 (zero)
Iterations «context» TaxPayer distance > minimal_distance «calculate» Normal rate per unit for declared distance «intermediate» expected_amount 22 no (false) : MonetaryValue «assert» Check correctness of prorata_period * flat_rate * distance deduction granted to taxpayer «rule» «iterative» inc : Income «query» Agent type: Officer Question: When was the request postmarked? OCL: self.incomes-> select(i:Income| i.year = tax_year) «in» «fromagent» tax_year «in» incomes distance < maximal_distance «fromrecord» «calculate» No deduction «calculate» Special flat rate for maximal distance «formula» yes (true) «query» yes (true) no (false) «decision» «decision» prorata_period * maximal_flat_rate «statement» «formula» actual_amount = expected_amount «formula» 0 (zero)
Inputs (1) «context» TaxPayer distance > minimal_distance «calculate» Normal rate per unit for declared distance «intermediate» expected_amount 23 no (false) : MonetaryValue «assert» Check correctness of prorata_period * flat_rate * distance deduction granted to taxpayer «rule» «iterative» inc : Income «query» Agent type: Officer Question: When was the request postmarked? OCL: self.incomes-> select(i:Income| i.year = tax_year) «in» «fromagent» tax_year «in» incomes distance < maximal_distance «fromrecord» «calculate» No deduction «calculate» Special flat rate for maximal distance «formula» yes (true) «query» «query» Source: Art. 105bis of the LITL, 2013 OCL: inc.getFD (tax_year).amount «in» « fromlaw» «in» « fromlaw» maximal_flat_rate «in»« fromlaw» «in»« fromlaw» «in»« fromrecord» actual_amount «query» OCL: inc.prorata_period «in»« fromrecord» prorata_period «query» flat_rate minimal_distance maximal_distance yes (true) no (false) «decision» «decision» prorata_period * maximal_flat_rate «statement» «formula» actual_amount = expected_amount «formula» 0 (zero) «in»« fromrecord» distance «query» OCL: inc.distance Source: Ministerial Regulation of February 6, 2012
«context» TaxPayer distance > Address minimal_distance TaxPayer «calculate» Normal rate per unit for declared distance «intermediate» expected_amount 24 no (false) : MonetaryValue «assert» Check correctness of 1 «enumera(on» prorata_period * flat_rate * distance deduction granted to taxpayer «rule» «iterative» inc : Income «query» Agent type: Officer Question: When was the request postmarked? OCL: self.incomes-> select(i:Income| i.year = tax_year) «in» «fromagent» tax_year «in» incomes distance < maximal_distance «fromrecord» «calculate» No deduction «calculate» Special flat rate for maximal distance «formula» yes (true) «query» «query» Source: Art. 105bis of the LITL, 2013 OCL: inc.getFD (tax_year).amount «in» « fromlaw» «in» « fromlaw» maximal_flat_rate «in»« fromlaw» «in»« fromlaw» «in»« fromrecord» actual_amount «query» OCL: inc.prorata_period «in»« fromrecord» prorata_period «query» flat_rate minimal_distance maximal_distance yes (true) no (false) «decision» «decision» prorata_period * maximal_flat_rate Constant «statement» «formula» actual_amount = expected_amount «formula» 0 (zero) «in»« fromrecord» distance «query» OCL: inc.distance Source: Ministerial Regulation of February 6, 2012 IncomeTaxDeduction - flat_rate - maximal_flat_rate - maximal_distance - minimal_distance * * taxpayer * 1 incomes lives at * * * is accomplished at 1..* CommutingExpense Deduction is based on * * * works at Service 0..1 is paid for Income - distance:DistanceUnit - prorata_period:Number getFD(Date):MonetaryValue 1..* Inputs (2)
Putting it together 25 1 «enumera(on» Constant no (false) Address TaxPayer IncomeTaxDeduction «context» TaxPayer distance > minimal_distance «calculate» Normal rate per unit for declared distance «intermediate» expected_amount : MonetaryValue «assert» Check correctness of prorata_period * flat_rate * distance deduction granted to taxpayer «rule» «iterative» inc : Income «query» { Agent type: Officer Question: When was the request postmarked? OCL: self.incomes-> select(i:Income| i.year = tax_year) «in» «fromagent» tax_year «in» incomes distance < maximal_distance «fromrecord» «calculate» No deduction «calculate» Special flat rate for maximal distance «formula» yes (true) «query» «query» Source: Art. 105bis of the LITL, 2013 OCL: inc.getFD (tax_year).amount «in» « fromlaw» «in» « fromlaw» maximal_flat_rate «in»« fromlaw» «in»« fromlaw» «in»« fromrecord» actual_amount «query» OCL: inc.prorata_period «in»« fromrecord» prorata_period «query» flat_rate minimal_distance maximal_distance yes (true) no (false) «decision» «decision» prorata_period * maximal_flat_rate «statement» «formula» actual_amount = expected_amount «formula» 0 (zero) «in»« fromrecord» distance «query» OCL: inc.distance Source: Ministerial Regulation of February 6, 2012 - flat_rate - maximal_flat_rate - maximal_distance - minimal_distance * * taxpayer * 1 incomes lives at * * * is accomplished at 1..* CommutingExpense Deduction is based on * * * works at Service 0..1 is paid for Income - distance:DistanceUnit - prorata_period:Number getFD(Date):MonetaryValue 1..* Art. 105bis […]The commuting expenses deduction (FD) is defined as a function over the distance between the principal town of the municipality on whose territory the taxpayer's home is located and the place of taxpayer’s work. The distance is measured in units of distance expressing the kilometric distance between [principal] towns. A ministerial regulation provides these distances. ! The amount of the deduction is calculated as follows: If the distance exceeds 4 units but is less than 30 units, the deduction is € 99 per unit of distance. The first 4 units does not trigger any deduction and the deduction for a distance exceeding 30 units is limited to € 2,574. {
2. Build UML profile 26 3. Use profile for transforming models • What information content should we expect? • What are the complexity factors? • Explicit means for capturing information requirements • Basis for modeling methodology • Reuse existing automation techniques • Solvers for testing • MATLAB for simulation 1. Conduct grounded theory study
Transformation to OCL (1) Activity Diagram Retrieve all required inputs! Declare Inputs 27 Recognize Pattern Transform Pattern to OCL Make recursive call to handle next element ! «itera've» iterator: Type «in»+ Set(Object) name:
Transformation to OCL (2) Activity Diagram name ! forAll (iterator: Type | Retrieve all required inputs! Declare Inputs 28 Recognize Pattern Filled by the algorithm’s unwinding Transform Pattern to OCL ) Make recursive call to handle next element !
OCL vs. Model 1. context TaxPayer inv FD: 2. let tax year:Date = self.tax year in 3. let incomes:Set(Income) = self.incomes!select(i:Income | i.year = tax year) in 4. incomes!forAll(inc:Income | 5. let distance:DistanceUnit = inc.distance in 6. let minimal distance:DistanceUnit = 7. Constant::MINIMAL DISTANCE.oclAsType(DistanceUnit) in 8. if (distance > minimal distance) = true then 9. let maximal distance:DistanceUnit = 10. Constant::MAXIMAL DISTANCE.oclAsType(DistanceUnit) in 11. if (distance < maximal distance) = true then 12. let flat rate:MonetaryValue = 13. Constant::FLAT RATE.oclAsType(MonetaryValue) in 14. let prorata period:Numeric = inc.prorata period in 15. let expected amount:MonetaryValue = prorata period * flat rate * distance in 16. let actual amount:MonetaryValue = inc.getFD(tax year).amount in 17. actual amount = expected amount 18. else if (distance < maximal distance) = false then 19. let maximal flat rate:MonetaryValue = 20. Constant::MAXIMAL FLAT RATE.oclAsType(MonetaryValue) in 21. let prorata period:Numeric = inc.prorata period in 22. let expected amount:MonetaryValue = prorata period * maximal flat rate in 23. let actual amount:MonetaryValue = inc.getFD(tax year).amount in 24. actual amount = expected amount 25. else false endif 26. endif 27. else if (distance > minimal distance) = false then 28. let expected amount:MonetaryValue = 0 in 29. let actual amount:MonetaryValue = inc.getFD(tax year).amount in 30. actual amount = expected amount 31. else false endif endif 32. ) 29
2. Build UML profile 30 3. Use profile for transforming models • What information content should we expect? • What are the complexity factors? • Explicit means for capturing information requirements • Basis for modeling methodology • Reuse existing automation techniques • Solvers for testing • MATLAB for simulation 1. Conduct grounded theory study
Evaluation of effort We modeled the deductions and credits associated with personal income taxes: 31 ! ! ! ! Deductions (12 ADs):! • Commuting Expense ! • Miscellaneous Expenses ! • Spousal Expenses ! • Special Expenses! • Extraordinary Expenses! ! Credits (3 ADs):! • Employment ! • Pension ! • Single parents Luxembourgish tax card
Models sizes Resulting models have reasonable size FD FO AC CE1 CE2 CE3 DS1 DS2 DS3 DS4 DS5 DS6 CIS CIP CIM 32 Number of elements 80 70 60 50 40 30 20 10 0 Activity Diagrams
Measured effort Approximately 3.3 person-hour per activity diagram! ! ! ! ! 33 ! ! ! Effort spent to model deductions and credits for personal income taxes:
Complexity reduction (1) • AD tailored by our profile vs. manually-written OCL ! • Metrics related to the identified complexity factors: 34 - Navigations ! - If statements ! - Operations on collections ! - Iterative operations [Reynoso et al., 2004]
Complexity reduction (2) • AD tailored by our profile vs. manually-written OCL ! • Metrics related to the identified complexity factors: - Navigations: ↘ 45%! 35 ! - If statements: ↘ 100%! ! - Operations on collections: ↘72% ! - Iterative operations: ↘ 53%
Limitations • Some complexity carries over to the models ! • Specific to prescriptive legal frameworks 36
What’s next? • User studies ! • Extension to declarative legal frameworks ! • Study how models built using our approach can support simulation 37
` context TaxPayer inv ResidentialStatus: let hasLocalAddress:Boolean «context» TaxPayer = self.addresses! select(a:Address | a.country = Country::LU) Metrics related to the identified complexity Datatype Set factors: Effort spent to model deductions and credits for personal income Yes taxes: No «query» Activity Diagram Agent type: Officer Question: When was the request postmarked? 1..* has as type Data Object 1..* has as input Test cases Actual software system «calculate» No deduction ✗ 1..* «in» «fromagent» * 1 produces as output tax_year «in» - Navigations: «in» « fromlaw» ↘ 45%! «in» « fromlaw» maximal_flat_rate «in»« fromlaw» Approximately 3.3 person-hour per «in»« fromlawactivity » diagram! «query» Source: Art. 105bis of the LITL, 2013 is derived from Traces minimal_distance 2. Build UML profile Traces input to input to Analyzable interpretation of the law Actual result distance > simulated result Generates Distance Results match? «calculate» Normal rate per unit for declared distance «intermediate» prorata_period * flat_rate * distance Impact of fiscal decisions Simulates Tax Law «in»« fromrecord» «in»« fromrecord» «in»« fromrecord» 30 3. Use profile for transforming models • What information content should we expect? • What are the complexity factors? • Explicit means for capturing information requirements • Basis for modeling methodology • Reuse existing automation techniques • Solvers for testing • MATLAB for simulation 1. Conduct grounded theory study Traceability Package Legal Text Legal Agent prorata_period * maximal_flat_rate Record expected_amount Information Source 1..* 0..1 Process Package Step * 0..1 originates from Datatype Package Numeric String Boolean Domain Object Age Percentage Unit Monetary Value Decision Operation Date ▶ ▲ ▶ ▲ Legal Rule ▶ 1 !notEmpty() in if hasLocalAddress then self.oclIsTypeOf(ResidentTaxPayer) else let hasLocalIncomes:Boolean = self.incomes! select(i:Income | i.oclIsTypeOf(LocalIncome)) !notEmpty() in if hasLocalIncome then self.oclIsTypeOf(NonResidentTaxPayer) else false endif endif no (false) : MonetaryValue «assert» Check correctness of deduction granted to taxpayer «rule» «iterative» inc : Income OCL: self.incomes-> select(i:Income| i.year = tax_year) incomes distance < maximal_distance «fromrecord» «calculate» Special flat rate for maximal distance «formula» yes (true) «query» OCL: inc.getFD (tax_year).amount actual_amount «query» OCL: inc.prorata_period prorata_period «query» flat_rate minimal_distance maximal_distance yes (true) no (false) «decision» «decision» «statement» «formula» actual_amount = expected_amount «formula» 0 (zero) distance «query» OCL: inc.distance Source: Ministerial Regulation of February 6, 2012 Retrieve all required inputs! Declare Inputs Recognize Pattern Transform Pattern to OCL Make recursive call to handle next element ! 38 ! ! ! ! ! - If statements: ↘ 100%! ! - Operations on collections: ↘72% ! - Iterative operations: ↘ 53%
Acknowledgements • CTIE: Ludwig Balmer, Marc Blau, Yves Boland, Michaël Masseroni, Gautier Barrère • ACD: Thierry Prommenschenkel, Guy Heintz, Vincent D'Angelo • SnT: Domenico Bianculli 39
Profile for tax legal rules 40
Modeling methodology 41 Relevant Legal Texts Feedback Analysis Model the domain Model legal rules Domain Model Formal Specification ADToOCL Transformation UML Profile adequate input Activity Diagram (legal rule) OCL

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Using UML for Modeling Procedural Legal Rules

  • 1.
    Using UML forModeling Procedural Legal Rules Approach and a Study of Luxembourg’s Tax Law! Ghanem Soltana Elizabeta Fourneret Morayo Adedjouma ! Mehrdad Sabetzadeh Lionel Briand SsoftwareV verificVation & va.lidlaution University of Luxembourg, Luxembourg!
  • 2.
    How did thiswork come about? • Collaboration with Government of Luxembourg • CTIE: Government’s IT Centre • ACD: Tax Administration Department • New tax system under development • System needs to be compliant with the law 2
  • 3.
    Focus of thetalk:! What needs to be modeled? Yes No Context and motivation 3 Test cases Actual software system ✗ Traces to Traces to Input to Input to Analyzable interpretation of the law Actual result Simulated result Generates Results match? Impact of fiscal decisions Simulates What language to use? What methodology to apply? Tax Law
  • 4.
    Related work •Dutch legislation: UML Class Diagrams + OCL [van Engers et al., 2001] • US Internal Revenue Code: ontologies [Melz et al., 2004] • US healthcare: rule-based framework [Breaux, 2009] 4
  • 5.
    What are thedifferences? • Modeling procedural & administrative aspects ! ! ! ! •Support for automated verification in various form ! 5
  • 6.
    Research steps 2.Build UML profile 6 3. Use profile for transforming models • What information content should we expect? • What are the complexity factors? • Explicit means for capturing information requirements • Basis for modeling methodology • Reuse existing automation techniques • Solvers for testing • MATLAB for simulation 1. Conduct grounded theory study
  • 7.
    What does thetax law look like? • Legal framework composed of legislation, regulations, and circulars ! Art. 105bis […]The commuting expenses deduction (FD) is defined as a function over the distance between the principal town of the municipality on whose territory the taxpayer's home is located and the place of taxpayer’s work. The distance is measured in units of distance expressing the kilometric distance between [principal] towns. A ministerial regulation provides these distances. ! The amount of the deduction is calculated as follows: If the distance exceeds 4 units but is less than 30 units, the deduction is € 99 per unit of distance. The first 4 units does not trigger any deduction and the deduction for a distance exceeding 30 units is limited to € 2,574. • Framework has prescriptive nature Procedure for calculating FD deduction 7 {{ Legal concepts definition
  • 8.
    Meta-concepts in prescriptivelaws ! Grounded theory coding of 16 articles from Luxembourg’s Income Tax Law Art. 105bis […]The commuting expenses deduction (FD) is defined as a function over the distance between the principal town of the municipality on whose territory the taxpayer's home is located and the place of taxpayer’s work. The distance is measured in units of distance expressing the kilometric distance between [principal] towns. A ministerial regulation provides these distances. ! The amount of the deduction is calculated as follows: If the distance exceeds 4 units but is less than 30 units, the deduction is € 99 per unit of distance. The first 4 units does not trigger any deduction and the deduction for a distance exceeding 30 units is limited to € 2,574. 8 Decision Operation
  • 9.
    Information requirements (1) 9 Datatype Set Distance 1 Traceability Package Legal Text Legal Agent Record Information Source 1..* 0..1 Process Package Data Object 1..* produces as output Step 1..* has as input * 0..1 is derived from originates from Datatype Package Numeric String Boolean Domain Object Age Percentage Unit Monetary Value Decision Operation Date ▶ ▲ ▶ ▲ Legal Rule
  • 10.
    Information requirements (2) * 1 10 Datatype Set Distance Traceability Package Legal Text Legal Agent Record Information Source 1..* 0..1 Process Package Data Object 1..* produces as output Step 1..* has as input * 0..1 has as type Datatype Package Numeric String Boolean Domain Object Age Percentage Unit Monetary Value Decision Operation Date ▲ ▲ Legal Rule ▶
  • 11.
    Information requirements (3) * 1 11 Datatype Set Distance Traceability Package Legal Text Legal Agent Record Information Source 1..* 0..1 Process Package 1..* has as type Data Object 1..* produces as output Step 1..* has as input * 0..1 is derived from originates from Datatype Package Numeric String Boolean Domain Object Age Percentage Unit Monetary Value Decision Operation Date ▶ ▲ ▶ ▲ Legal Rule ▶ 1
  • 12.
    OCL complexity factors(1) 12 Numerous branches! ! ! Art. 2 Individuals are considered resident taxpayers if they have their address in the Grand Duchy. Individuals are considered non-resident taxpayers if they do not reside in the Grand Duchy but have a local income within the definition of Article 156. context TaxPayer inv ResidentialStatus: let hasLocalAddress:Boolean = self.addresses! select(a:Address | a.country = Country::LU) !notEmpty() in if hasLocalAddress then self.oclIsTypeOf(ResidentTaxPayer) else let hasLocalIncomes:Boolean = self.incomes! select(i:Income | i.oclIsTypeOf(LocalIncome)) !notEmpty() in if hasLocalIncome then self.oclIsTypeOf(NonResidentTaxPayer) else false endif endif
  • 13.
    OCL complexity factors(2) Art. 127 […]. An eligible dependent is a person who lives in the same household as the taxpayer but is not taxpayer himself. Only dependent receiving some allowances from the government are eligible. self.taxPayerDependents!select(dependent:Person | not dependent.oclIsTypeOf(TaxPayer) and dependent.addresses!intersection(self.addresses)!notEmpty() and dependent.allowances.amount!sum>0) 13 Lengthy navigations! ! !
  • 14.
    OCL complexity factors(3) Art. 127bis On request, the taxpayer gets a deduction for extraordinary expenses for children care. When children under the age of twenty-one are maintained and educated mostly by the taxpayer, the total amount of all expenses dedicated to these children is considered as extraordinary expenses. However, extraordinary expenses defined by the current article must not exceed 3.480 euros per year and per child […] 14 Nested iterations context TaxPayer inv CE3: let tax year:Date = self.tax year, incomes:Set(Income) = self.incomes! select(i:Income | i.year = tax year), dependents:Set(Dependent) = self.dependents! select(d:Dependent | d.age < 21 ) in incomes!forAll(inc:Income | dependents!forAll(dep:Dependent | let total expenses:MonetaryValue = inc.expenses! select(exp:Expense | exp.beneficiary = dep)!sum() in if total expenses < 3480 then total expenses = inc.getCE3(tax year).amount else inc.getCE3(tax year).amount = 3480 endif))
  • 15.
    2. Build UML profile 15 3. Use profile for transforming models Background: UML Profiles are a standard mechanism to extend UML with domain-specific modeling concepts • What information content should we expect? • What are the complexity factors? • Explicit means for capturing information requirements • Basis for modeling methodology • Reuse existing automation techniques • Solvers for testing • MATLAB for simulation 1. Conduct grounded theory study
  • 16.
    Characteristics of ourprofile Our UML profile: ! • Customizes the activity modeling fragment of UML ! ! • Provides stereotypes for capturing information 16 requirements ! ! • Has built-in consistency constraints to ensure correct use of the profile ! ! !
  • 17.
    Profile illustrated onan example Art. 105bis […]The commuting expenses deduction (FD) is defined as a function over the distance between the principal town of the municipality on whose territory the taxpayer's home is located and the place of taxpayer’s work. The distance is measured in units of distance expressing the kilometric distance between [principal] towns. A ministerial regulation provides these distances. ! The amount of the deduction is calculated as follows: If the distance exceeds 4 units but is less than 30 units, the deduction is € 99 per unit of distance. The first 4 units does not trigger any deduction and the deduction for a distance exceeding 30 units is limited to € 2,574. 17
  • 18.
    OCL context «rule»«context» TaxPayer 18
  • 19.
    Decisions and operations(1) «rule» «context» TaxPayer «intermediate» expected_amount : MonetaryValue 19 «assert» Check correctness of deduction granted to taxpayer «calculate» No deduction no (false) «decision» distance > minimal_distance «statement» actual_amount = expected_amount «formula» 0 (zero)
  • 20.
    Decisions and operations(2) «rule» «context» TaxPayer distance > minimal_distance distance < maximal_distance «calculate» Normal rate per unit for declared distance «intermediate» expected_amount : MonetaryValue 20 «assert» Check correctness of prorata_period * flat_rate * distance deduction granted to taxpayer «calculate» No deduction «formula» yes (true) yes (true) no (false) «decision» «decision» «statement» actual_amount = expected_amount «formula» 0 (zero)
  • 21.
    Decisions and operations(3) «rule» «context» TaxPayer distance > minimal_distance distance < maximal_distance «calculate» Normal rate per unit for declared distance «intermediate» expected_amount 21 no (false) : MonetaryValue «assert» Check correctness of prorata_period * flat_rate * distance deduction granted to taxpayer «calculate» No deduction «calculate» Special flat rate for maximal distance «formula» yes (true) yes (true) no (false) «decision» «decision» prorata_period * maximal_flat_rate «statement» «formula» actual_amount = expected_amount «formula» 0 (zero)
  • 22.
    Iterations «context» TaxPayer distance > minimal_distance «calculate» Normal rate per unit for declared distance «intermediate» expected_amount 22 no (false) : MonetaryValue «assert» Check correctness of prorata_period * flat_rate * distance deduction granted to taxpayer «rule» «iterative» inc : Income «query» Agent type: Officer Question: When was the request postmarked? OCL: self.incomes-> select(i:Income| i.year = tax_year) «in» «fromagent» tax_year «in» incomes distance < maximal_distance «fromrecord» «calculate» No deduction «calculate» Special flat rate for maximal distance «formula» yes (true) «query» yes (true) no (false) «decision» «decision» prorata_period * maximal_flat_rate «statement» «formula» actual_amount = expected_amount «formula» 0 (zero)
  • 23.
    Inputs (1) «context»TaxPayer distance > minimal_distance «calculate» Normal rate per unit for declared distance «intermediate» expected_amount 23 no (false) : MonetaryValue «assert» Check correctness of prorata_period * flat_rate * distance deduction granted to taxpayer «rule» «iterative» inc : Income «query» Agent type: Officer Question: When was the request postmarked? OCL: self.incomes-> select(i:Income| i.year = tax_year) «in» «fromagent» tax_year «in» incomes distance < maximal_distance «fromrecord» «calculate» No deduction «calculate» Special flat rate for maximal distance «formula» yes (true) «query» «query» Source: Art. 105bis of the LITL, 2013 OCL: inc.getFD (tax_year).amount «in» « fromlaw» «in» « fromlaw» maximal_flat_rate «in»« fromlaw» «in»« fromlaw» «in»« fromrecord» actual_amount «query» OCL: inc.prorata_period «in»« fromrecord» prorata_period «query» flat_rate minimal_distance maximal_distance yes (true) no (false) «decision» «decision» prorata_period * maximal_flat_rate «statement» «formula» actual_amount = expected_amount «formula» 0 (zero) «in»« fromrecord» distance «query» OCL: inc.distance Source: Ministerial Regulation of February 6, 2012
  • 24.
    «context» TaxPayer distance> Address minimal_distance TaxPayer «calculate» Normal rate per unit for declared distance «intermediate» expected_amount 24 no (false) : MonetaryValue «assert» Check correctness of 1 «enumera(on» prorata_period * flat_rate * distance deduction granted to taxpayer «rule» «iterative» inc : Income «query» Agent type: Officer Question: When was the request postmarked? OCL: self.incomes-> select(i:Income| i.year = tax_year) «in» «fromagent» tax_year «in» incomes distance < maximal_distance «fromrecord» «calculate» No deduction «calculate» Special flat rate for maximal distance «formula» yes (true) «query» «query» Source: Art. 105bis of the LITL, 2013 OCL: inc.getFD (tax_year).amount «in» « fromlaw» «in» « fromlaw» maximal_flat_rate «in»« fromlaw» «in»« fromlaw» «in»« fromrecord» actual_amount «query» OCL: inc.prorata_period «in»« fromrecord» prorata_period «query» flat_rate minimal_distance maximal_distance yes (true) no (false) «decision» «decision» prorata_period * maximal_flat_rate Constant «statement» «formula» actual_amount = expected_amount «formula» 0 (zero) «in»« fromrecord» distance «query» OCL: inc.distance Source: Ministerial Regulation of February 6, 2012 IncomeTaxDeduction - flat_rate - maximal_flat_rate - maximal_distance - minimal_distance * * taxpayer * 1 incomes lives at * * * is accomplished at 1..* CommutingExpense Deduction is based on * * * works at Service 0..1 is paid for Income - distance:DistanceUnit - prorata_period:Number getFD(Date):MonetaryValue 1..* Inputs (2)
  • 25.
    Putting it together 25 1 «enumera(on» Constant no (false) Address TaxPayer IncomeTaxDeduction «context» TaxPayer distance > minimal_distance «calculate» Normal rate per unit for declared distance «intermediate» expected_amount : MonetaryValue «assert» Check correctness of prorata_period * flat_rate * distance deduction granted to taxpayer «rule» «iterative» inc : Income «query» { Agent type: Officer Question: When was the request postmarked? OCL: self.incomes-> select(i:Income| i.year = tax_year) «in» «fromagent» tax_year «in» incomes distance < maximal_distance «fromrecord» «calculate» No deduction «calculate» Special flat rate for maximal distance «formula» yes (true) «query» «query» Source: Art. 105bis of the LITL, 2013 OCL: inc.getFD (tax_year).amount «in» « fromlaw» «in» « fromlaw» maximal_flat_rate «in»« fromlaw» «in»« fromlaw» «in»« fromrecord» actual_amount «query» OCL: inc.prorata_period «in»« fromrecord» prorata_period «query» flat_rate minimal_distance maximal_distance yes (true) no (false) «decision» «decision» prorata_period * maximal_flat_rate «statement» «formula» actual_amount = expected_amount «formula» 0 (zero) «in»« fromrecord» distance «query» OCL: inc.distance Source: Ministerial Regulation of February 6, 2012 - flat_rate - maximal_flat_rate - maximal_distance - minimal_distance * * taxpayer * 1 incomes lives at * * * is accomplished at 1..* CommutingExpense Deduction is based on * * * works at Service 0..1 is paid for Income - distance:DistanceUnit - prorata_period:Number getFD(Date):MonetaryValue 1..* Art. 105bis […]The commuting expenses deduction (FD) is defined as a function over the distance between the principal town of the municipality on whose territory the taxpayer's home is located and the place of taxpayer’s work. The distance is measured in units of distance expressing the kilometric distance between [principal] towns. A ministerial regulation provides these distances. ! The amount of the deduction is calculated as follows: If the distance exceeds 4 units but is less than 30 units, the deduction is € 99 per unit of distance. The first 4 units does not trigger any deduction and the deduction for a distance exceeding 30 units is limited to € 2,574. {
  • 26.
    2. Build UML profile 26 3. Use profile for transforming models • What information content should we expect? • What are the complexity factors? • Explicit means for capturing information requirements • Basis for modeling methodology • Reuse existing automation techniques • Solvers for testing • MATLAB for simulation 1. Conduct grounded theory study
  • 27.
    Transformation to OCL(1) Activity Diagram Retrieve all required inputs! Declare Inputs 27 Recognize Pattern Transform Pattern to OCL Make recursive call to handle next element ! «itera've» iterator: Type «in»+ Set(Object) name:
  • 28.
    Transformation to OCL(2) Activity Diagram name ! forAll (iterator: Type | Retrieve all required inputs! Declare Inputs 28 Recognize Pattern Filled by the algorithm’s unwinding Transform Pattern to OCL ) Make recursive call to handle next element !
  • 29.
    OCL vs. Model 1. context TaxPayer inv FD: 2. let tax year:Date = self.tax year in 3. let incomes:Set(Income) = self.incomes!select(i:Income | i.year = tax year) in 4. incomes!forAll(inc:Income | 5. let distance:DistanceUnit = inc.distance in 6. let minimal distance:DistanceUnit = 7. Constant::MINIMAL DISTANCE.oclAsType(DistanceUnit) in 8. if (distance > minimal distance) = true then 9. let maximal distance:DistanceUnit = 10. Constant::MAXIMAL DISTANCE.oclAsType(DistanceUnit) in 11. if (distance < maximal distance) = true then 12. let flat rate:MonetaryValue = 13. Constant::FLAT RATE.oclAsType(MonetaryValue) in 14. let prorata period:Numeric = inc.prorata period in 15. let expected amount:MonetaryValue = prorata period * flat rate * distance in 16. let actual amount:MonetaryValue = inc.getFD(tax year).amount in 17. actual amount = expected amount 18. else if (distance < maximal distance) = false then 19. let maximal flat rate:MonetaryValue = 20. Constant::MAXIMAL FLAT RATE.oclAsType(MonetaryValue) in 21. let prorata period:Numeric = inc.prorata period in 22. let expected amount:MonetaryValue = prorata period * maximal flat rate in 23. let actual amount:MonetaryValue = inc.getFD(tax year).amount in 24. actual amount = expected amount 25. else false endif 26. endif 27. else if (distance > minimal distance) = false then 28. let expected amount:MonetaryValue = 0 in 29. let actual amount:MonetaryValue = inc.getFD(tax year).amount in 30. actual amount = expected amount 31. else false endif endif 32. ) 29
  • 30.
    2. Build UML profile 30 3. Use profile for transforming models • What information content should we expect? • What are the complexity factors? • Explicit means for capturing information requirements • Basis for modeling methodology • Reuse existing automation techniques • Solvers for testing • MATLAB for simulation 1. Conduct grounded theory study
  • 31.
    Evaluation of effort We modeled the deductions and credits associated with personal income taxes: 31 ! ! ! ! Deductions (12 ADs):! • Commuting Expense ! • Miscellaneous Expenses ! • Spousal Expenses ! • Special Expenses! • Extraordinary Expenses! ! Credits (3 ADs):! • Employment ! • Pension ! • Single parents Luxembourgish tax card
  • 32.
    Models sizes Resultingmodels have reasonable size FD FO AC CE1 CE2 CE3 DS1 DS2 DS3 DS4 DS5 DS6 CIS CIP CIM 32 Number of elements 80 70 60 50 40 30 20 10 0 Activity Diagrams
  • 33.
    Measured effort Approximately3.3 person-hour per activity diagram! ! ! ! ! 33 ! ! ! Effort spent to model deductions and credits for personal income taxes:
  • 34.
    Complexity reduction (1) • AD tailored by our profile vs. manually-written OCL ! • Metrics related to the identified complexity factors: 34 - Navigations ! - If statements ! - Operations on collections ! - Iterative operations [Reynoso et al., 2004]
  • 35.
    Complexity reduction (2) • AD tailored by our profile vs. manually-written OCL ! • Metrics related to the identified complexity factors: - Navigations: ↘ 45%! 35 ! - If statements: ↘ 100%! ! - Operations on collections: ↘72% ! - Iterative operations: ↘ 53%
  • 36.
    Limitations • Somecomplexity carries over to the models ! • Specific to prescriptive legal frameworks 36
  • 37.
    What’s next? •User studies ! • Extension to declarative legal frameworks ! • Study how models built using our approach can support simulation 37
  • 38.
    ` context TaxPayerinv ResidentialStatus: let hasLocalAddress:Boolean «context» TaxPayer = self.addresses! select(a:Address | a.country = Country::LU) Metrics related to the identified complexity Datatype Set factors: Effort spent to model deductions and credits for personal income Yes taxes: No «query» Activity Diagram Agent type: Officer Question: When was the request postmarked? 1..* has as type Data Object 1..* has as input Test cases Actual software system «calculate» No deduction ✗ 1..* «in» «fromagent» * 1 produces as output tax_year «in» - Navigations: «in» « fromlaw» ↘ 45%! «in» « fromlaw» maximal_flat_rate «in»« fromlaw» Approximately 3.3 person-hour per «in»« fromlawactivity » diagram! «query» Source: Art. 105bis of the LITL, 2013 is derived from Traces minimal_distance 2. Build UML profile Traces input to input to Analyzable interpretation of the law Actual result distance > simulated result Generates Distance Results match? «calculate» Normal rate per unit for declared distance «intermediate» prorata_period * flat_rate * distance Impact of fiscal decisions Simulates Tax Law «in»« fromrecord» «in»« fromrecord» «in»« fromrecord» 30 3. Use profile for transforming models • What information content should we expect? • What are the complexity factors? • Explicit means for capturing information requirements • Basis for modeling methodology • Reuse existing automation techniques • Solvers for testing • MATLAB for simulation 1. Conduct grounded theory study Traceability Package Legal Text Legal Agent prorata_period * maximal_flat_rate Record expected_amount Information Source 1..* 0..1 Process Package Step * 0..1 originates from Datatype Package Numeric String Boolean Domain Object Age Percentage Unit Monetary Value Decision Operation Date ▶ ▲ ▶ ▲ Legal Rule ▶ 1 !notEmpty() in if hasLocalAddress then self.oclIsTypeOf(ResidentTaxPayer) else let hasLocalIncomes:Boolean = self.incomes! select(i:Income | i.oclIsTypeOf(LocalIncome)) !notEmpty() in if hasLocalIncome then self.oclIsTypeOf(NonResidentTaxPayer) else false endif endif no (false) : MonetaryValue «assert» Check correctness of deduction granted to taxpayer «rule» «iterative» inc : Income OCL: self.incomes-> select(i:Income| i.year = tax_year) incomes distance < maximal_distance «fromrecord» «calculate» Special flat rate for maximal distance «formula» yes (true) «query» OCL: inc.getFD (tax_year).amount actual_amount «query» OCL: inc.prorata_period prorata_period «query» flat_rate minimal_distance maximal_distance yes (true) no (false) «decision» «decision» «statement» «formula» actual_amount = expected_amount «formula» 0 (zero) distance «query» OCL: inc.distance Source: Ministerial Regulation of February 6, 2012 Retrieve all required inputs! Declare Inputs Recognize Pattern Transform Pattern to OCL Make recursive call to handle next element ! 38 ! ! ! ! ! - If statements: ↘ 100%! ! - Operations on collections: ↘72% ! - Iterative operations: ↘ 53%
  • 39.
    Acknowledgements • CTIE:Ludwig Balmer, Marc Blau, Yves Boland, Michaël Masseroni, Gautier Barrère • ACD: Thierry Prommenschenkel, Guy Heintz, Vincent D'Angelo • SnT: Domenico Bianculli 39
  • 40.
    Profile for taxlegal rules 40
  • 41.
    Modeling methodology 41 Relevant Legal Texts Feedback Analysis Model the domain Model legal rules Domain Model Formal Specification ADToOCL Transformation UML Profile adequate input Activity Diagram (legal rule) OCL