A model-based framework for probabilistic simulation of legal policies
| Autor: | Mehrdad Sabetzadeh, Lionel C. Briand, Ghanem Soltana, Nicolas Sannier |
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| Přispěvatelé: | Fonds National de la Recherche – FnR [sponsor], Interdisciplinary Centre for Security, Reliability and Trust (SnT) > Software Verification and Validation Lab (SVV Lab) [research center] |
| Rok vydání: | 2015 |
| Předmět: |
Legal Policy Simulation
Computer science [C05] [Engineering computing & technology] education.field_of_study Legal policies Model- Driven Code Generation Test data generation Management science Computer science Population Probabilistic logic Probabilistic Data Generation ComputingMilieux_LEGALASPECTSOFCOMPUTING Sciences informatiques [C05] [Ingénierie informatique & technologie] Data modeling Unified Modeling Language Risk analysis (engineering) Revenue education computer Tax law computer.programming_language |
| Zdroj: | MoDELS 18th ACM/IEEE International Conference on Model Driven Engineering Languages and Systems (MODELS'15) (pp. 70-79). IEEE (2015). |
| DOI: | 10.1109/models.2015.7338237 |
| Popis: | Legal policy simulation is an important decision-support tool in domains such as taxation. The primary goal of legal policy simulation is predicting how changes in the law affect measures of interest, e.g., revenue. Currently, legal policies are simulated via a combination of spreadsheets and software code. This poses a validation challenge both due to complexity reasons and due to legal experts lacking the expertise to understand software code. A further challenge is that representative data for simulation may be unavailable, thus necessitating a data generator. We develop a framework for legal policy simulation that is aimed at addressing these challenges. The framework uses models for specifying both legal policies and the probabilistic characteristics of the underlying population. We devise an automated algorithm for simulation data generation. We evaluate our framework through a case study on Luxembourg's Tax Law. |
| Databáze: | OpenAIRE |
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