A model-based framework for probabilistic simulation of legal policies

Ghanem Soltana, Nicolas Sannier, Mehrdad Sabetzadeh, Lionel C. Briand

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

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.

Original languageEnglish
Title of host publication2015 ACM/IEEE 18th International Conference on Model Driven Engineering Languages and Systems, MODELS 2015 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages70-79
Number of pages10
ISBN (Electronic)9781467369084
DOIs
Publication statusPublished - 25 Nov 2015
Externally publishedYes
Event18th ACM/IEEE International Conference on Model Driven Engineering Languages and Systems, MODELS 2015 - Ottawa, Canada
Duration: 30 Sep 20152 Oct 2015

Publication series

Name2015 ACM/IEEE 18th International Conference on Model Driven Engineering Languages and Systems, MODELS 2015 - Proceedings

Conference

Conference18th ACM/IEEE International Conference on Model Driven Engineering Languages and Systems, MODELS 2015
Country/TerritoryCanada
CityOttawa
Period30/09/152/10/15

Keywords

  • Legal Policies
  • Model-Driven Code Generation
  • Probabilistic Data Generation
  • Simulation
  • UML Profiles

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