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Software and Systems Modeling
Erschienen in: Software and Systems Modeling 3/2018

05.07.2016 | Special Section Paper

Model-based simulation of legal policies: framework, tool support, and validation

verfasst von: Ghanem Soltana, Nicolas Sannier, Mehrdad Sabetzadeh, Lionel C. Briand

Erschienen in: Software and Systems Modeling | Ausgabe 3/2018

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Abstract

Simulation of legal policies 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. Legal policy simulation is currently implemented using a combination of spreadsheets and software code. Such a direct implementation poses a validation challenge. In particular, legal experts often lack the necessary software background to review complex spreadsheets and code. Consequently, these experts currently have no reliable means to check the correctness of simulations against the requirements envisaged by the law. A further challenge is that representative data for simulation may be unavailable, thus necessitating a data generator. A hard-coded generator is difficult to build and validate. We develop a framework for legal policy simulation that is aimed at addressing the challenges above. 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.
Vorheriger Artikel Full contract verification for ATL using symbolic execution
Nächster Artikel Testing models and model transformations using classifying terms

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Fußnoten
1
This profile is not to be confused with the profile that we present in Sect. 5 for extending domain models with probabilistic information.
 
2
We note that the traversal strategy of Alg. 1, discussed in Sect. 6.4, ensures that associations that have an end with a cardinality of 1, 0..1, 1..n or \(1..*\) will satisfy the multiplicity constraints. We further note that the satisfaction of many-to-many multiplicity constraints is a given. Nevertheless, our data generator interprets many-to-many multiplicity constraints as m-to-n ones, with m and n chosen either randomly or by the «multiplicity» stereotype.
 
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Metadaten
Titel
Model-based simulation of legal policies: framework, tool support, and validation
verfasst von
Ghanem Soltana
Nicolas Sannier
Mehrdad Sabetzadeh
Lionel C. Briand
Publikationsdatum
05.07.2016
Verlag
Springer Berlin Heidelberg
Erschienen in
Software and Systems Modeling / Ausgabe 3/2018
Print ISSN: 1619-1366
Elektronische ISSN: 1619-1374
DOI
https://doi.org/10.1007/s10270-016-0542-0

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