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Deriving non-Zeno behaviour models from goal models using ILP

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Formal Aspects of Computing

Abstract

One of the difficulties in goal-oriented requirements engineering (GORE) is the construction of behaviour models from declarative goal specifications. This paper addresses this problem using a combination of model checking and machine learning. First, a goal model is transformed into a (potentially Zeno) behaviour model. Then, via an iterative process, Zeno traces are identified by model checking the behaviour model against a time progress property, and inductive logic programming (ILP) is used to learn operational requirements (pre-conditions) that eliminate these traces. The process terminates giving a non-Zeno behaviour model produced from the learned pre-conditions and the given goal model.

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Authors and Affiliations

  1. Department of Computing, Imperial College London, 180 Queen’s Gate, London, SW7 2AZ, UK

    D. Alrajeh, J. Kramer, A. Russo & S. Uchitel

  2. Departamento de Computaciòn, FCEyN, Universidad de Buenos Aires, Buenos Aires, Argentina

    S. Uchitel

Authors
  1. D. Alrajeh
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  2. J. Kramer
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  3. A. Russo
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  4. S. Uchitel
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Corresponding author

Correspondence to D. Alrajeh.

Additional information

Communicated by J.L. Fiadeiro, P. Inverardi and T.S.E. Maibaum

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Alrajeh, D., Kramer, J., Russo, A. et al. Deriving non-Zeno behaviour models from goal models using ILP. Form Asp Comp 22, 217–241 (2010). https://doi.org/10.1007/s00165-009-0128-5

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  • DOI: https://doi.org/10.1007/s00165-009-0128-5

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