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Test Data Generation for Event-B Models Using Genetic Algorithms

  • Ionut Dinca
  • Alin Stefanescu
  • Florentin Ipate
  • Raluca Lefticaru
  • Cristina Tudose
Part of the Communications in Computer and Information Science book series (CCIS, volume 181)

Abstract

Event-B is a formal modeling language having set theory as its mathematical foundation and abstract state machines as its behavioral specifications. The language has very good tool support based on theorem proving and model checking technologies, but very little support for test generation. Motivated by industrial interest in the latter domain, this paper presents an approach based on genetic algorithms that generates test data for Event-B test paths. For that, new fitness functions adapted to the set-theoretic nature of Event-B are devised. The approach was implemented and its efficiency was proven on a carefully designed benchmark using statistically sound evaluations.

Keywords

Genetic Algorithm Test Generation Random Testing Abstract State Machine Large State Space 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Ionut Dinca
    • 1
  • Alin Stefanescu
    • 1
  • Florentin Ipate
    • 1
  • Raluca Lefticaru
    • 1
  • Cristina Tudose
    • 1
  1. 1.Department of Computer ScienceUniversity of PitestiPitestiRomania

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