Deriving non-Zeno behaviour models from goal models using ILP

D. Alrajeh (1) , J. Kramer (1) , A. Russo (1) , S. Uchitel (1, 2)

1 Department of Computing [London]
2 Departamento de Computación [Buenos Aires]

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 () that eliminate these traces. The process terminates giving a non-Zeno behaviour model produced from the learned pre-conditions and the given goal model.

Mots clés: Goal-oriented requirements engineering; Zeno behaviour; Operational requirements; Model checking; Inductive learning

D. Alrajeh, J. Kramer, A. Russo, S. Uchitel. Deriving non-Zeno behaviour models from goal models using ILP. Formal Aspects of Computing, 2009, 22 (3), pp.217-241. ⟨10.1007/s00165-009-0128-5⟩. ⟨hal-00523663⟩