Abstract
System modeling is a classical approach to ensure their reliability since it is suitable both for a formal verification and for software testing techniques. In the context of model-based testing an approach combining random testing and coverage based testing has been recently introduced [9]. However, this approach is not tractable on quite large models. In this paper we show how to use statistical approximations to make the approach work on larger models. Experimental results, on models of communicating protocols, are provided; they are very promising, both for the computation time and for the quality of the generated test suites.
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Notes
- 1.
Computing test suites of a reduced size is a major issue in the testing process, since executing test on the system is frequently a complex issue (not addressed in this paper).
- 2.
The approach can easily be adapted for transitions coverage.
- 3.
Resolutions have been performed using the lp_solve solver.
- 4.
- 5.
Eccentricity is an important parameter since it is the minimal length required for paths to have a chance to visit each state.
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Bernard, J., Héam, PC., Kouchnarenko, O. (2018). An Approximation-Based Approach for the Random Exploration of Large Models. In: Dubois, C., Wolff, B. (eds) Tests and Proofs. TAP 2018. Lecture Notes in Computer Science(), vol 10889. Springer, Cham. https://doi.org/10.1007/978-3-319-92994-1_2
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