Comparing algorithms for search-based test data generation of matlab® simulink® models

Authors:
Kamran Ghani;John A. Clark;Yuan Zhan
Affiliations:
Department of Computer Science, The University of York, Heslington, York, UK;Department of Computer Science, The University of York, Heslington, York, UK;The MathWorks, inc.
Venue:
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Year:
2009

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Abstract

Search Based Software Engineering (SBSE) is an evolving field where meta-heuristic techniques are applied to solve many software engineering problems. One area of SBSE, where considerable research is underway, is software testing. We see much application of meta-heuristics search techniques for generating input test data. But most of the work in this area is concentrated on test data generation from source code. We see very little application of such techniques to testing from other sources such as requirement and design models. Zhan and Clark applied such techniques to generate test data for Simulink models. This paper extends the work of Zhan and Clark by investigating the application of Genetic Algorithms (GAs) to Simulink models and then statistically compares the results to the existing work, which is mainly based on Simulated Annealing (SA).