@misc{8766,
  keywords = {Conference},
  author = {Muhammad Iqbal and Andrea Arcuri and Lionel Briand},
  title = {Empirical Investigation of Search Algorithms for Environment Model-Based Testing of Real-Time Embedded Software},
  abstract = {System testing of real-time embedded systems (RTES) is a challenging task and only a fully automated testing approach can scale up to the testing requirements of industrial RTES. One such approach, which offers the advantage for testing teams to be black-box, is to use environment models to automatically generate test cases and oracles and an environment simulator to enable earlier and more practical testing. In this paper, we propose novel heuristics for search-based, RTES system testing which are based on these environment models. We evaluate the fault detection effectiveness of two search-based algorithms, i.e., Genetic Algorithms and (1+1) Evolutionary Algorithm, when using these novel heuristics and their combinations. Preliminary experiments on 13 carefully selected, non-trivial artificial problems, show that, under certain conditions, these novel heuristics are effective at bringing the environment into a state exhibiting a system fault. The heuristic combination that showed the best overall performance on the artificial problems was applied on an industrial case study where it showed consistent results.},
  year = {2012},
  journal = {International Symposium on Software Testing and Analysis (ISSTA), ACM},
  publisher = {ACM},
  address = {New York, NY, USA},
}