TY - GEN
T1 - Empirical investigation of search algorithms for environment model-based testing of real-time embedded software
AU - Iqbal, Muhammad Zohaib
AU - Arcuri, Andrea
AU - Briand, Lionel
PY - 2012
Y1 - 2012
N2 - 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.
AB - 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.
KW - Automated model-based testing
KW - branch distance
KW - real-time embedded systems
KW - search-based software engineering
UR - http://www.scopus.com/inward/record.url?scp=84865288583&partnerID=8YFLogxK
U2 - 10.1145/04000800.2336777
DO - 10.1145/04000800.2336777
M3 - Conference contribution
AN - SCOPUS:84865288583
SN - 9781450314541
T3 - 2012 International Symposium on Software Testing and Analysis, ISSTA 2012 - Proceedings
SP - 199
EP - 209
BT - 2012 International Symposium on Software Testing and Analysis, ISSTA 2012 - Proceedings
T2 - 21st International Symposium on Software Testing and Analysis, ISSTA 2012
Y2 - 15 July 2012 through 20 July 2012
ER -