TY - GEN
T1 - Automated test suite generation for time-continuous simulink models
AU - Matinnejad, Reza
AU - Nejati, Shiva
AU - Briand, Lionel C.
AU - Bruckmann, Thomas
N1 - Publisher Copyright:
© 2016 ACM.
PY - 2016/5/14
Y1 - 2016/5/14
N2 - All engineering disciplines are founded and rely on models, although they may differ on purposes and usages of modeling. Interdisciplinary domains such as Cyber Physical Systems (CPSs) seek approaches that incorporate different modeling needs and usages. Specifically, the Simulink modeling platform greatly appeals to CPS engineers due to its seamless support for simulation and code generation. In this paper, we propose a test generation approach that is applicable to Simulink models built for both purposes of simulation and code generation. We define test inputs and outputs as signals that capture evolution of values over time. Our test generation approach is implemented as a meta-heuristic search algorithm and is guided to produce test outputs with diverse shapes according to our proposed notion of diversity. Our evaluation, performed on industrial and public domain models, demonstrates that: (1) In contrast to the existing tools for testing Simulink models that are only applicable to a subset of code generation models, our approach is applicable to both code generation and simulation Simulink models. (2) Our new notion of diversity for output signals outperforms random baseline testing and an existing notion of signal diversity in revealing faults in Simulink models. (3) The fault revealing ability of our test generation approach outperforms that of the Simulink Design Verifier, the only testing toolbox for Simulink.
AB - All engineering disciplines are founded and rely on models, although they may differ on purposes and usages of modeling. Interdisciplinary domains such as Cyber Physical Systems (CPSs) seek approaches that incorporate different modeling needs and usages. Specifically, the Simulink modeling platform greatly appeals to CPS engineers due to its seamless support for simulation and code generation. In this paper, we propose a test generation approach that is applicable to Simulink models built for both purposes of simulation and code generation. We define test inputs and outputs as signals that capture evolution of values over time. Our test generation approach is implemented as a meta-heuristic search algorithm and is guided to produce test outputs with diverse shapes according to our proposed notion of diversity. Our evaluation, performed on industrial and public domain models, demonstrates that: (1) In contrast to the existing tools for testing Simulink models that are only applicable to a subset of code generation models, our approach is applicable to both code generation and simulation Simulink models. (2) Our new notion of diversity for output signals outperforms random baseline testing and an existing notion of signal diversity in revealing faults in Simulink models. (3) The fault revealing ability of our test generation approach outperforms that of the Simulink Design Verifier, the only testing toolbox for Simulink.
KW - Output diversity
KW - Search-based software testing
KW - Signal features
KW - Simulink Design Verifier (SLDV)
KW - Simulink models
KW - Software testing
KW - Structural coverage
KW - Time-continuous behaviors
UR - http://www.scopus.com/inward/record.url?scp=84971426915&partnerID=8YFLogxK
U2 - 10.1145/2884781.2884797
DO - 10.1145/2884781.2884797
M3 - Conference contribution
AN - SCOPUS:84971426915
T3 - Proceedings - International Conference on Software Engineering
SP - 595
EP - 606
BT - Proceedings - 2016 IEEE/ACM 38th IEEE International Conference on Software Engineering Companion, ICSE 2016
PB - IEEE Computer Society
T2 - 2016 IEEE/ACM 38th IEEE International Conference on Software Engineering, ICSE 2016
Y2 - 14 May 2016 through 22 May 2016
ER -