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Volume 55 Issue 5
Oct.  2020
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Journal of Southwest Jiaotong University  > 2020  >  55(5): 937-945, 962.
ZHOU Yangjing, FENG Zhiqiang, NING Po, WANG Changyong. Numerical Algorithm and Software Development for Metal Forming[J]. Journal of Southwest Jiaotong University, 2019, 54(4): 855-862. doi: 10.3969/j.issn.0258-2724.20170442
Citation: WEI Baiquan, LÜ Jidong, CHEN Kexing, TANG Tao, WANG Wei. Mutation Timed Automata with Input and Output-Based Method of Generating Test Suites for Chinese Train Control System Level 3[J]. Journal of Southwest Jiaotong University, 2020, 55(5): 937-945, 962. doi: 10.3969/j.issn.0258-2724.20180078
shu

Mutation Timed Automata with Input and Output-Based Method of Generating Test Suites for Chinese Train Control System Level 3

doi: 10.3969/j.issn.0258-2724.20180078
  • Received Date: 03 Feb 2018
  • Rev Recd Date: 01 Aug 2018
    • Available Online: 13 Jul 2020
  • Publish Date: 01 Oct 2020
    Abstract
  • In order to design and select the proper set of test cases so that all the known faults can be covered, an automatic test suite generation method was proposed for the Chinese train control system level 3 (CTCS-3) based on timed automata with input and output (TAIO) and mutation analysis. Firstly, according to the characteristics of the fault modes of the system mode transition, kinds of mutation operators (change action, change target, change source, etc.) had been designed, and 15106 mutants were generated. Secondly, based on the timed input and output conformance relation (tioco) and the k-Bounded model checking technique, 10 843 test cases were generated. Finally, the conformance relation score (CRS), average conformance relation score (ACRS) and weighted conformance relation score (WCRS) had been introduced to analyze the coverage of faults domain. The results show that the test cases generated can effectively cover the fault modes of change action, change invariant and sink location, however, the negate guard and invert reset fault modes cannot be effectively covered, which may require additional information of observation for the fault detection.

     

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