The Search-Based Mutation Testing of the Chinese Train Control System Level 3 On Board a Train Control System

In this article, we combined a search-based technique with model-based mutation testing to overcome the inherent computational cost that comes with the test-case generation of the Chinese Train Control System Level 3 (CTCS-3) train control system by providing a newly designed fitness function to guide the search process of test cases. First, we defined the test-case inputs as
timed input traces
, which can easily deal with noninput-enabled systems with both input events and input variables. Because the input sequence of the timed input traces can be potentially infinite, they can be more flexible in dealing with different scales of train control systems than can the traditional model-checking techniques. Furthermore, we proposed a way of encoding timed input traces as blocks of inputs for the genetic algorithm, together with crossover and mutation operators, to reduce the search space and improve algorithm efficiency. By using the encoded input blocks as individuals, the test cases generated from the train control system will be more compact and easier to perform. Finally, we applied the mutation operators to the mode-transition function of the CTCS-3 from which all of the known faults have been considered comprehensively. To evaluate the coverage of the test cases generated and compare the performance of different methods, the benchmarking indicators of conformance relation score (CRS), average CRS, and weighted CRS have all been analyzed. In addition, we performed an experiment to determine the extent to which the maximum block width can influence the search performance as a guidance for parameter selection in practice.