Evaluation of Mutation Testing in a Nuclear Industry Case Study

For software quality assurance, many safety-critical industries appeal to the use of dynamic testing and structural coverage criteria. However, there are reasons to doubt the adequacy of such practices. Mutation testing has been suggested as an alternative or complementary approach but its cost has traditionally hindered its adoption by industry, and there are limited studies applying it to real safety-critical code. This paper evaluates the effectiveness of state-of-the-art mutation testing on safety-critical code from within the U.K. nuclear industry, in terms of revealing flaws in test suites that already meet the structural coverage criteria recommended by relevant safety standards. It also assesses the practical feasibility of implementing such mutation testing in a real setting. We applied a conventional selective mutation approach to a C codebase supplied by a nuclear industry partner and measured the mutation score achieved by the existing test suite. We repeated the experiment using trivial compiler equivalence (TCE) to assess the benefit that it might provide. Using a conventional approach, it first appeared that the existing test suite only killed 82% of the mutants, but applying TCE revealed that it killed 92%. The difference was due to equivalent or duplicate mutants that TCE eliminated. We then added new tests to kill all the surviving mutants, increasing the test suite size by 18% in the process. In conclusion, mutation testing can potentially improve fault detection compared to structural-coverage-guided testing, and may be affordable in a nuclear industry context. The industry feedback on our results was positive, although further evidence is needed from application of mutation testing to software with known real faults

Assessment of C++ object-oriented mutation operators: A selective mutation approach

Mutation testing is an effective but costly testing technique. Several studies have observed that some mutants can be redundant and therefore removed without affecting its effectiveness. Similarly, some mutants may be more effective than others in guiding the tester on the creation of high‐quality test cases. On the basis of these findings, we present an assessment of C++ class mutation operators by classifying them into 2 rankings: the first ranking sorts the operators on the basis of their degree of redundancy and the second regarding the quality of the tests they help to design. Both rankings are used in a selective mutation study analysing the trade‐off between the reduction achieved and the effectiveness when using a subset of mutants. Experimental results consistently show that leveraging the operators at the top of the 2 rankings, which are different, lead to a significant reduction in the number of mutants with a minimum loss of effectiveness