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  • 1.
    Lindström, Birgitta
    et al.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Márki, András
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    On Strong Mutation and Subsuming Mutants2016In: Proceedings: 2016 IEEE International Conference on Software Testing, Verification and Validation Workshops, IEEE Computer Society, 2016, p. 112-121Conference paper (Refereed)
    Abstract [en]

    Mutation analysis is a powerful technique for software testing but it is also known to be computationally expensive.The main reason for the high computational cost is that many of themutants are redundant and thus, do not contribute to the quality of the test suite. One of the most promising approaches toavoid producing redundant mutants is to identify subsumption relations among mutants, preferably before these are generated.Such relations have for example, been identified at an operator level for mutants created by the ROR operator. This reduced set of non-redundant mutants hasbeen used in several recent studies and is also the default option in at least one mutation testing tool that supports strong mutation. This raises questions on whether the identified subsumption relations between the mutants hold in a context ofstrong mutation or variants of weak mutation that require some limited error propagation (firm mutation).

    We have conducted an experimental study to investigate the subsumption relations in the context of strong or firm mutation.We observed that it is possible to create a test suite that is 100\% adequate for the reduced set of mutants while not being 100\% adequate for the complete set. This shows that the subsumption relations do not hold for strong or firm mutation. We provide several examples on this behavior and discuss the root causes. Our findings are important since strong and firm mutation both are frequently used to evaluate test suites and testing criteria. The choice of whether to use a reduced set of mutants or an entire set should however, not be made without consideration of the context in which they are used (i.e., strong, firm or weak mutation) since the subsumption relations between ROR mutants do not hold for strong or firm mutation.Just as redundant mutants can give an overestimation of the mutation score for a test suite, using the reduced set of mutantscan give an underestimation if used together with strong or firm mutation. Results reported from such studies should therefore, be accompanied by information on whether the reduced or complete set of mutants was used and if the researchers used strong, firm or weak mutation.

  • 2.
    Lindström, Birgitta
    et al.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Márki, András
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    On strong mutation and the theory of subsuming logic‐based mutants2019In: Software testing, verification & reliability, ISSN 0960-0833, E-ISSN 1099-1689, Vol. 29, no 1-2 Special Issue: SI, p. 1-23, article id e1667Article in journal (Refereed)
    Abstract [en]

    Redundant mutants might cause problems when benchmarking since testing techniques can get high scores without detecting any nonredundant mutants. However, removing nonredundant mutants might cause similar problems. Subsumed mutants are per definition also redundant since no additional tests are required to detect them once all other mutants are detected. We focus on relational operator replacement (ROR) and conditional operator replacement mutants. Subsumption relations between ROR mutants are defined by fault hierarchies. The fault hierarchies are proven for weak mutation but have since they were published been used with strong mutation. We prove that ROR fault hierarchies do not hold for strong mutation and show why. We also show that the probability for a random test to experience the problem can be more than 30% and that 50% of the mutants might be affected in a real software system. Finally, we show that there is a similar problem with the theory on sufficient conditional operator replacement.

  • 3.
    Márki, András
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Towards minimal mutation analysis: Using the approximated dominator set of mutants2019Report (Other academic)
    Abstract [en]

    In mutation testing, variants (i.e., mutants) of the software under test are created. Themutants are then used to design tests that can detect the difference between the mutantsand the original software under test. Empirical studies have shown that test suites thatare effective in detecting mutants are also effective in detecting real faults. Mutationanalysis is therefore often used to benchmark effectiveness of other testing techniques.The main drawback of mutation testing is that it is computationally expensive becauseof the large number of mutants to analyze. It is well known that many of these mutantsare redundant and recent studies have shown that the redundancy among the mutantscan be up to 99%. However, identifying which mutants that are redundant is challengingsince this depends on the software under test as well as the specific mutations.

    This work aims to combine techniques from areas, such as static analysis and machinelearning, in a process for cost-effective mutation analysis. Such techniques are expectedto provide partial solutions to the problem of avoiding creation of the redundant mutants.The outcome of this research is two-fold: (i) an evaluation of techniques that canbe used to minimize the set of non-redundant mutants that needs to be created, and (ii)a process for mutation analysis combining such minimization techniques. A frameworkwill also be developed to evaluate the minimization techniques and the entire process.

  • 4.
    Márki, András
    et al.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Lindström, Birgitta
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Mutation tools for Java2017In: SAC '17 Proceedings of the Symposium on Applied Computing, Association for Computing Machinery (ACM), 2017, p. 1364-1371Conference paper (Refereed)
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