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  • 1.
    González-Hernández, Loreto
    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.
    Offutt, Jeff
    George Mason University, USA.
    Andler, Sten F.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Potena, Pasqualina
    RISE SICS, Västerås.
    Bohlin, Markus
    RISE SICS, Västerås.
    Using Mutant Stubbornness to Create Minimal and Prioritized Test Sets2018In: 2018 IEEE International Conference on Software Quality, Reliability and Security (QRS), IEEE Computer Society, 2018, p. 446-457Conference paper (Refereed)
    Abstract [en]

    In testing, engineers want to run the most useful tests early (prioritization). When tests are run hundreds or thousands of times, minimizing a test set can result in significant savings (minimization). This paper proposes a new analysis technique to address both the minimal test set and the test case prioritization problems. This paper precisely defines the concept of mutant stubbornness, which is the basis for our analysis technique. We empirically compare our technique with other test case minimization and prioritization techniques in terms of the size of the minimized test sets and how quickly mutants are killed. We used seven C language subjects from the Siemens Repository, specifically the test sets and the killing matrices from a previous study. We used 30 different orders for each set and ran every technique 100 times over each set. Results show that our analysis technique performed significantly better than prior techniques for creating minimal test sets and was able to establish new bounds for all cases. Also, our analysis technique killed mutants as fast or faster than prior techniques. These results indicate that our mutant stubbornness technique constructs test sets that are both minimal in size, and prioritized effectively, as well or better than other techniques.

  • 2.
    Lindström, Birgitta
    et al.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Offutt, Jeff
    George Mason University, USA.
    González-Hernández, Loreto
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Andler, Sten F.
    University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre.
    Identifying Useful Mutants to Test Time Properties2018In: 2018 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW), IEEE Computer Society, 2018, p. 69-76Conference paper (Refereed)
    Abstract [en]

    Real-time systems have to be verified and tested for timely behavior as well as functional behavior. Thus, time is an extra dimension that adds to the complexity of software testing. A timed automata model with a model-checker can be used to generate timed test traces. To properly test the timely behavior, the set of test traces should challenge the different time constraints in the model. This paper describes and adapts mutation operators that target such time constraints in timed automata models. Time mutation operators apply a delta to the time constraints to help testers design tests that exceed the time constraints. We suggest that the size of this delta determines how easy the mutant is to kill and that the optimal delta varies by the program, mutation operator, and the individual mutant. To avoid trivial and equivalent time mutants, the delta should be set individually for each mutant. We discuss mutant subsumption and define the problem of finding dominator mutants in this new domain. In this position paper, we outline an iterative tuning process where a statistical model-checker, UPPAAL SMC, is used to: (i) create a tuned set of dominator time mutants, and (ii) generate test traces that kill the mutants.

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