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  • 1.
    Lindström, Birgitta
    et al.
    Högskolan i Skövde, Institutionen för informationsteknologi. Högskolan i Skövde, Forskningscentrum för Informationsteknologi.
    Márki, András
    Högskolan i Skövde, Institutionen för informationsteknologi. Högskolan i Skövde, Forskningscentrum för Informationsteknologi.
    On redundant mutants and strong mutation2015Rapport (Övrigt vetenskapligt)
    Abstract [en]

    This study evaluates a theory of subsumption relations among mutants created by the ROR mutation operator, thus making most of these mutants redundant. A redundant mutant can be skipped during mutation analysis without decreasing the quality of the resulting test suite. This theory is interesting since mutation testing is computationally expensive and the theory states that the set of ROR mutants can be reduced by 57%. The reduced set of ROR mutants has therefore, been used in several recent studies. However, we provide proof that this theory do not hold for strong mutation and that part of the theory is incorrect. The theory itself has to our knowledge, never before been evaluated empirically.

    By finding counter examples, we prove that a test suite, which is 100% adequate for the non-redundant ROR mutants might not be 100% adequate for the mutants, which are supposed to be redundant. The subsumption relations do not hold for strong mutation. We have also proved that more than one top-level mutant can be detected by the same test. This should not be possible according to the theory. Hence, this part of the theory is incorrect, independent of strong or weak mutation.

    Our findings are important since strong mutation is frequently used to evaluate test suites and testing criteria. Just as redundant mutants can give an overestimation of the mutation score for a test suite, using the reduced set can give an underestimation. Results reported from such studies should therefore, be accompanied by information on whether the reduced or complete set of ROR was used and if the researchers used strong or weak mutation.

  • 2.
    Lindström, Birgitta
    et al.
    Högskolan i Skövde, Institutionen för informationsteknologi. Högskolan i Skövde, Forskningscentrum för Informationsteknologi.
    Márki, András
    Högskolan i Skövde, Institutionen för informationsteknologi. Högskolan i Skövde, Forskningscentrum för Informationsteknologi.
    On Strong Mutation and Subsuming Mutants2016Ingår i: Proceedings: 2016 IEEE International Conference on Software Testing, Verification and Validation Workshops, IEEE Computer Society, 2016, s. 112-121Konferensbidrag (Refereegranskat)
    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.

  • 3.
    Lindström, Birgitta
    et al.
    Högskolan i Skövde, Institutionen för informationsteknologi. Högskolan i Skövde, Forskningscentrum för Informationsteknologi.
    Márki, András
    Högskolan i Skövde, Institutionen för informationsteknologi. Högskolan i Skövde, Forskningscentrum för Informationsteknologi.
    On strong mutation and the theory of subsuming logic‐based mutants2019Ingår i: Software testing, verification & reliability, ISSN 0960-0833, E-ISSN 1099-1689, Vol. 29, nr 1-2 Special Issue: SI, s. 1-23, artikel-id e1667Artikel i tidskrift (Refereegranskat)
    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.

  • 4.
    Lindström, Birgitta
    et al.
    Högskolan i Skövde, Institutionen för informationsteknologi. Högskolan i Skövde, Forskningsmiljön Informationsteknologi.
    Offutt, Jeff
    George Mason University, United States.
    Baral, Kesina
    George Mason University, United States.
    Márki, András
    Högskolan i Skövde, Institutionen för informationsteknologi. Högskolan i Skövde, Forskningsmiljön Informationsteknologi.
    Message from the TestEd 2020 Chairs2020Ingår i: 2020 IEEE 13th International Conference on Software Testing, Verification and Validation Workshops: 23–27 March 2020 Porto, Portugal, IEEE, 2020, artikel-id 9155714Konferensbidrag (Övrigt vetenskapligt)
  • 5.
    Márki, András
    Högskolan i Skövde, Institutionen för informationsteknologi. Högskolan i Skövde, Forskningscentrum för Informationsteknologi.
    Towards minimal mutation analysis: Using the approximated dominator set of mutants2019Rapport (Övrigt vetenskapligt)
    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.

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  • 6.
    Márki, András
    et al.
    Högskolan i Skövde, Institutionen för informationsteknologi. Högskolan i Skövde, Forskningscentrum för Informationsteknologi.
    Lindström, Birgitta
    Högskolan i Skövde, Institutionen för informationsteknologi. Högskolan i Skövde, Forskningscentrum för Informationsteknologi.
    Mutation tools for Java2017Ingår i: SAC '17 Proceedings of the Symposium on Applied Computing, Association for Computing Machinery (ACM), 2017, s. 1364-1371Konferensbidrag (Refereegranskat)
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