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Reducing the Cost of Higher-Order Mutation Testing.

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Title: Reducing the Cost of Higher-Order Mutation Testing.
Authors: Ghiduk, Ahmed S.1,2 asaghiduk@tu.edu.sa, Girgis, Moheb R.3 moheb.girgis@mu.edu.eg, Shehata, Marwa H.1 marwahashem88@yahoo.com
Source: Arabian Journal for Science & Engineering (Springer Science & Business Media B.V. ). Dec2018, Vol. 43 Issue 12, p7473-7486. 14p.
Subjects: Mutation testing of computer software, Cost effectiveness, High-order derivatives (Mathematics)
Abstract: Constructing mutants of order higher than first order is a key step in higher-order mutation testing. The majority of higher-order mutant generation techniques merge two (or more) first-order mutants (FOMs) to build a higher-order mutant. Unfortunately, these techniques suffer from the high cost due to the explosion in the number of higher-order mutants (HOMs). Consequently, developing techniques to find the minimum adequate and effective number of mutants are desired. Earlier work reduced the number of mutants by considering only a subset of mutants, a subset of operators, or selecting specific locations in the program (to be mutated) instead of the whole program. In this paper, we present three new techniques (SCWR, 2E2O, and 2E2OWR) to generate and reduce the overall number of HOMs and the equivalent ones as well. Each technique merges FOMs in more effective and simpler way than the previous techniques to find more effective HOMs. These techniques have been applied on a benchmark of programs, and the results have been compared to the results of some related work such as DiffOp, JudyDiffOp, and Last2First techniques. The results showed that SCWR, 2E2O, and 2E2OWR outperformed the related work and reduced the total number of mutants by 67.9, 16.0, and 60.1% comparing to approximately 50% for the related work and the number of equivalent mutants by 66.9, 79.6, and 65.0% comparing to 25.8 and 36.4% for the related work, respectively. [ABSTRACT FROM AUTHOR]
Copyright of Arabian Journal for Science & Engineering (Springer Science & Business Media B.V. ) is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: <searchLink fieldCode="DE" term="%22Mutation+testing+of+computer+software%22">Mutation testing of computer software</searchLink><br /><searchLink fieldCode="DE" term="%22Cost+effectiveness%22">Cost effectiveness</searchLink><br /><searchLink fieldCode="DE" term="%22High-order+derivatives+%28Mathematics%29%22">High-order derivatives (Mathematics)</searchLink>
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  Data: Constructing mutants of order higher than first order is a key step in higher-order mutation testing. The majority of higher-order mutant generation techniques merge two (or more) first-order mutants (FOMs) to build a higher-order mutant. Unfortunately, these techniques suffer from the high cost due to the explosion in the number of higher-order mutants (HOMs). Consequently, developing techniques to find the minimum adequate and effective number of mutants are desired. Earlier work reduced the number of mutants by considering only a subset of mutants, a subset of operators, or selecting specific locations in the program (to be mutated) instead of the whole program. In this paper, we present three new techniques (SCWR, 2E2O, and 2E2OWR) to generate and reduce the overall number of HOMs and the equivalent ones as well. Each technique merges FOMs in more effective and simpler way than the previous techniques to find more effective HOMs. These techniques have been applied on a benchmark of programs, and the results have been compared to the results of some related work such as DiffOp, JudyDiffOp, and Last2First techniques. The results showed that SCWR, 2E2O, and 2E2OWR outperformed the related work and reduced the total number of mutants by 67.9, 16.0, and 60.1% comparing to approximately 50% for the related work and the number of equivalent mutants by 66.9, 79.6, and 65.0% comparing to 25.8 and 36.4% for the related work, respectively. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Arabian Journal for Science & Engineering (Springer Science & Business Media B.V. ) is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1007/s13369-018-3108-3
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      – SubjectFull: Cost effectiveness
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      – SubjectFull: High-order derivatives (Mathematics)
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              Text: Dec2018
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