A systematic literature review of how mutation testing supports quality assurance processes.
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| Title: | A systematic literature review of how mutation testing supports quality assurance processes. |
|---|---|
| Authors: | Zhu, Qianqian1 qianqian.zhu@tudelft.nl, Panichella, Annibale1, Zaidman, Andy1 |
| Source: | Software Testing: Verification & Reliability. Sep2018, Vol. 28 Issue 6, p1-1. 39p. |
| Subjects: | Mutation testing of computer software, Computer software testing, Debugging, Electronic data processing, Data editing |
| Abstract: | Summary: Mutation testing has been very actively investigated by researchers since the 1970s, and remarkable advances have been achieved in its concepts, theory, technology, and empirical evidence. While the most influential realisations have been summarised by existing literature reviews, we lack insight into how mutation testing is actually applied. Our goal is to identify and classify the main applications of mutation testing and analyse the level of replicability of empirical studies related to mutation testing. To this aim, this paper provides a systematic literature review on the application perspective of mutation testing based on a collection of 191 papers published between 1981 and 2015. In particular, we analysed in which quality assurance processes mutation testing is used, which mutation tools and which mutation operators are employed. Additionally, we also investigated how the inherent core problems of mutation testing, ie, the equivalent mutant problem and the high computational cost, are addressed during the actual usage. The results show that most studies use mutation testing as an assessment tool targeting unit tests, and many of the supporting techniques for making mutation testing applicable in practice are still underdeveloped. Based on our observations, we made 9 recommendations for future work, including an important suggestion on how to report mutation testing in testing experiments in an appropriate manner. [ABSTRACT FROM AUTHOR] |
| Copyright of Software Testing: Verification & Reliability is the property of Wiley-Blackwell 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.) | |
| Database: | Engineering Source |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 131298337 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: A systematic literature review of how mutation testing supports quality assurance processes. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Zhu%2C+Qianqian%22">Zhu, Qianqian</searchLink><relatesTo>1</relatesTo><i> qianqian.zhu@tudelft.nl</i><br /><searchLink fieldCode="AR" term="%22Panichella%2C+Annibale%22">Panichella, Annibale</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Zaidman%2C+Andy%22">Zaidman, Andy</searchLink><relatesTo>1</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Software+Testing%3A+Verification+%26+Reliability%22">Software Testing: Verification & Reliability</searchLink>. Sep2018, Vol. 28 Issue 6, p1-1. 39p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Mutation+testing+of+computer+software%22">Mutation testing of computer software</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+software+testing%22">Computer software testing</searchLink><br /><searchLink fieldCode="DE" term="%22Debugging%22">Debugging</searchLink><br /><searchLink fieldCode="DE" term="%22Electronic+data+processing%22">Electronic data processing</searchLink><br /><searchLink fieldCode="DE" term="%22Data+editing%22">Data editing</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Summary: Mutation testing has been very actively investigated by researchers since the 1970s, and remarkable advances have been achieved in its concepts, theory, technology, and empirical evidence. While the most influential realisations have been summarised by existing literature reviews, we lack insight into how mutation testing is actually applied. Our goal is to identify and classify the main applications of mutation testing and analyse the level of replicability of empirical studies related to mutation testing. To this aim, this paper provides a systematic literature review on the application perspective of mutation testing based on a collection of 191 papers published between 1981 and 2015. In particular, we analysed in which quality assurance processes mutation testing is used, which mutation tools and which mutation operators are employed. Additionally, we also investigated how the inherent core problems of mutation testing, ie, the equivalent mutant problem and the high computational cost, are addressed during the actual usage. The results show that most studies use mutation testing as an assessment tool targeting unit tests, and many of the supporting techniques for making mutation testing applicable in practice are still underdeveloped. Based on our observations, we made 9 recommendations for future work, including an important suggestion on how to report mutation testing in testing experiments in an appropriate manner. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Software Testing: Verification & Reliability is the property of Wiley-Blackwell 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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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1002/stvr.1675 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 39 StartPage: 1 Subjects: – SubjectFull: Mutation testing of computer software Type: general – SubjectFull: Computer software testing Type: general – SubjectFull: Debugging Type: general – SubjectFull: Electronic data processing Type: general – SubjectFull: Data editing Type: general Titles: – TitleFull: A systematic literature review of how mutation testing supports quality assurance processes. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Zhu, Qianqian – PersonEntity: Name: NameFull: Panichella, Annibale – PersonEntity: Name: NameFull: Zaidman, Andy IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 09 Text: Sep2018 Type: published Y: 2018 Identifiers: – Type: issn-print Value: 09600833 Numbering: – Type: volume Value: 28 – Type: issue Value: 6 Titles: – TitleFull: Software Testing: Verification & Reliability Type: main |
| ResultId | 1 |
