Mutation operators for feature‐oriented software product lines
Summary Mutation testing is an approach to assess the quality of test cases. Mutants are modified versions of a system that ideally compose faulty behaviour. Test cases for a system are effective if they kill these mutants. For software product lines, several works have addressed mutation testing to...
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| Published in: | Software testing, verification & reliability Vol. 29; no. 1-2 |
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| Main Authors: | , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Chichester
Wiley Subscription Services, Inc
01.01.2019
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| Subjects: | |
| ISSN: | 0960-0833, 1099-1689 |
| Online Access: | Get full text |
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| Summary: | Summary
Mutation testing is an approach to assess the quality of test cases. Mutants are modified versions of a system that ideally compose faulty behaviour. Test cases for a system are effective if they kill these mutants. For software product lines, several works have addressed mutation testing to inject variability faults, which may only exist in some variants. These works focus on variability models or specific implementation techniques. In contrast, feature‐oriented programming has been rarely investigated, wherefore, we (1) derive corresponding mutation operators, (2) investigate the feasibility of our proposed and conventional operators on 4 software product lines, and (3) discuss open challenges in mutation testing of software product lines. The results show that our proposed operators are suitable to cause variability faults and extend the capabilities of conventional operators. Nonetheless, mutation testing of software product lines is comparably expensive, due to a high number of variants and mutants—resulting in equivalence and redundancy.
This article proposes a set of variability‐aware mutation operators to assess test cases of configurable systems (ie, implemented with feature‐oriented programming). The results show that the proposed operators are more suitable to assess the ability of tests to find variability faults, but they can also result in an increased number of redundant and equivalent mutants. Several open challenges of mutation testing for configurable systems are discussed to guide further research. |
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| Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| ISSN: | 0960-0833 1099-1689 |
| DOI: | 10.1002/stvr.1676 |