Multi-objective test suite optimization for detection and localization of software faults
Testing of software is done with an intention to find faults. If a fault is there then it needs to be detected, located and then resolved. Fault detection and localization are adjoining activities and thus it is difficult to combine them. Fault detection requires test information that helps in detec...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2022-06-01
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| Series: | Journal of King Saud University: Computer and Information Sciences |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1319157819313850 |
| _version_ | 1818236032333643776 |
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| author | Neha Gupta Arun Sharma Manoj Kumar Pachariya |
| author_facet | Neha Gupta Arun Sharma Manoj Kumar Pachariya |
| author_sort | Neha Gupta |
| collection | DOAJ |
| description | Testing of software is done with an intention to find faults. If a fault is there then it needs to be detected, located and then resolved. Fault detection and localization are adjoining activities and thus it is difficult to combine them. Fault detection requires test information that helps in detecting the faults early whereas fault localization requires information which helps in locating the faults accurately. But test information is one common thing that is required for both the activities. This pre-condition helps to effectively combine both fault detection and localization. In this research work, a code and mutant coverage based multi-objective approach has been proposed to produce a minimized test suite having the ability of both detecting and locating faults. For optimization of test cases, NSGA-II algorithm has been used. Results on the projects of Defects4j repository depicts that the proposed approach is able to produce minimized test suites having the capability of detecting 95.16% of faults and locating all detected faults with fault localization score almost equivalent to that of the complete test suite. The average percentage of reduction in test suite size is 78% which is a good reduction percentage with the given fault detection and localization scores. |
| first_indexed | 2024-12-12T12:03:25Z |
| format | Article |
| id | doaj.art-013fa6f97d544c3e80656f5376c22224 |
| institution | Directory Open Access Journal |
| issn | 1319-1578 |
| language | English |
| last_indexed | 2024-12-12T12:03:25Z |
| publishDate | 2022-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of King Saud University: Computer and Information Sciences |
| spelling | doaj.art-013fa6f97d544c3e80656f5376c222242022-12-22T00:25:03ZengElsevierJournal of King Saud University: Computer and Information Sciences1319-15782022-06-0134628972909Multi-objective test suite optimization for detection and localization of software faultsNeha Gupta0Arun Sharma1Manoj Kumar Pachariya2Department of Information Technology, Indira Gandhi Delhi Technical University for Women, New Delhi 110006, India; Corresponding author.Department of Information Technology, Indira Gandhi Delhi Technical University for Women, New Delhi 110006, IndiaDepartment of Computer Science and Applications, Makhanlal Chaturvedi National University of Journalism and Communication, Bhopal 462011, IndiaTesting of software is done with an intention to find faults. If a fault is there then it needs to be detected, located and then resolved. Fault detection and localization are adjoining activities and thus it is difficult to combine them. Fault detection requires test information that helps in detecting the faults early whereas fault localization requires information which helps in locating the faults accurately. But test information is one common thing that is required for both the activities. This pre-condition helps to effectively combine both fault detection and localization. In this research work, a code and mutant coverage based multi-objective approach has been proposed to produce a minimized test suite having the ability of both detecting and locating faults. For optimization of test cases, NSGA-II algorithm has been used. Results on the projects of Defects4j repository depicts that the proposed approach is able to produce minimized test suites having the capability of detecting 95.16% of faults and locating all detected faults with fault localization score almost equivalent to that of the complete test suite. The average percentage of reduction in test suite size is 78% which is a good reduction percentage with the given fault detection and localization scores.http://www.sciencedirect.com/science/article/pii/S1319157819313850Fault detectionMulti-objective optimizationFault localizationCode coverageMutant partitioningTest suite reduction |
| spellingShingle | Neha Gupta Arun Sharma Manoj Kumar Pachariya Multi-objective test suite optimization for detection and localization of software faults Journal of King Saud University: Computer and Information Sciences Fault detection Multi-objective optimization Fault localization Code coverage Mutant partitioning Test suite reduction |
| title | Multi-objective test suite optimization for detection and localization of software faults |
| title_full | Multi-objective test suite optimization for detection and localization of software faults |
| title_fullStr | Multi-objective test suite optimization for detection and localization of software faults |
| title_full_unstemmed | Multi-objective test suite optimization for detection and localization of software faults |
| title_short | Multi-objective test suite optimization for detection and localization of software faults |
| title_sort | multi objective test suite optimization for detection and localization of software faults |
| topic | Fault detection Multi-objective optimization Fault localization Code coverage Mutant partitioning Test suite reduction |
| url | http://www.sciencedirect.com/science/article/pii/S1319157819313850 |
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