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- Publisher Website: 10.1002/9781119880929.ch13
- Scopus: eid_2-s2.0-85161195512
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Book Chapter: Emerging aspects of software fault localization
| Title | Emerging aspects of software fault localization |
|---|---|
| Authors | |
| Keywords | Automated test case generation tool Fault localization tool Machine-learning approach Metamorphic relations |
| Issue Date | 20-Apr-2023 |
| Publisher | Wiley |
| Abstract | In this final chapter of the Handbook, we introduce emerging, innovative methods in software fault localization. First, we present scientific and systematic hypothesis-testing techniques and show they may be applied in practice. Second, for fault localization in the absence of a test oracle, we present a semi-proving methodology based on metamorphic relations and symbolic evaluation. It hinges on causes and effects instead of statistical probabilities. Third, we present an approach to predict the effectiveness of fault localization tools using machine learning. Lastly, we discuss why manually produced test cases are not ideal for fault localization and explain how to mitigate the problem by using automatically generated test cases. |
| Persistent Identifier | http://hdl.handle.net/10722/354580 |
| ISBN |
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Tse, TH | - |
| dc.contributor.author | Lo, D | - |
| dc.contributor.author | Groce, A | - |
| dc.contributor.author | Perscheid, M | - |
| dc.contributor.author | Hirschfeld, R | - |
| dc.contributor.author | Wong, WE | - |
| dc.date.accessioned | 2025-02-21T00:35:04Z | - |
| dc.date.available | 2025-02-21T00:35:04Z | - |
| dc.date.issued | 2023-04-20 | - |
| dc.identifier.isbn | 9781119291800 | - |
| dc.identifier.uri | http://hdl.handle.net/10722/354580 | - |
| dc.description.abstract | <p>In this final chapter of the Handbook, we introduce emerging, innovative methods in software fault localization. First, we present scientific and systematic hypothesis-testing techniques and show they may be applied in practice. Second, for fault localization in the absence of a test oracle, we present a semi-proving methodology based on metamorphic relations and symbolic evaluation. It hinges on causes and effects instead of statistical probabilities. Third, we present an approach to predict the effectiveness of fault localization tools using machine learning. Lastly, we discuss why manually produced test cases are not ideal for fault localization and explain how to mitigate the problem by using automatically generated test cases.<br></p> | - |
| dc.language | eng | - |
| dc.publisher | Wiley | - |
| dc.relation.ispartof | Handbook of Software Fault Localization: Foundations and Advances | - |
| dc.subject | Automated test case generation tool | - |
| dc.subject | Fault localization tool | - |
| dc.subject | Machine-learning approach | - |
| dc.subject | Metamorphic relations | - |
| dc.title | Emerging aspects of software fault localization | - |
| dc.type | Book_Chapter | - |
| dc.identifier.doi | 10.1002/9781119880929.ch13 | - |
| dc.identifier.scopus | eid_2-s2.0-85161195512 | - |
| dc.identifier.spage | 529 | - |
| dc.identifier.epage | 579 | - |
| dc.identifier.eisbn | 9781119880929 | - |
