Conference item
Probabilistic fault localisation
- Abstract:
- Efficient fault localisation is becoming increasingly important as software grows in size and complexity. In this paper we present a new formal framework, denoted probabilistic fault localisation (pfl), and compare it to the established framework of spectrum based fault localisation (sbfl). We formally prove that pfl satisfies some desirable properties which sbfl does not, empirically demonstrate that pfl is signifuicantly more effective at finding faults than all known sbfl measures in large scale experimentation, and show pfl has comparable efficiency. Results show that the user investigates 37% more code (and finds a fault immediately in 27% fewer cases) when using the best performing sbfl measures, compared to the pfl framework. Furthermore, we show that it is theoretically impossible to design strictly rational sbfl measures that outperform pfl techniques on a large set of benchmarks.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
Actions
Access Document
- Files:
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(Preview, Accepted manuscript, pdf, 844.3KB, Terms of use)
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- Publisher copy:
- 10.1007/978-3-319-49052-6_5
Authors
- Publisher:
- Springer
- Host title:
- 12th International Haifa Verification Conference - Hardware and Software: Verification and Testing
- Journal:
- HVC 2016 - Hardware and Software: Verification and Testing More from this journal
- Publication date:
- 2016-11-01
- Acceptance date:
- 2016-09-05
- DOI:
- ISSN:
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0302-9743, 1611-3349
- ISBN:
- 9783319490519
- Keywords:
- Pubs id:
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pubs:664494
- UUID:
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uuid:f89f78f4-bf8f-4ee5-b6a3-66e5f38e3bec
- Local pid:
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pubs:664494
- Source identifiers:
-
664494
- Deposit date:
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2017-01-28
- ARK identifier:
Terms of use
- Copyright holder:
- Springer International Publishing AG
- Copyright date:
- 2016
- Notes:
- © Springer International Publishing AG 2016
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