Ammonia: an approach for deriving project-specific bug patterns
書誌事項
- 公開日
- 2020-03-07
- 資源種別
- journal article
- 権利情報
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- https://creativecommons.org/licenses/by/4.0
- https://creativecommons.org/licenses/by/4.0
- DOI
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- 10.1007/s10664-020-09807-w
- 10.48550/arxiv.2001.09630
- 公開者
- Springer Science and Business Media LLC
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説明
<jats:title>Abstract</jats:title><jats:p>Finding and fixing buggy code is an important and cost-intensive maintenance task, and static analysis (SA) is one of the methods developers use to perform it. SA tools warn developers about potential bugs by scanning their source code for commonly occurring bug patterns, thus giving those developers opportunities to fix the warnings (potential bugs) before they release the software. Typically, SA tools scan for general bug patterns that are common to any software project (such as null pointer dereference), and not for project specific patterns. However, past research has pointed to this lack of customizability as a severe limiting issue in SA. Accordingly, in this paper, we propose an approach called , which is based on statically analyzing changes across the development history of a project, as a means to identify project-specific bug patterns. Furthermore, the bug patterns identified by our tool do not relate to just one developer or one specific commit, they reflect the project as a whole and compliment the warnings from other SA tools that identify general bug patterns. Herein, we report on the application of our implemented tool and approach to four Java projects: , , , and . The results obtained show that our tool could detect 19 project specific bug patterns across those four projects. Next, through manual analysis, we determined that six of those change patterns were actual bugs and submitted pull requests based on those bug patterns. As a result, five of the pull requests were merged.</jats:p>
収録刊行物
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- Empirical Software Engineering
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Empirical Software Engineering 25 (3), 1951-1979, 2020-03-07
Springer Science and Business Media LLC
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詳細情報 詳細情報について
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- CRID
- 1361975840802440320
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- ISSN
- 15737616
- 13823256
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- HANDLE
- 10061/14124
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- 資料種別
- journal article
-
- データソース種別
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- Crossref
- KAKEN
- OpenAIRE
- IRDB
