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Pathidea: Improving Information Retrieval-Based Bug Localization by Re-Constructing Execution Paths Using Logs

delete2022-08-01
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AI
A
An Ran Chen *
T
Tse-Hsun Chen
S
Shaowei Wang
DOI:10.1109/TSE.2021.3071473delete
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摘要

摘要

En 中文
To assist developers with debugging and analyzing bug reports, researchers have proposed information retrieval-based bug localization (IRBL) approaches. IRBL approaches leverage the textual information in bug reports as queries to generate a ranked list of potential buggy files that may need further investigation. Although IRBL approaches have shown promising results, most prior research only leverages the textual information that is visible in bug reports, such as bug description or title. However, in addition to the textual description of the bug, developers also often attach logs in bug reports. Logs provide important information that can be used to re-construct the system execution paths when an issue happens and assist developers with debugging. In this paper, we propose an IRBL approach, Pathidea, which leverages logs in bug reports to re-construct execution paths and helps improve the results of bug localization. Pathidea uses static analysis to create a file-level call graph, and re-constructs the call paths from the reported logs. We evaluate Pathidea on eight open source systems, with a total of 1,273 bug reports that contain logs. We find that Pathidea achieves a high recall (up to 51.9 percent for Top@5). On average, Pathidea achieves an improvement that varies from 8 to 21 and 5 to 21 percent over BRTracer in terms of Mean Average Precision (MAP) and Mean Reciprocal Rank (MRR) across studied systems, respectively. Moreover, we find that the re-constructed execution paths can also complement other IRBL approaches by providing a 10 and 8 percent improvement in terms of MAP and MRR, respectively. Finally, we conduct a parameter sensitivity analysis and provide recommendations on setting the parameter values when applying Pathidea.
Keyword:
Computer bugs
Location awareness
Debugging
Static analysis
Information retrieval
History
Tools
Bug localization
log
bug report
information retrieval
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期刊

IEEE Transactions on Software Engineering 封面图
IEEE Transactions on Software Engineering
IF:
5.6
论文数:
2.9K
被引数:
1.1W

机构

U
University of Manitoba
学者数:
1.9W
论文数: 1.7W
被引数: 18
C
concordia university - canada
学者数:
8.0K
论文数: 8.9K
被引数: 4
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