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Extracting structural information from bug reports

Published: 10 May 2008 Publication History

Abstract

In software engineering experiments, the description of bug reports is typically treated as natural language text, although it often contains stack traces, source code, and patches. Neglecting such structural elements is a loss of valuable information; structure usually leads to a better performance of machine learning approaches. In this paper, we present a tool called infoZilla that detects structural elements from bug reports with near perfect accuracy and allows us to extract them. We anticipate that infoZilla can be used to leverage data from bug reports at a different granularity level that can facilitate interesting research in the future.

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  • (2024)Prompting Is All You Need: Automated Android Bug Replay with Large Language ModelsProceedings of the IEEE/ACM 46th International Conference on Software Engineering10.1145/3597503.3608137(1-13)Online publication date: 20-May-2024
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cover image ACM Conferences
MSR '08: Proceedings of the 2008 international working conference on Mining software repositories
May 2008
162 pages
ISBN:9781605580241
DOI:10.1145/1370750
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 10 May 2008

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Author Tags

  1. bug reports
  2. patches
  3. source code
  4. stack traces
  5. structural information

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