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University of Lethbridge

Detecting planning conversations in bug reports

Abstract

Software developers refer to bug reports as a reliable source of information. However, these bug reports are written in the form of conversations among developers and often become long depending on the complexity of the issue, necessitating a significant amount of time and effort to locate the desired information. Prior work focused on tagging the different types of information in the bug reports. However, their work did not identify Plans. In our work, we focus on retrieving Plans from bug reports and labeling them with a Plan Labeller. First, we analyzed bug reports to identify which section contains Plans. Then we examined three methods to detect Plans. Based on that, we found keywords and key-phrases to be the best approach. We applied lists of keywords and key-phrases iteratively to randomly selected bug reports to construct a list of keywords and key-phrases that can identify Plans in a bug report.

Author and committee

dc:creator, dc:contributor.*
Authors
  • Islam, Rafat Bin
  • University of Lethbridge. Faculty of Arts and Science

Subjects

dc:subject × 8

Identifiers

dc:identifier.*
Identifier
hdl:10133/6415
OAI identifier oai:identifier
oai:opus.uleth.ca:10133/6415

Chain of custody

source
Harvested from
University of Lethbridge
Base URL
opus.uleth.ca/server/oai/request
Last updated
2026-07-27
Source record
OAI-PMH GetRecord
citation

Islam, Rafat Bin; University of Lethbridge. Faculty of Arts and Science. Detecting planning conversations in bug reports. 2022.