Early Identification of Invalid Bug Reports in Industrial Settings – A Case Study

Muhammad Laiq, Nauman bin Ali, Jürgen Böstler, Emelie Engström

Research output: Chapter in Book/Report/Conference proceedingPaper in conference proceedingpeer-review

Abstract

Software development companies spend considerable time resolving bug reports. However, bug reports might be invalid, i.e., not point to a valid flaw. Expensive resources and time might be expended on invalid bug reports before discovering that they are invalid. In this case study, we explore the impact of invalid bug reports and develop and assess the use of machine learning (ML) to indicate whether a bug report is likely invalid. We found that about 15% of bug reports at the case company are invalid, and that their resolution time is similar to valid bug reports. Among the ML-based techniques we used, logistic regression and SVM show promising results. In the feedback, practitioners indicated an interest in using the tool to identify invalid bug reports at early stages. However, they emphasized the need to improve the explainability of ML-based recommendations and to reduce the maintenance cost of the tool.

Original languageEnglish
Title of host publicationProduct-Focused Software Process Improvement - 23rd International Conference, PROFES 2022, Proceedings
EditorsDavide Taibi, Marco Kuhrmann, Tommi Mikkonen, Pekka Abrahamsson, Jil Klünder
PublisherSpringer Science and Business Media B.V.
Pages497-507
Number of pages11
ISBN (Print)9783031213878
DOIs
Publication statusPublished - 2022
Event23rd International Conference on Product-Focused Software Process Improvement, PROFES 2022 - Jyväskylä, Finland
Duration: 2022 Nov 212022 Nov 23

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13709 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference23rd International Conference on Product-Focused Software Process Improvement, PROFES 2022
Country/TerritoryFinland
CityJyväskylä
Period2022/11/212022/11/23

Subject classification (UKÄ)

  • Software Engineering

Free keywords

  • Bug classification
  • Bug reports
  • Invalid bugs
  • Machine learning
  • Software analytics
  • Valid bugs

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