Bug-fix time prediction models: Can we do better?

Pamela Bhattacharya, Iulian Neamtiu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

85 Scopus citations

Abstract

Predicting bug-fix time is useful in several areas of software evolution, such as predicting software quality or coordinating development effort during bug triaging. Prior work has proposed bug-fix time prediction models that use various bug report attributes (e.g., number of developers who participated in fixing the bug, bug severity, number of patches, bug-opener's reputation) for estimating the time it will take to fix a newly-reported bug. In this paper we take a step towards constructing more accurate and more general bug-fix time prediction models by showing how existing models fail to validate on large projects widely-used in bug studies. In particular, we used multivariate and univariate regression testing to test the prediction significance of existing models on 512,474 bug reports from five open source projects: Eclipse, Chrome and three products from the Mozilla project (Firefox, Seamonkey and Thunderbird). The results of our regression testing indicate that the predictive power of existing models is between 30% and 49% and that there is a need for more independent variables (attributes) when constructing a prediction model. Additionally, we found that, unlike in prior recent studies on commercial software, in the projects we examined there is no correlation between bug-fix likelihood, bug-opener's reputation and the time it takes to fix a bug. These findings indicate three open research problems: (1) assessing whether prioritizing bugs using bug-opener's reputation is beneficial, (2) identifying attributes which are effective in predicting bug-fix time, and (3) constructing bug-fix time prediction models which can be validated on multiple projects.

Original languageEnglish (US)
Title of host publicationMSR'11
Subtitle of host publicationProceedings of the 8th Working Conference on Mining Software Repositories, Co-located with ICSE 2011
Pages207-210
Number of pages4
DOIs
StatePublished - Jun 22 2011
Externally publishedYes
Event8th Working Conference on Mining Software Repositories, MSR 2011, Co-located with ICSE 2011 - Waikiki, Honolulu, HI, United States
Duration: May 21 2011May 22 2011

Other

Other8th Working Conference on Mining Software Repositories, MSR 2011, Co-located with ICSE 2011
Country/TerritoryUnited States
CityWaikiki, Honolulu, HI
Period5/21/115/22/11

All Science Journal Classification (ASJC) codes

  • Software

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