- Title
- Predicting bug-fixing time: an empirical study of commercial software projects
- Creator
- Zhang, Hongyu; Gong, Liang; Versteeg, Steve
- Relation
- 2013 35th International Conference on Software Engineering (ICSE). 2013 35th International Conference on Software Engineering (ICSE) Proceedings ( San Francisco, CA 18-26 May, 2013) p. 1042-1051
- Publisher Link
- http://dx.doi.org/10.1109/ICSE.2013.6606654
- Publisher
- Institute of Electrical and Electronics Engineers (IEEE)
- Resource Type
- conference paper
- Date
- 2013
- Description
- For a large and evolving software system, the project team could receive many bug reports over a long period of time. It is important to achieve a quantitative understanding of bug-fixing time. The ability to predict bug-fixing time can help a project team better estimate software maintenance efforts and better manage software projects. In this paper, we perform an empirical study of bug-fixing time for three CA Technologies projects. We propose a Markov-based method for predicting the number of bugs that will be fixed in future. For a given number of defects, we propose a method for estimating the total amount of time required to fix them based on the empirical distribution of bug-fixing time derived from historical data. For a given bug report, we can also construct a classification model to predict slow or quick fix (e.g., below or above a time threshold). We evaluate our methods using real maintenance data from three CA Technologies projects. The results show that the proposed methods are effective.
- Subject
- bugs; bug fixing time; prediction; effort elimination; software maintenance
- Identifier
- http://hdl.handle.net/1959.13/1355860
- Identifier
- uon:31546
- Identifier
- ISBN:9781467330763
- Language
- eng
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