Determining Implementation Expertise from Bug Reports

As developers work on a software product they accumulate expertise, including expertise about the code base of the software product. We call this type of expertise 'implementation expertise'. Knowing the set of developers who have implementation expertise for a software product has many important uses. This paper presents an empirical evaluation of two approaches to determining implementation expertise from the data in source and bug repositories. The expertise sets created by the approaches are compared to those provided by experts and evaluated using the measures of precision and recall. We found that both approaches are good at finding all of the appropriate developers, although they vary in how many false positives are returned.

[1]  Massimiliano Di Penta,et al.  An approach to classify software maintenance requests , 2002, International Conference on Software Maintenance, 2002. Proceedings..

[2]  Tom DeMarco,et al.  Peopleware: Productive Projects and Teams , 1987 .

[3]  Chadd C. Williams,et al.  Bug Driven Bug Finders , 2004, MSR.

[4]  Gail C. Murphy,et al.  Recommending Emergent Teams , 2007, Fourth International Workshop on Mining Software Repositories (MSR'07:ICSE Workshops 2007).

[5]  Audris Mockus,et al.  Expertise Browser: a quantitative approach to identifying expertise , 2002, Proceedings of the 24th International Conference on Software Engineering. ICSE 2002.

[6]  Gail C. Murphy,et al.  Who should fix this bug? , 2006, ICSE.

[7]  Audris Mockus,et al.  International Workshop on Mining Software Repositories , 2004 .

[8]  Les Gasser,et al.  Bug Report Networks: Varieties, Strategies, and Impacts in a F/OSS Development Community , 2004, MSR.

[9]  G. Duclos New York 1987 , 2000 .

[10]  David W. McDonald,et al.  Evaluating expertise recommendations , 2001, GROUP.

[11]  James D. Herbsleb,et al.  Object-Oriented Analysis and Design in Software Project Teams , 1995, Hum. Comput. Interact..

[12]  Gerardo Canfora,et al.  How Software Repositories can Help in Resolving a New Change Request , 2005 .

[13]  Gail C. Murphy,et al.  Predicting source code changes by mining change history , 2004, IEEE Transactions on Software Engineering.

[14]  Robert DeLine,et al.  Information Needs in Collocated Software Development Teams , 2007, 29th International Conference on Software Engineering (ICSE'07).

[15]  Mark S. Ackerman,et al.  Expertise recommender: a flexible recommendation system and architecture , 2000, CSCW '00.

[16]  Dewayne E. Perry,et al.  People, organizations, and process improvement , 1994, IEEE Software.