Automatic Bug Triage Using Execution Trace and Ownership Vector Space

Came up with this idea by smashing together two papers from Greg's reading list. Using this for my NSERC & OGS applications, so please don't steal it :)


Previously presented topics on automatic bug triage (directing bug reports to the appropriate member of the development team) showed very bright prospects, but lacked enough accuracy to make them a usable product [1]. This entry point for bug information is also an excellent location to apply any number of other filtering heuristics desired, such as the duplicate detection algorithm proposed by [2]. The method proposed in [2] requires, in addition to a natural language description of the problem, and execution trace that can be used to more quantitatively measure two, or more, bug's similarities. I propose that the same execution trace could be used to assist in the triage functionality described by [1]. Since the vector space created by Wang et. al. to measure bug similarity is based on function calls, a similar approach could be used, requiring the same input execution trace, to determine bug ownership. A master vector space could be created at build time from all possible called functions in a source code repository, and assigning ownership of these functions to developers based on either activity in a source revision system, or some static assignment. This would create volumes of ownership within the function vector space. In theory, a bug report, assuming it is not a duplicate, should be assigned to the developer in whose volume the bug's vector terminates. This may also have interesting and relevant applications to visualizing ownership of code, for management purposes.

[1] D. Cubranic and G. C. Murphy, "Automatic bug triage using text categorization," in Proceedings of the Sixteenth International Conference on Software Engineering & Knowledge Engineering, F. Maurer and G. Ruhe, Eds., June 2004, pp. 92-97. [Online]. Available: http://www.cs.ubc.ca/labs/spl/papers/2004/seke04-bugzilla.pdf

[2] X. Wang, L. Zhang, T. Xie, J. Anvik, and J. Sun, “An approach to detecting duplicate bug reports using natural language and execution information,” in Proceedings of the Thirtyth International conference on Software engineering