DRETOM: developer recommendation based on topic models for bug resolution
Proceedings of the 8th International Conference on Predictive Models in Software Engineering
A hybrid bug triage algorithm for developer recommendation
Proceedings of the 28th Annual ACM Symposium on Applied Computing
Bug report assignee recommendation using activity profiles
Proceedings of the 10th Working Conference on Mining Software Repositories
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This paper proposes a new approach called DREX (Developer Recommendation with k-nearest-neighbor search and Expertise ranking) to developer recommendation for bug resolution based on K-Nearest-Neighbor search with bug similarity and expertise ranking with various metrics, including simple frequency and social network metrics. We collect Mozilla Fire fox open bug repository as the experimental data set and compare different ranking metrics on the performance of recommending capable developers for bugs. Our experimental results demonstrate that, when recommending 10 developers for each one of the 250 testing bugs, DREX has produced better performance than traditional methods with multi-labeled text categorization. The best performance obtained by two metrics as Out-Degree and Frequency, is with recall as 0.6 on average. Moreover, other social network metrics such as Degree and Page Rank have produced comparable performance on developer recommendation as Frequency when used for developer expertise ranking.