KSAP: An approach to bug report assignment using KNN search and heterogeneous proximity

Context: Bug report assignment, namely, to assign new bug reports to developers for timely and effective bug resolution, is crucial for software quality assurance. However, with the increasing size of software system, it is difficult to assign bugs to appropriate developers for bug managers. Objective: This paper propose an approach, called KSAP (K-nearest-neighbor search and heterogeneous proximity), to improve automatic bug report assignment by using historical bug reports and heterogeneous network of bug repository. Method: When a new bug report was submitted to the bug repository, KSAP assigns developers for the bug report by using a two-phase procedure. The first phase is to search historically-resolved similar bug reports to the new bug report by K-nearest-neighbor (KNN) method. The second phase is to rank the developers who contributed to those similar bug reports by heterogeneous proximity. Results: We collected bug repositories of Mozilla, Eclipse, Apache Ant and Apache Tomcat6 projects to investigate the performance of the proposed KSAP approach. Experimental results demonstrate that KSAP can improve the recall of bug report assignment between 7.5–32.25% in comparison with the state of art techniques. When there is only a small number of developer collaborations on common bug reports, KSAP has shown its excellence over other sate of art techniques. When we tune the parameters of the number of historically-resolved similar bug reports (K) and the number of developers (Q) for recommendation, KSAP keeps its superiority steadily. Conclusion: This is the first paper to demonstrate how to automatically build heterogeneous network of a bug repository and extract meta-paths of developer collaborations from the heterogeneous network for bug