Impact of Software Bug Report Preprocessing and Vectorization on Bug Assignment Accuracy

Abstract

Bug handling processes aimed at efficient defect resolution provisioning is an important part of a software development lifecycle and usually has a very formal process definition in modern and professional large software development organizations. Improvements of such process may include automated bug assignment, which is a task of selecting a correct development team for further investigations of a bug report. As bug reports contain lots of natural language descriptions, the bug assignment becomes a non-trivial task, especially in testing of large-scale projects or complex systems. This research focuses on natural language preprocessing and vectorization impact on accuracy of bug report assignment based on real data captured in large software development projects. Experimentation results cover stemming and lemmatization techniques applied for bug description preprocessing and term frequency – inverse document frequency (TF-IDF) parametrization as vectorization method.