Improved bug localization technique using hybrid information retrieval model

Abstract

The need of bug localization tools and increased popularity of text based IR models to locate the source code files containing bugs is growing continuously. Time and cost required for fixing bugs can be considerably minimized by improving the techniques of reducing the search space from few thou‐ sand source code files to a few files. The main contribution of this paper is to propose a Hybrid model based on two existing IR models (VSM and N-gram) for bug localization. In the proposed hybrid model performance is further improved by using word based bigrams. We have also introduced a weighing factor beta β to calculate the weighted sum of unigram and bigram and analyzed its accuracy for values ranging from (0-1). Using TopN, MRR and MAP measures, we have conducted experiments which show that the proposed hybrid model outperforms some existing state-of-art bug localization techniques.