Improving software maintenance with improved bug triaging

Bug triaging is a critical and time-consuming activity of software maintenance. This paper aims to present an automated heuristic approach combined with fuzzy multi-criteria decision-making for bug triag-ing. To date, studies lack consideration of multi-criteria inputs to gather decisive and explicit knowledge of bug reports. The proposed approach builds a bug priority queue using the multi-criteria fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method and combines it with Bacterial Foraging Optimization Algorithm (BFOA) and Bar Systems (BAR) optimization to select develop-ers. A relative threshold value is computed and categorization of developers is performed using hybrid optimization techniques to make a distinction between active, inactive, or new developers for bug allo-cation. The harmonic mean of precision, recall, f-measure, and accuracy obtained is 92.05%, 89.21%, 85.09%, and 93.11% respectively. This indicates increased overall accuracy of 90%+/- 2% when compared with existing approaches. Overall, it is a novel solution to improve the bug assignment process which uti-lizes intuitive judgment of triagers using fuzzy multi-criteria decision making and is capable of making a distinction between active, inactive, and new developers based on their relative workload categorization. (c) 2021 The Authors. Published by Elsevier B.V. on behalf of King Saud University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).