Bugs Prioritization in Software Engineering : A Systematic Literature Review on Techniques and Methods

Abstract: Today’s world is a network of interconnected systems that are always running to facilitate information exchange so people can carry out their daily activities. Software applications are constantly evolving to meet the increasing expectations of the growing market, thereby giving rise to the development of large complex systems. It is very likely for these complex systems to encounter bugs which is a situation that can cause errors in software. These bugs can prevent the systems from operating as intended, slowing down software development and deployment, and causing delays in deadlines. This study undertook a systematic literature review to find trends in the field of bug prioritization. Software bug prioritization can help developers determine the order of fixing bugs by assigning priority levels based on the severity analysis. This study aims to identify the most promising techniques that can change the bug prediction and resolution process. It is observed that machine learning techniques (ML) have been gaining popularity in addressing the bug prioritization issue since they can automatically assign priority levels. However, these ML techniques also have limitations addressed in this study along with a taxonomic classification of identified techniques. The review obtained 34 manuscripts based on study selection criteria. These manuscripts discovered 63 unique bug prioritization techniques, including a mix of ML, data reduction and hybrid techniques. It is evident that though these techniques perform automatic prioritization, they can sometimes be slow and lack consistency in the accuracy of results.