Bug Tracking System to Reduce Duplicate Bug Reports Using Cost-Aware Algorithm

Abstract

Software engineers rely heavily on bug-tracking solutions to help direct their maintenance efforts. In certain projects, as many as quarters of all bug reports are duplicates, reducing the usefulness of these systems. Bugs are prioritized by cost-conscious algorithms according to their effect on consumers, possible business hazards, and resource availability. By doing this, the bug tracking system can concentrate on fixing high-priority problems first, reducing the effect on users and the software system. A cost-aware algorithm in a bug tracking system aims to maximize the problem resolution process via resource allocation, bug fix prioritization, and cost management of software issues. Manually identifying duplicate bug reports is a time-consuming and expensive procedure that adds to developers' workloads. To prevent developers from wasting time, suggest a system that may automatically sort incoming problem reports into distinct categories. This method makes use of graph clustering in addition to textual semantics and surface information to make duplication predictions. Simulate a real-time bug reporting environment and conduct experiments using a dataset of 29,000 bug reports from Mozilla projects. By eliminating 8% of duplicate bug reports while ensuring that developers get at least one report for each genuine fault, the solution can cut down on development costs significantly. A bug-tracking system is a piece of software that acts as a database for recording software defects and user recommendations. The result shows that the false positive rate is reduced to 1% by using the Cost Aware algorithm.