Nirikshan: mining bug report history for discovering process maps, inefficiencies and inconsistencies

Issue tracking systems such as Bugzilla, Mantis and JIRA are Process Aware Information Systems to support business process of issue (defect and feature enhancement) reporting and resolution. The process of issue reporting to resolution consists of several steps or activities performed by various roles (bug reporter, bug triager, bug fixer, developers, and quality assurance manager) within the software maintenance team. Project teams define a workflow or a business process (design time process model and guidelines) to streamline and structure the issue management activities. However, the runtime process (reality) may not conform to the design time model and can have imperfections or inefficiencies. We apply business process mining tools and techniques to analyze the event log data (bug report history) generated by an issue tracking system with the objective of discovering runtime process maps, inefficiencies and inconsistencies. We conduct a case-study on data extracted from Bugzilla issue tracking system of the popular open-source Firefox browser project. We present and implement a process mining framework, Nirikshan, consisting of various steps: data extraction, data transformation, process discovery, performance analysis and conformance checking. We conduct a series of process mining experiments to study self-loops, back-and-forth, issue reopen, unique traces, event frequency, activity frequency, bottlenecks and present an algorithm and metrics to compute the degree of conformance between the design time and the runtime process.