Nirikshan: process mining software repositories to identify inefficiencies, imperfections, and enhance existing process capabilities

Abstract

Process mining is to extract knowledge about business processes from data stored implicitly in ad-hoc way or explicitly by information systems. The aim is to discover runtime process, analyze performance and perform conformance verification, using process mining tools like ProM and Disco, for single software repository and processes spanning across multiple repositories. Application of process mining to software repositories has recently gained interest due to availability of vast data generated during software development and maintenance. Process data are embodied in repositories which can be used for analysis to improve the efficiency and capability of process, however, involves a lot of challenges which have not been addressed so far. Project team defines workflow, design process and policies for tasks like issue tracking (defect or feature enhancement), peer code review (review the submitted patch to avoid defects before they are injected) etc. to streamline and structure the activities. The reality may not be the same as defined because of imperfections so the extent of non-conformance needs to be measured. We propose a research framework `Nirikshan' to process mine the data of software repositories from multiple perspectives like process, organizational, data and time. We apply process mining on software repositories to derive runtime process map, identify and remove inefficiencies and imperfections, extend the capabilities of existing software engineering tools to make them more process aware, and understand interaction pattern between various contributors to improve the efficiency of project.

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