Software Process Intelligence (SPI) is an emerging and evolving discipline involving mining and analysis of software processes. This is modeled on the lines of Business Process Intelligence (BPI), but with the focus on software processes and its applicability in software systems. Process mining consists of mining event log and process trace data for the purpose of process discovery (run-time process model), process verification or compliance checking (comparison between design-time and run-time process model), process enhancement and recommendation. Software Process Mining or Intelligence is a new and emerging discipline which falls at the intersection of Software Process & Mining, and Software & Process Mining. Software Process Mining is integral to discovering and verifying the processes in a software system.
Software Process Mining is a three word phrase which can be viewed from two perspectives: Software + Process Mining and Software Process + Mining. Software development and evolution involves usage of several workflow management and information systems and tools such as Issue Tracking Systems (ITS), Version Control Systems (VCS), Peer Code Review Systems (PCR) and Continuous Integration Tools (CIT). Such information systems log data consisting of events, activities, time-stamp, user or actor and context specific data. Such events or trace data generated by information systems used during software construction (as part of the software development process) contains valuable information which can be mined for gaining useful insights and actionable information. In this paper, we present Kashvi: A Framework for Software Process Intelligence
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