Software Evolution Management with Differential Facts

Abstract

Many techniques have been proposed to mine knowledge from software artefacts and solve software evolution management tasks. To promote effective reusing of those knowledge, we propose a unified format, differential facts, to represent software changes across versions as well as various relations within each version, such as call graphs. Based on queryable formats, differential facts can be manipulated to implement complex evolution management tasks. Since facts once extracted can be shared among different tasks, the reusability brings improvements to overall performance. We validate the technique and show its benefits of being efficient, flexible, and easy to implement, with several applications, including semantic history slicing, regression test selection, documentation error detection and client-specific usage patterns discovery.