Towards a knowledge warehouse and expert system for the automation of SDLC tasks

Abstract

Cost of a skilled and competent software developer is high, and it is desirable to minimize dependency on such costly human resources. One of the ways to minimize such costs is via automation of various software development tasks. Recent advances in Artificial Intelligence (AI) and the availability of a large volume of knowledge bearing data at various software development related venues present a ripe opportunity for building tools that can automate software development tasks. For instance, there is significant latent knowledge present in raw or unstructured data associated with items such as source files, code commit logs, defect reports, comments, and so on, available in the Open Source Software (OSS) repositories. We aim to leverage such knowledge-bearing data, the latest advances in AI and hardware to create knowledge warehouses and expert systems for the software development domain. Such tools can help in building applications for performing various software development tasks such as defect prediction, effort estimation, code review, etc