Extraction and Management of Rationale

Abstract

Software developers often have to make many design decisions. The underlying logic behind these decisions, also called design rationale, represents beneficial and valuable information. In the past, researchers have tried to automatically extract and exploit this information, however, prior techniques are only applicable to specific contexts and there is insufficient progress on an automated end-to-end rationale extraction and management system. In this research project, we propose to use Natural Language Processing (NLP) and Machine Learning (ML) techniques to create a system for the automated extraction, structuring and management of design rationale. This system would support and ensure the consistency and the coherence of the development process.