Bridging the gap between user stories and feature models by leveraging version control systems: A step towards software product line migration

Abstract

Context: Throughout the software lifecycle, a significant amount of knowledge is accumulated around the source code. In our work, we focus on agile software requirements, particularly user stories, and on issues and merge requests in version control systems, that have been opened for implementing user stories. Objective: The objective of this paper is to present a method that leverages this knowledge to guide an SPL migration. Methods: We consider merge requests in version control systems as the link between user stories (requirements) and the source code (implementation). The method combines Natural Language Processing (NLP) and clustering to identify features from user stories and hierarchically organize them. Relational Concept Analysis (RCA) is then used to compute logical rules from the hierarchy of features, using their links with the products and the source code. The logical rules are finally transformed into constraints in the produced feature model. Results: The method was implemented and evaluated on a dataset from an industrial partner. The results showed the efficiency of our method in synthesizing feature models for an SPL migration of the partner's code base. Conclusion: The proposed method synthesizes feature models to guide an SPL migration based on agile software development practices and demonstrates its effectiveness on a real industrial dataset.