Knowledge Incorporation in Requirements Traceability Recovery

Abstract

The necessity of continuous change and adaptation in software systems makes maintenance tasks complex and difficult. One of the challenges in software maintenance is keeping requirements traceability up to date automatically. This problem can be considered as an optimization problem where the goal is to assign each requirement to one or many software artifacts (class, method, variable, etc.). However, some of the traceability links proposed using this approach do not necessarily make sense depending on the context and the semantic of the system under analysis. This paper proposes an approach that tackles this problem by adapting the Interactive Genetic Algorithm (IGA) which enables to interact with users and integrate their feedbacks into a classic GA. The proposed algorithm uses a fitness function that combines the recency of change, the frequency of change, and the semantic similarity between the description of the requirement and the software artifact, and the designers’ ratings of the traceability links proposed during execution of the classic GA. Experimentation with the approach yielded interesting and promising results.