Conflict Detection of Functional Requirements Based on Clustering and Rule-Based System

Functional requirement identification is the initial stage in software development and a crucial step in the success of software development. Good functional requirements sentences should be consistent with each other or conflict-free. There are already ways used to detect conflicting functional requirements. One of the methods, the Rule-based System (RBS), can pair conflicting functional requirements sentences but needs 1.6s for computing time for checking conflict or conflict-free requirements and 0.52 of accuration value. This study proposed a combination of the Clustering method and Rule-Based System to reduce computing time and increase accuracy in detecting conflict requirements. The evaluation used four public datasets containing 435 sentences and two private datasets containing 420 sentences. The proposed method reduces 97% computing time for a combination of K-Means and RBS. The proposed method can increase the 23% accuracy score for a combination of Agglomerative and RBS and Mean-Shift and RBS. The evaluation verified the proposed method to reduce computing time and increase accuracy for detecting conflict functional requirements.