Constrained agglomerative hierarchical software clustering with hard and soft constraints

Although agglomerative hierarchical software clustering technique has been widely used in reverse engineering to recover a high-level abstraction of the software in the case of limited resources, there is a lack of work in this research context to integrate the concept of pair-wise constraints, such as must-link and cannot-link constraints, to further improve the quality of clustering. Pair-wise constraints that are derived from experts or software developers, provide a means to indicate whether a pair of software components belongs to the same functional group. In this paper, a constrained agglomerative hierarchical clustering algorithm is proposed to maximize the fulfilment of must-link and cannot-link constraints in a unique manner. Two experiments using real-world software systems are performed to evaluate the effectiveness of the proposed algorithm. The result of evaluation shows that the proposed algorithm is capable of handling constraints to improve the quality of clustering, and ultimately provide a better understanding of the analyzed software system.