Information-Theoretic Remodularization of Object-Oriented Software Systems

Software remodularization consists in reorganizing software entities into modules such that pairs of entities belonging to the same modules are more similar than those belonging to different modules. In recent years, Search-Based Software Engineering (SBSE) approach has gained unprecedented growth for solving software remodularization problem. Most of the previous studies remodularize the software system by optimizing the structural coupling and cohesion metrics as objective functions. These metrics are defined in terms of the number of structural relationships counts, rather than taking patterns of relationships. It has been observed that the computation of coupling and cohesion based on patterns of relationships (i.e., information-theory based) are more accurate than the number of relationships. This paper proposes an information-theoretic software remodularization where an entropy-based similarity measure is introduced as an objective function along with other objective functions i.e., inter-module class change coupling, intra-module class change coupling, module size index (MSI), and module count index (MCI) and is further optimized using many-objective meta-heuristic algorithm. To evaluate the effectiveness of the proposed approach, seven object-oriented software systems have been remodularized using NSGA-III, MOEA/D, IBEA, and TAA algorithms. The results are compared with existing multi-objective formulation of remodularization problem in terms of authoritative software remodularization, non-extreme distribution, and stability. The experimentation results suggest that the proposed approach can be a good alternative to improve the quality of software systems. The findings suggest that the approach is more suitable for generating remodularization solution good from both quality metrics and developers perspective.