Software Evolution Information Driven Service Oriented Software Clustering
Service oriented software in business is often programmed using Java language. For purpose of making software evolvable and maintainable, the technology of software clustering is often used to make the software modularized. However, traditional software clustering methods have not considered the potential relation between software elements, which cannot be identified by using the static analysis method, so it can make the software not satisfy the principle of "high cohesion, low coupling" in the area of software engineering. For solving the problem, this paper proposes a method by introducing the software evolution information into the software clustering process, based on that we construct an extended software dependency model and use Agglomerative Hierarchical Clustering (AHC) algorithm to cluster software. Experiments on two open source project show that this method can improve the accuracy of software clustering and aid the maintainer refactoring business software.
2016 IEEE International Congress on Big Data (BigData Congress)