A Heuristic Approach for Resolving the Class Responsibility Assignment Case

This paper describes one of the solutions for the ninth Transformation Tool Contest (TTC ’16), which resolves the Class Responsibility Assignment Case using a transformation tool based on Microsoft Excel and Visual Basic. In this project, these relatively unusual technologies are used to effectively enhance the processing of large models and matrices throughout different test cases proposed for the competition. Given a Responsibility Dependency Graph, the solution analyzes the relationships among the given features and produces a class diagram that aims to get the highest possible cohesion and lowest possible coupling. The solution is based on an adaptation of the Markov Clustering Algorithm used to manage bi-directional, un-weighted sets of nodes and grouping them into clusters. The aim of this work is to take one step further in the graph/model optimization field through the treatment of matrices, a strategy that is not so widely used.