Aftab Hussain
University of Houston

Software Restructuring using Hierarchical Clustering

Aftab Hussain, Md. Saidur Rahman
Graph Drawing and Information Visualization Lab
Department of Computer Science and Engineering
Bangladesh University of Engineering and Technology
Supported by CodeCrafters International
2011 to 2013
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Ill-structured code is difficult to understand and thereby, costly to maintain and reuse. Software restructuring techniques based on hierarchical agglomerative clustering (HAC) algorithms have been widely used to restructure large modules with low cohesion into smaller modules with high cohesion, without changing the overall behaviour of the software. These techniques generate clustering trees, of modules, that are sliced at different cut-points to obtain desired restructurings.

Choosing appropriate cut-points has always been a difficult problem in clustering. Previous HAC techniques generate clustering trees that have large number of cut-points. Moreover, many of those cut-points return clusters of which only a few lead to a meaningful restructuring of the software.

In this work, we develop a new hierarchical clustering technique for restructuring software at the function level that improves refactoring visualization by at least 30% over 3 widely popular clustering algorithms, is 60% faster, and yields the same code quality improvements on Java functions extracted from real-life industrial programs.

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Paper
Thesis
CohesionOptimizer tool
Tool manual (from thesis)