Sub-graph Mining: Identifying Micro-architectures in Evolving Object-oriented Software. Belderrar, A., Kpodjedo, S., Gu�h�neuc, Y., Antoniol, G., & Galinier, P. In Kanellopoulos, Y. & Mens, T., editors, Proceedings of the 15<sup>th</sup> European Conference on Software Maintenance and Reengineering (CSMR), pages 171–180, March, 2011. IEEE CS Press. 10 pages.
Sub-graph Mining: Identifying Micro-architectures in Evolving Object-oriented Software [pdf]Paper  abstract   bibtex   
Developers introduce novel and undocumented micro-architectures when performing evolution tasks on object-oriented applications. We are interested in understanding whether those organizations of classes and relations can bear, much like cataloged design and anti-patterns, potential harm or benefit to an object-oriented application. We present SGFinder, a sub-graph mining approach and tool based on an efficient enumeration technique to identify recurring micro-architectures in object-oriented class diagrams. Once SGFinder has detected instances of micro-architectures, we exploit these instances to identify their desirable properties, such as stability, or unwanted properties, such as change or fault proneness. We perform a feasibility study of our approach by applying SGFinder on the reverse-engineered class diagrams of several releases of two Java applications: ArgoUML and Rhino. We characterize and highlight some of the most interesting micro-architectures, \eg the most change and fault prone, and conclude that SGFinder opens the way to further interesting studies.

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