Defining coupling metrics among classes in an OWL ontology
IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part II
Towards a classification of logical dependencies origins: a case study
Proceedings of the 12th International Workshop on Principles of Software Evolution and the 7th annual ERCIM Workshop on Software Evolution
Information and Software Technology
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In large scale software projects, developers make much software during long term. The source codes of software are frequently revised in the projects. The source codes evolve to become complex. Measurements of software complexity have been proposed, such as module coupling and logical coupling. In the case of the module coupling, even if developers copy pieces of source codes to a new module, the module coupling can not detect relationship between the pieces of the source codes although the pieces of the two modules have strong coupling. On the other hand, in the logical coupling, if two modules are accidentally revised at same time by a same developer, the logical coupling will judge strong coupling between the two modules although the modules have no relation. Therefore, we proposed a visualization technique and software complexity metrics for software evolution. A basic idea is that modules including strong module coupling should have strong logical coupling. If a gap between a set of modules including strong module couplings and a set of modules including strong logical couplings is large, the software complexity will be large. In addition, our visualization technique helps developers understand changes of software complexity. As a result of experiments in open source projects, we confirmed that the proposed metrics and visualization technique were able to detect high risky project with many bugs.