An ontology based e-learning system using antipatterns

Antipatterns are mechanisms that describe how to arrive at a good (refactored) solution from a fallacious solution that has negative consequences. These mechanisms are used in a variety of computer science topics and although their integration in teaching and computer science curriculum has been proposed, the development of an e-learning system using antipatterns, still remains an open issue. Previous work has proposed the use of WebProtege, a Web-based environment that allows collaborative editing as well as annotation and voting of both components and changes of the antipattern ontology. This ontology has been implemented as the knowledge base of SPARSE, an intelligent system that uses semantic web tools and techniques in order to detect the antipatterns that exist in a software project. In this paper, we leverage this semantic web technology and the formalism of ontology in order to propose a peer-production based e-learning system for the electronically supported learning of antipatterns. We illustrate how this Web-based system can transfer antipattern knowledge using an e-learning scenario as an example.