Understanding language profile of open source software using association rule mining

The development of open source software has gained popularity. Most of the software projects use diverse sets of programming languages for development. In this work, the Knowledge Discovery in Data (KDD) approach to analyze the data of 30,518 open source projects hosted on SourceForge. The process of knowledge discovery is explored by using the association rule mining algorithm to find the programming languages, which are often used together in combination for the development of software project. The group-matrix based visualization technique is further implied to visualize the generated associated group of languages. The generated knowledge base and visualization of associated languages provide current and future developers with insight knowledge of multiple set of programming languages which are used together frequently for the development of open source software projects.