Test Cases Selection Based on Source Code Features Extraction
International Journal of Software Engineering and Its Applications
Extracting valuable information from source code automatically was the subject of many research papers. Such information can be used for document traceability, concept or feature extraction, etc. In this paper, we used an Information Retrieval (IR) technique: Latent Semantic Indexing (LSI) for the automatic extraction of source code concepts for the purpose of test cases' reduction. We used and updated the open source FLAT Eclipse add on to try several code stemming approaches. The goal is to
... eck the best approach to extract code concepts that can improve the process of test cases' selection or reduction. are proposed in this area (e.g., Briand et al.,  ). However, in the scope of this paper, coupling and cohesion metrics are used feature extraction and similarity evaluation. Similar to search in search engines, feature or concept extraction from source code can start from concepts or keywords defined by users as an input. Feature extraction tools are then used to map code elements that reflect or response to such input concepts or keywords. The rest of the paper is organized as the following: Section two presents a literature review for papers relevant to the subject of this paper. Section three presents methodology and approaches, section four presents experiments and analysis and the paper is concluded with conclusion section.