Mining traces between source code and textual documents. (2019)

• Record Type: Journal Article
• Authors: Rasekh, Amir Hossein; Fakhrahmad, Seyed Mostafa; Sadreddini, Mohammad Hadi
• Is Part Of: International journal of computer applications technology. Volume 59:Number 1(2019)
• Page Start: 43
• Page End: 52
• Publication Date: 2019
• Subjects: traceability -- data mining -- artefacts -- documentation -- source code -- similarity; Technology -- Data processing -- Periodicals; 620.00285
• Languages: English
• ISSNs: 0952-8091

Abstract

Currently, researchers in computer science are dealing with a major challenge to link the source codes with the software documents. Writing informal documents by using natural and unstructured language causes this problem. In this paper, we present a model for recovery of traceable links between the source code and requirement documents. The proposed method in this paper is executed in four interconnected sections. The first section goes through extracting the features from the documents, which is followed by extracting the features from the source code. During the third section, abbreviations will be completed, using similarity measure as a feature. Finally, data mining algorithms will be implemented to find the hidden links between source code and software documentation. The most outstanding advantage of using this method is to be independent from the language. Also the preliminary results show that the proposed method has a good performance.