Traceability mining between unit test and source code based on textual analysis applied to software systems. (24th June 2020)

• Record Type: Journal Article
• Authors: Arshia, Amir Hossein; Rasekh, Amir Hossein; Moosavi, Mohammad Reza; Fakhrahmad, Seyed Mostafa; Sadreddini, Mohammad Hadi
• Is Part Of: Digital scholarship in the humanties. Volume 36:Number 2(2021)
• Page Start: 268
• Page End: 285
• Publication Date: 2020-06-24
• Subjects: Philology -- Data processing -- Periodicals; Computational linguistics -- Periodicals; 410.285
• DOI: 10.1093/llc/fqaa017
• Languages: English
• ISSNs: 2055-768X

Abstract

Abstract: Correctness of the designed system is one of the most important issues in the software development process. Therefore, various tests have been defined and designed to help software teams develop software with little or no problem. Finding a proper link between test class and the class under the test is an important but difficult task. Finding this relation helps the developers to conduct regression tests more efficiently. In this paper, we seek to propose a model for recovering traceable links between test classes and the classes under the test. The proposed method encompasses three parts: (1) method for extracting keywords and the measure of similarity of a specific part of code, (2) backward chain method based on a rule-based system, (3) using hybrid model to find traceable links between test classes and the code under test. This study uses three open-source and one industrial source projects to conduct experiments. The results are satisfactory compared to previous studies.