TY  - JOUR
A1  - Boukhlif, Mohamed
A1  - Hanine, Mohamed
A1  - Kharmoum, Nassim
A1  - Ruigómez Noriega, Atenea
A1  - García Obeso, David
A1  - Ashraf, Imran
AV  - public
UR  - http://doi.org/10.1109/ACCESS.2024.3407753
Y1  - 2024/05//
N2  - New approaches to software testing are required due to the rising complexity of today?s software applications and the rapid growth of software engineering practices. Among these methods, one that has shown promise is the introduction of Natural Language Processing (NLP) tools to software testing practices. NLP has witnessed a rise in popularity within all IT fields, especially in software engineering, where its use has improved the way we extract information from textual data. The goal of this systematic literature review (SLR) is to provide an in-depth analysis of the present body of the literature on the expanding subject of NLP-based software testing. Through a repeatable process, that takes into account the quality of the research, we examined 24 papers extracted from Web of Science and Scopus databases to extract insights about the usage of NLP techniques in the field of software testing. Requirements analysis and test case generation popped up as the most hot topics in the field. We also explored NLP techniques, software testing types, machine/deep learning algorithms, and NLP tools and frameworks used in the studied body of literature. This study also stressed some recurrent open challenges that need further work in future research such as the generalization of the NLP algorithm across domains and languages and the ambiguity in the natural language requirements. Software testing professionals and researchers can get important insights from the findings of this SLR, which will help them comprehend the advantages and challenges of using NLP in software testing.
ID  - unic14279
SP  - 79383
VL  - 12
EP  - 79400
TI  - Natural Language Processing-Based Software Testing: A Systematic Literature Review
JF  - IEEE Access
SN  - 2169-3536
KW  - Software testing
KW  -  natural language processing (NLP)
KW  -  systematic review
KW  -  test case generation
ER  -