A Survey of the Software Test Methods and Identification of Critical Success Factors for Automation

• Published in: SN computer science Vol. 3; no. 6; p. 449
• Main Authors: Bindu Bhargavi, S. M., Suma, V.
• Format: Journal Article
• Language: English
• Published: Singapore Springer Nature Singapore 20.08.2022; Springer Nature B.V
• Subjects: Automation; Computer Imaging; Computer Science; Computer Systems Organization and Communication Networks; Data Structures and Information Theory; Effectiveness; Information Systems and Communication Service; Original Research; Pattern Recognition and Graphics; Predictive Artificial Intelligence for Cyber Security and Privacy; Product development; Software development; Software Engineering/Programming and Operating Systems; Software quality; Software testing; Usability; Vision; Regression testing; Test Automation; Tool Selection; Automation Strategy; Factor identification; Lights out mode
• ISSN: 2661-8907; 2662-995X; 2661-8907
• DOI: 10.1007/s42979-022-01297-5

Analytical studies based on software testing have shown that 50–80% of the total development cost is spent on testing the software for defects, adherence to functional and nonfunctional requirements. Software Testing enables the testers to discover the possible faults, bugs and errors existing in the software before being deployed in production, thereby verifying and validating the software over the requirements defined. Since manual testing is time consuming, less efficient and does not guarantee complete coverage, automation testing is recommended. Automation testing is performed with the main idea of improving the test coverage and increasing the test efficiency. The process of automation testing is facilitated by the use of automation tools which aid in increasing the speed of testing, but may need additional investments, in terms of revenue invested on tool, preparation of automation scripts, maintenance and training for better automation. Development of the software is associated with updates, changes/modifications being made over the course of time, resulting in testing the software in a repetitive manner which can be performed by regression testing. The proposed work analyzes different projects to determine and identify the significant factors influencing the effectiveness of testing for the sampled projects. The aim is to identify factors which influence the test effectiveness, have an impact on efficiency, and identify the appropriate test cases for automation. This research aims to study the relationship if any, among contributing factors and ultimately to explore the effectiveness of test automation.