Sena TLS-Parser: A Software Testing Tool for Generating Test Cases

Currently, software complexity and size has been steadily growing, while the variety of testing has also been increased as well. The quality of software testing must be improved to meet deadlines and reduce development testing costs. Testing software manually is time consuming, while automation save...

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Bibliographic Details
Main Authors: Ibrahim, R., AbuSalim, S.W.G., Jamel, S., Wahab, J.A.
Format: Article
Published: Science and Information Organization 2022
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85133385887&doi=10.14569%2fIJACSA.2022.0130649&partnerID=40&md5=914f14e5832d19f783bf6e6999815b7b
http://eprints.utp.edu.my/33394/
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Summary:Currently, software complexity and size has been steadily growing, while the variety of testing has also been increased as well. The quality of software testing must be improved to meet deadlines and reduce development testing costs. Testing software manually is time consuming, while automation saves time and money as well as increasing test coverage and accuracy. Over the last several years, many approaches to automate test case creation have been proposed. Model-based testing (MBT) is a test design technique that supports the automation of software testing processes by generating test artefacts based on a system model that represents the system under test's (SUT) behavioral aspects. The optimization technique for automatically generating test cases using Sena TLS-Parser is discussed in this paper. Sena TLS-Parser is developed as a Plug-in Tool to generate test cases automatically and reduce the time spent manually creating test cases. The process of generating test cases automatically by Sena TLS-Parser is be presented through several case studies. Experimental results on six publicly available java applications show that the proposed framework for Sena TLS-Parser outperforms other automated test case generation frameworks. Sena TLS-Parser has been shown to solve the problem of software testers manually creating test cases, while able to complete optimization in a shorter period of time. © 2022. International Journal of Advanced Computer Science and Applications. All Rights Reserved.