Water Loop Software Testing: A Novel Approach for Test Case Generation

Abstract

The aim of the present study is to investigate a novel testing approach named Water Loop Software Testing (WLST), which may be used for the automatic generation of test cases, ultimately fostering the development of high-quality software products. An empirical study is meticulously performed, leveraging the concept of a token bucket algorithm for the precise generation of test cases designed to rigorously test software modules. The performance of the proposed technique is then rigorously compared with the established genetic approach of software testing, utilizing a comprehensive case study to ensure a fair and robust evaluation. The computed results, showcasing the efficacy of WLST, are meticulously depicted in the form of detailed tables. It is observed that the presented testing approach generates a substantial 100 test cases in just 0.2670 seconds, accompanied by an impressively low average memory usage of 24.01MB and an average CPU utilization of a mere 0.68%. This remarkable efficiency and resource optimization highlight the novelty of the software testing approach, suggesting that it may be readily adopted by software industries to significantly outperform traditional methods in the development of superior software products.