Publication

Abstract : Automatic functional tests are a long-standing issue in software development projects, and they are still carried out manually. The Selenium testing framework has gained popularity as an active community and standard environment for automated assessment of web applications. As a result, the trend setting of web services is evolving on a daily basis, and there is a need to improve automatic testing. The study involves to make the system to understand the experiences of previous test cases and apply new cases to predict the status of test case using Tanh activated Clustering and Classification model (TACC). The primary goal is to improve the model's clustering and classification output. The outcomes show that the TACC model has increased performance and demonstrated that automated testing results can be predicted, which is cost effective and reduces manual effort to a greater extent.