Fuzzy Based Expert System For Test Case Generation On Web Graphical User Interface For Usability Test Improvement
DOI:
https://doi.org/10.61506/01.00419Keywords:
fuzzy based expert system, generation on web graphical, usability test improvementAbstract
The Ease of Use Test (UT) method is used to evaluate a website's or its point of interaction's usability without involving the site's actual users. UT can be carried out manually or with the use of a machine. Currently, a lot of software testers manually test their program, which leads to issues like lengthier test times, uneven testing, and the requirement for human intervention to complete every test. The ease of use test manual is an expensive and time-consuming process. Analyzers are additional resources needed for manual labor, and there is a great chance that these results will conflict. The goal of this investigation is to improve the reliability and skill of the Test Case (TC) age experiments; the test system is delivered using test instruments that have been programmed. The purpose of this examination's efficient writing audit was to identify any gaps in the current AT and create a mess in the TC era. The evaluation was also focused on identifying the primary issues raised by alternate neighborhood analysts throughout the physical creation of TC. According to the selected plausible experiments, TC was created using the fluffy rationale master structure. Non-probabilistic, vulnerability-related, and multi-esteemed reasoning can all be emphasized in fluffy reasoning. The purpose of the information inquiry was to obtain access to the login page and to create experiments about Graphic User Interface events using a lighthearted justification. The framework separated the conditions, traits, and watchwords from the information examination code, and the outcomes were displayed as experiments. A close examination of behavioral test system age processes was conducted using the master framework for evaluation based on fluff. The evaluation results obtained through quantifiable analysis demonstrated that the provided framework is significantly more productive and reliable for conducting experiments than the manual framework.
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