An Archetypal for Test Case Generation and Classification in Agile Using Orchestrated Raw Requirement Analysis

Abstract

The software testing phase involves rigorous assessment using specific test cases to ensure consistency, acceptability, and error detection. Automated testing emerges as a practical solution to expedite the traditionally time-consuming manual testing process, prioritizing swift feedback crucial for preventing potential delays in development. Software quality, as defined by meeting both stated and implied requirements, remains a paramount objective within the SDLC. newlineThe integration of AI and ML in software testing holds promise for reducing fatigue, enhancing efficiency, and bridging the gap between human and machine testing capabilities. Despite challenges, the application of AI and ML in testing processes is expected to contribute to business growth and meet the demands of shorter and more complex software life cycles. The application of machine learning in quality assurance and software testing is presented as a key factor in meeting rising consumer demands and ensuring efficient testing within tight timeframes. newlineThis work addresses the limitations of traditional methods in software engineering and advocates for the adoption of more advanced techniques, specifically AI and ML, in test case generation automation. This work aims to drive research and innovation in intelligent automated software test case generation, providing valuable insights for quality professionals navigating the dynamic landscape of software testing. newlineWhile traditional test automation has primarily focused on accelerating test execution, the need necessity lies in automating test generation and planning. Key areas are identified for generating test cases from requirements specification, particularly focusing on use case descriptions, and the improvement of accuracy and efficiency in the test case generation process.The proposed approach, rooted in user stories, demonstrates its efficacy in generating relevant test cases early in the development process, particularly aligning with Agile methodologies like Test-Driven Development (TDD).