Nirikshak: A Clustering Based Autonomous API Testing Framework
This addresses inefficiencies in software QA for developers, though it appears incremental as it builds on existing automated methods with a new clustering approach.
The paper tackles the problem of repetitive and resource-intensive REST API testing by introducing Nirikshak, a clustering-based autonomous framework that achieves level 2 autonomy, streamlining testing and improving adaptability to software updates.
Quality Assurance (QA) is a critical component in product development, particularly in software testing. Despite the evolution of automated methods, testing for REST APIs often involves repetitive tasks. A significant portion of resources is dedicated more to scripting tests than to detecting and resolving actual software bugs. Additionally, conventional testing methods frequently struggle to adapt to software updates. However, with advancements in data science, a new paradigm is emerging: a self-reliant testing framework. This innovative approach minimizes the need for user intervention, achieving level 2 of autonomy in executing REST API testing procedures. It does so by employing a clustering method and analysis on logs categorizing test cases efficiently and thereby streamlining the testing process as well as ensuring more dynamic adaptability to software changes. Nirikshak is publicly available as an open-source software for the community at https://github.com/yashmahalwal/nirikshak.