Abstract

In the continually evolving domain of software development, guaranteeing the dependability and functionality of Application Programming Interfaces (APIs) is of utmost importance. Traditional approaches to API testing frequently encounter difficulties in keeping up with the dynamic nature of APIs, resulting in inefficiencies and overlooked defects. This research paper investigates the transformative potential of Artificial Intelligence (AI) in API testing, ushering in a new era of intelligent testing. Intelligent API testing harnesses the capabilities of AI to enhance the efficiency, precision, and adaptability of the testing process. API driven techniques enable the production of diverse and realistic test data, ensuring comprehensive test coverage. Furthermore, AI-powered algorithms can anticipate potential issues, identify anomalies, and optimize test case selection, all while adapting to evolving API schemas. This research paper delves into the various aspects of intelligent API testing, encompassing data generation, tools and technologies, benefits and impact, challenges, and real-world use cases. We illustrate how AI empowers testers to discover subtle defects, streamline testing endeavors, and enhance the overall quality of APIdriven applications. As we navigate the era of digital transformation, intelligent API testing emerges as an essential tool in the software development toolkit, enabling organizations to deliver robust and resilient APIs that fulfill the demands of contemporary applications. Embracing AI in API testing not only holds the promise of expediting the development lifecycle but also ensures that APIs remain agile and reliable in an ever-changing digital landscape.

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