PERCEPTIONS ON RESTFUL APIs TESTING AND EVALUATION FOR DIGITIAL AI DEPLOYED APPLICATIONS- A LITERATURE REVIEW AND SYSTEMATIC SURVEY

Abstract

Web based Application Programming Interface(Web-API) grants a programmatic interfaces to a software developed. In recent times, Web-APIs perform a crucial position in accessing the publically available GPTs for the AI(Artificial Intelligence) based deployment in their customized applications like chatbots and information guidance system(IGS). By connecting the first rate GPTs and its resources, software architects can increases their product potential and create the impact on people’s life. But, a bug in this APIs could smack the complete product both intrinsically(services depends on Web-APIs) and extrinsically(third-party applications and users). Hence the evaluating the usability of Web-APIs specifically REST APIs have seen the exponential increase in research. These evaluation tests can recognize the issue area and offers the suggestions for enhancing the Web-APIs suitable for AI based product development. In this systematic surveys, 24 research studies were investigated to categorize the evaluation tests of Web-APIs specifically suitable for AI based deployment. Furthermore, implementation difficulties, existing limitations and other challenges are analysed this review article. This literature review will show the brighter path for both scholars and professionals in the industry are intrigued in deploying and evaluating these Web-APIs for AI applications.