RAPID: a knowledge-based assistant for designing web APIs

摘要

With the rise in initiatives such as software ecosystems and Internet of Things (IoT), developing web Application Programming Interfaces (web APIs) has become an increasingly common practice. One main concern in developing web APIs is that they expose back-end systems and data toward clients. This exposure threatens critical non-functional requirements, such as the security of back-end systems, the performance of provided services, and the privacy of communications with clients. Although dealing with non-functional requirements during software design has been long studied, there is still no framework to specifically assist software developers in addressing these requirements in web APIs. In this paper, we introduce Rational API Designer (RAPID), an open-source assistant that advises on designing non-functional requirements in the architecture of web APIs. We have equipped RAPID with a broad range of expert knowledge about API design, systematically collected and extracted from the literature. The API design knowledge has been encoded as a set of 156 rules using the Non-Functional Requirements (NFR) multi-valued logic, a formal framework commonly used to describe non-functional and functional requirements of software systems. RAPID uses the encoded knowledge in a stepwise inference procedure to arrive from a given requirement, to a set of design alternatives to a final recommendation for a given API design specification. Seven well-experienced software engineers have blindly evaluated the accuracy of RAPID's consultations over seven different cases of web API design and on providing design guidelines for thirty design questions. The results of the evaluation show that RAPID's recommendations meet acceptable standards of the majority of the evaluators 73.3% of the time. Moreover, analysis of the evaluators' comments suggests that more than one-third of the unacceptable ratings (33.8%) given to RAPID's answers are due to valid but incomplete design guidelines. We thus expect that the accuracy of the consultations will increase as RAPID's knowledge of API design is extended and refined.