A Quality Model and Its Quantitative Evaluation Method for Web APIs

As Representational State Transfer (REST)-based Web APIs are spreading to enterprise information systems, software development for the use and provision of Web APIs is rapidly increasing. The quality of the Web APIs significantly influences the application quality and development productivity. However, no quality model for Web APIs has been established yet, because Web APIs differ from conventional APIs in that they execute remotely on different servers and may be changed independently of their users. These unique characteristics introduce new problems in the software engineering of Web APIs, and impose risks to the users, especially those using enterprise Web APIs, whose numbers are increasing. To solve these problems, in this paper, we propose a quality model for Web APIs that reflects their unique characteristics. As the main characteristics of this quality model, we propose the concept of Web API learnability to use and stability to change, from the perspective of Web API users. Based on this quality model, we also propose a set of measures and a quantitative evaluation method. In this study, we applied the proposed quality model and evaluation method to four types of actual Web APIs, including Uber, WordPress, OpenStack, and Media Processing. To validate the proposed model, we also conducted an empirical study of the usability of the Web APIs. Our comparison of the proposed quality statistics with those from the empirical study validates the effectiveness of the proposed quality model and its associated measures of the learnability and stability of Web APIs.