RESTful APIs based on HTTP are one of the most important ways to make data and functionality available to applications and software services. However, the quality of the API design strongly impacts API understandability and usability, and many rules have been specified for this. While we have evidence for the effectiveness of many design rules, it is still difficult for nractitioners to identify rule violations in their design. We therefore present RESTRuler, a Java-based open-source tool that uses static analysis to detect design rule violations in OpenAPI descriptions. The current prototype supports 14 rules that go beyond simple syntactic checks and partly rely on natural language processing. The modular architecture also makes it easy to implement new rules. To evaluate RESTRuler, we conducted a benchmark with over 2,300 public OpenAPI descriptions and asked 7 API experts to construct 111 complicated rule violations. For robustness, RESTRuler successfully analyzed 99% of the used real-world OpenAPI definitions, with some failing due to excessive size. For performance efficiency, the tool performed well for the majority of files and could analyze 84% in less than 23 seconds with low CPU and RAM usage. Lastly, for effectiveness, RESTRuler achieved a precision of 91% (ranging from 60% to 100% per rule) and recall of 68% (ranging from 46% to 100%). Based on these variations between rule implementations, we identified several opportunities for improvements. While RESTRuler is still a research prototype, the evaluation suggests that the tool is quite robust to errors, resource-efficient for most APIs, and shows good precision and decent recall. Practitioners can use it to improve the quality of their API design.

Abstract Context Web APIs are one of the most used ways to expose application functionality on the Web, and their understandability is important for efficiently using the provided resources. While many API design rules exist, empirical evidence for the effectiveness of most rules is lacking. Objective We therefore wanted to study 1) the impact of RESTful API design rules on understandability, 2) if rule violations are also perceived as more difficult to understand, and 3) if demographic attributes like REST-related experience have an influence on this. Method We conducted a controlled Web-based experiment with 105 participants, from both industry and academia and with different levels of experience. Based on a hybrid between a crossover and a between-subjects design, we studied 12 design rules using API snippets in two complementary versions: one that adhered to a rule and one that was a violation of this rule. Participants answered comprehension questions and rated the perceived difficulty. Results For 11 of the 12 rules, we found that violation performed significantly worse than rule for the comprehension tasks. Regarding the subjective ratings, we found significant differences for 9 of the 12 rules, meaning that most violations were subjectively rated as more difficult to understand. Demographics played no role in the comprehension performance for violation. Conclusions Our results provide first empirical evidence for the importance of following design rules to improve the understandability of Web APIs, which is important for researchers, practitioners, and educators.