Do RESTful API design rules have an impact on the understandability of Web APIs?

Justus Bogner, Sebastian Kotstein, Timo Pfaff

Research output: Contribution to JournalArticleAcademicpeer-review

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.
Original languageEnglish
Article number132
JournalEmpirical Software Engineering
Volume28
Issue number6
DOIs
Publication statusPublished - 1 Nov 2023
Externally publishedYes

Funding

We kindly thank all our experiment participants for their valuable time! We also thank the experts participating in our pilot for their detailed feedback! Lastly, we thank Dr. Daniel Graziotin (University of Stuttgart) and Dr. Sira Vegas (Universidad Politécnica de Madrid) for discussing the experiment design and its terminology with us.

FundersFunder number
Universidad Politécnica de Madrid
Universität Stuttgart

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