A Mixed-method Approach to Recommend Corrections and Correct REST Antipatterns Revision for Supplemental Material

Many companies, e.g., Facebook and YouTube, use the REST architecture and provide REST APIs to their clients. Likeany other software systems, REST APIs need maintenance and must evolve to improve and stay relevant. Antipatterns—poor designpractices—hinder this maintenance and evolution. Although the literature defines many antipatterns and proposes approaches for their(automatic) detection, theircorrectiondid not receive much attention. Therefore,we apply a mixed-method approach to study RESTAPIs and REST antipatterns with the objectives to recommend corrections or, when possible, actually correct the RESTantipatterns.Qualitatively, via case studies, we analyse the evolution of 11 REST APIs, including Facebook, Twitter, and YouTube,over six years. We detect occurrences of eight REST antipatterns in the years 2014, 2017, and 2020 in 17 versions of 11 REST APIs.Thus, we show that (1) REST APIs and antipatterns evolve over time and (2) developers seem to remove antipatterns. Qualitatively via a discourse analysis, we analyse developers’ forums and report that developers are concerned with the occurrences of REST antipatternsand discuss corrections to these antipatterns. Following these qualitative studies, using anengineering-research approach, we proposethe following novel and unique contributions: (1) we describe and compare the corrections of eight REST antipatterns from the academicliterature and from developers’ forums; (2) we devise and describe algorithms to recommend corrections to some of these antipatterns;(3) we present algorithms and a tool to correct some of these antipatterns by intercepting and modifying responses from REST APIs;and, (4) we validate the recommendations and the corrections manually and via a survey answered by 24 REST developers.Thus, wepropose to REST API developers and researchers the first, grounded approach to correct REST antipatterns