
Conventionally, callbacks and inversion of control have been the main tools to structure event-driven applications. Sadly, those patterns constitute a well-known source of design problems. The Reactive Programming (RP) paradigm has arisen as an approach to mitigate these problems. Yet, little evidence has been provided regarding the advantages of RP, and concerns have also arisen about the API usability of RP libraries given their disparate number of operators. In this work, we conduct a study on GitHub (GH) and Stack Overflow (SO) and explore three Reactive Extensions (Rx) libraries (RxJava, RxJS, and RxSwift) with the most GH projects to understand how much the vast Rx operators are being used. Also, we examine Rx SO posts to complement the results from the GH exploration by understanding the problems faced by RP developers and how they relate with the operators' frequencies found in open source projects. Results reveal that, in spite of its API size, the great majority of the Rx operators are actually being used (95.2%), with only a few, mostly related to RxJava, not being utilized. Also, we unveil 23 topics from SO with more posts concerning the Stream Abstraction (36.4%). Posts related to Dependency Management, Introductory Questions, and iOS Development figure as relevant topics to the community. The findings herein present can not only stimulate advancements in the field by understanding the usage of RP API and the main problems faced by developers, but also help newcomers in identifying the most important operators and the areas that are the most likely to be relevant for a RP application.
API Usability, Information Systems and Management, Taverne, Reactive Programming, Mining Software Repositories, Safety, Risk, Reliability and Quality, Software
API Usability, Information Systems and Management, Taverne, Reactive Programming, Mining Software Repositories, Safety, Risk, Reliability and Quality, Software
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 8 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
