Abstract
The number of Web APIs for accessing information and services is continuously increasing, and yet, no tools exist to automate the time-consuming and error-prone process of invoking those APIs and composing their responses. The recent emergence of widely-adopted, standardized, Web-API description formats and the development of Linked Data technologies for data integration have motivated our work on the LRA (Linked REST APIs) methodology [1, 2]. LRA relies on RDF service specifications to automate the development process around the usage of Web APIs. This automation represents a great opportunity to systematize and improve the quality of service-oriented application development. However, LRA’s reliance on SPARQL as the user-interaction model may hinder its adoption, because it requires developers to learn the intricacies of the unconventional graph data model and its associated datasets. In this paper we have developed the LRA Workbench (LRA_{Wbench}), which takes advantage of the emergent schema of Web-API specifications, in order to simplify the formulation of LRA-compliant SPARQL queries. Our empirical evaluation of the LRA_{Wbench} usability demonstrates that our tool significantly improves the performance of developers formulating SPARQL queries for LRA. A subsequent study on the effectiveness of the LRA_{Wbench} demonstrated that developers using LRA tend to produce code with considerable better structural complexity, in less time, than developers manually composing APIs.
Highlights
The evolution of the Web has led to an increased adoption of Web APIs1, revolutionizing the way end users and software systems access information and services
The results show that Visual Query Assistant (VQA) users took significantly less time overall and required fewer attempts to formulate the queries than YASGUI users (95% confidence)
The results show that all the structural complexity measures favor the Linked REST APIs (LRA) approach with statistical significance
Summary
The evolution of the Web has led to an increased adoption of Web APIs1, revolutionizing the way end users and software systems access information and services. Web APIs have enabled companies to increase their revenues, by discovering and joining forces with complementors. Application developers need to examine large amounts of natural-language documentation in order to understand how Serrano and Stroulia J Big Data (2021) 8:123 to write client code for specific APIs, compose compatible APIs, and manage authentication credentials. They have to do it all over again, when any of these APIs change. Even though data can, in principle, be accessed through Web APIs, in many cases it still remains captive in isolated silos that do not interoperate with other resources and services on the Web
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