Hypermedia API Research Articles

Dynamic system models and their simulation in the Semantic Web

Modelling and Simulation (M&S) are core tools for designing, analysing and operating today’s industrial systems. They often also represent both a valuable asset and a significant investment. Typically, their use is constrained to a software environment intended to be used by engineers on a single computer. However, the knowledge relevant to a task involving modelling and simulation is in general distributed in nature, even across organizational boundaries, and may be large in volume. Therefore, it is desirable to increase the FAIRness (Findability, Accessibility, Interoperability, and Reuse) of M&S capabilities; to enable their use in loosely coupled systems of systems; and to support their composition and execution by intelligent software agents. In this contribution, the suitability of Semantic Web technologies to achieve these goals is investigated and an open-source proof of concept-implementation based on the Functional Mock-up Interface (FMI) standard is presented. Specifically, models, model instances, and simulation results are exposed through a hypermedia API and an implementation of the Pragmatic Proof Algorithm (PPA) is used to successfully demonstrate the API’s use by a generic software agent. The solution shows an increased degree of FAIRness and fully supports its use in loosely coupled systems. The FAIRness could be further improved by providing more “ rich” (meta)data.

Model-Driven Integration Testingof Hypermedia Systems

The proper design of Representational State Transfer (REST) APIs is not trivial because developers have to deal with a flood of recommendations and best practices, especially the proper application of the hypermedia constraint requires some decent experience. Furthermore, testing RESTful APIs is a missing topic within literature. Especially hypermedia testing is not mentioned at all. Manual hypermedia testing is time-consuming and hard to maintain. Testing a hypermedia API requires many test cases that have similar structure, especially when different user roles and error cases are considered. In order to tackle this problem, we proposed a Model-Driven Testing (MDT) approach for hypermedia systems using the metamodel within our existing Model Driven Software Development (MDSD) approach. This work discusses challenges and results of hypermedia testing for RESTful APIs using MDT techniques that were discovered within our research. MDT allows white-box testing, hence covering complete program structure and behavior of the generated application. By doing this, we are able to achieve a high automated test coverage. Moreover, any runtime behavior deviated from the metamodel reveals bugs within the generators.

Hypermedia Driven Application Programming Interface for Learning Object Management

The research purpose is to create a hypermedia driven API for learning object management. The research focuses on conception, design, implementation and evaluation of the learning object management hypermedia API. The hypermedia API was designed based on learning object models, hypermedia concepts, and related studies. Learning object model can be represented and manipulated as a hypermedia resource. It contains page resources with text and links to multimedia elements. The hypermedia API was designed using UML and represented in HTML5 because of its rich affordance. The implementation and evaluation phase were conducted by testing the API using three different client’s software to prove the concept of hypermedia as the engine of application state for managing learning objects. The results show that the hypermedia API for learning object management is accessible, consistent, and discoverable by heterogonous client applications.

The pragmatic proof: Hypermedia API composition and execution

AbstractMachine clients are increasingly making use of the Web to perform tasks. While Web services traditionally mimic remote procedure calling interfaces, a new generation of so-called hypermedia APIs works through hyperlinks and forms, in a way similar to how people browse the Web. This means that existing composition techniques, which determine a procedural plan upfront, are not sufficient to consume hypermedia APIs, which need to be navigated at runtime. Clients instead need a more dynamic plan that allows them to follow hyperlinks and use forms with a preset goal. Therefore, in this paper, we show how compositions of hypermedia APIs can be created by generic Semantic Web reasoners. This is achieved through the generation of a proof based on semantic descriptions of the APIs' functionality. To pragmatically verify the applicability of compositions, we introduce the notion of pre-execution and post-execution proofs. The runtime interaction between a client and a server is guided by proofs but driven by hypermedia, allowing the client to react to the application's actual state indicated by the server's response. We describe how to generate compositions from descriptions, discuss a computer-assisted process to generate descriptions, and verify reasoner performance on various composition tasks using a benchmark suite. The experimental results lead to the conclusion that proof-based consumption of hypermedia APIs is a feasible strategy at Web scale.