Artículos de revistas
A domain independent readability metric for web service descriptions
Fecha
2017-02Registro en:
de Renzis, Alan Ismael; Garriga, Martín; Flores, Andrés Pablo; Cechich, Susana Alejandra; Mateos Diaz, Cristian Maximiliano; et al.; A domain independent readability metric for web service descriptions; Elsevier Science; Computer Standards & Interfaces; 50; 2-2017; 124-141
0920-5489
CONICET Digital
CONICET
Autor
de Renzis, Alan Ismael
Garriga, Martín
Flores, Andrés Pablo
Cechich, Susana Alejandra
Mateos Diaz, Cristian Maximiliano
Zunino Suarez, Alejandro Octavio
Resumen
Web Services are influencing most IT-based industries as the basic building block of business infrastructures. A Web Service has an interface described in a machine-processable format (specifically WSDL). Service providers expose their services by publishing the corresponding WSDL documents. Service consumers can learn about service capability and how to interact with the services. Service descriptions (WSDL documents) should be ideally understood easily by service stakeholders so that the process of consuming services is simplified. In this work we present a practical metric to quantify readability in WSDL documents – attending to their semantics by using WordNet as the underlying concept hierarchy. In addition, we propose a set of best practices to be used during the development of WSDL documents to improve their readability. To validate our proposals, we performed both qualitative and quantitative experiments. A controlled survey with a group of (human) service consumers showed that software engineers required less time and effort to analyze WSDL documents with higher readability values. Other experiment compares readability values of a dataset of real-life WSDL documents from the industry before and after modifying them to adhere to the readability best practices proposed in this paper. We detected a significant readability improvement for WSDL documents written according to the best practices. In another experiment, we applied existing readability metrics for natural language texts detecting their unsuitability to the Web Service context. Lastly, we analyzed the readability best practices identifying their useful applicability to the industry.