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Please use this identifier to cite or link to this item: http://scholars.ntou.edu.tw/handle/123456789/18160
Title: Test-Oriented RESTful Service Discovery with Semantic Interface Compatibility
Authors: Ma, Shang-Pin 
Chen, Ying-Jen
Syu, Yang
Lin, Hsuan-Ju
Fanjiang, Yong-Yi
Keywords: Semantics;Quality of service;Web services;Search engines;Testing;Computer science;Oceans;Acceptance testing;interface compatibility;RESTful service;service discovery;term expansion;unit testing
Issue Date: 1-Sep-2021
Publisher: IEEE COMPUTER SOC
Journal Volume: 14
Journal Issue: 5
Start page/Pages: 1571-1584
Source: IEEE TRANSACTIONS ON SERVICES COMPUTING
Abstract: 
Web API/service technology has been attracting considerable attention and the REST (REpresentational State Transfer) architecture is now widely accepted as mainstream technology. Nonetheless, developing the means by which to discover RESTful Web APIs/services is crucial to the further development of this technology. Unfortunately, existing search engines for RESTful Web APIs/services provide only keyword-based or tag-based search functions. A failure to take into account the semantics and/or characteristics (e.g., their interface compatibility) greatly hampers the ability to find suitable APIs/services. In this study, we propose a novel approach to the discovery of RESTful Web API/services, referred to as Test-Oriented API Search with Semantic Interface Compatibility (TASSIC). This scheme involves expanding the terms of Web API/service documents based on DBpedia and WordNet. Unsuitable APIs/services are then filtered out using a systematic process, as follows: 1) calculation of semantic similarity between a set of candidate APIs/services and a user query, 2) analysis of interface compatibility between candidate APIs/services using the Hungarian Algorithm, 3) invocation of candidate APIs/services to verify functionality and availability, and 4) analysis of similarity between the actual response of the candidate services and the expected response specified in the user query. The proposed TASSIC increases the likelihood of matching APIs/services that are semantically equivalent or similar to user queries. Unit test and acceptance test are used to verify that a set of candidate APIs/services are actually available and that they actually meets user requirements. Experiment results demonstrate the efficacy of TASSIC, the accuracy of which is superior to that of existing methods.
URI: http://scholars.ntou.edu.tw/handle/123456789/18160
ISSN: 1939-1374
DOI: 10.1109/TSC.2018.2871133
Appears in Collections:資訊工程學系

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