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Cited by 320

The DOI matches its Crossref record; 91 of the 91 references it cites were found in a registry or an index.

Web Service Composition: A Survey of Techniques and Tools

Open access
Lemos, Angel Lagares, Daniel, Florian, Benatallah, Boualem·2016·ACM Computing Surveys

Abstract

Web services are a consolidated reality of the modern Web with tremendous, increasing impact on everyday computing tasks. They turned the Web into the largest, most accepted, and most vivid distributed computing platform ever. Yet, the use and integration of Web services into composite services or applications, which is a highly sensible and conceptually non-trivial task, is still not unleashing its full magnitude of power. A consolidated analysis framework that advances the fundamental understanding of Web service composition building blocks in terms of concepts, models, languages, productivity support techniques, and tools is required. This framework is necessary to enable effective exploration, understanding, assessing, comparing, and selecting service composition models, languages, techniques, platforms, and tools. This article establishes such a framework and reviews the state of the art in service composition from an unprecedented, holistic perspective.

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Metadata

Authors
Lemos, A. L., Daniel, F., & Benatallah, B.
Venue
ACM Computing Surveys
Published
2015-12-09
Volume
48
Issue
3
Pages
1-41
ISSN
  • 0360-0300 (ISSN-L)
  • 1557-7341
OpenAlex
W2192583762
Cited by
320
References
91
FWCI
96.40
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Web Service Composition: A Survey of Techniques and Tools. https://app.cochat.ai/papers/10.1145/2831270
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Lemos, A. L., Daniel, F., & Benatallah, B. (2016). Web Service Composition: A Survey of Techniques and Tools. ACM Computing Surveys. https://doi.org/10.1145/2831270

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.