OASIcs.SLATE.2019.23.pdf
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SeCoGen - A Service Code Generator
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8th Symposium on Languages, Applications and Technologies (SLATE 2019)
Series: Open Access Series in Informatics (OASIcs)
Conference: Symposium on Languages, Applications and Technologies (SLATE) - License:
Creative Commons Attribution 3.0 Unported license
- Publication Date: 2019-07-24
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Ricardo Queirós. SeCoGen - A Service Code Generator. In 8th Symposium on Languages, Applications and Technologies (SLATE 2019). Open Access Series in Informatics (OASIcs), Volume 74, pp. 23:1-23:8, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)
https://doi.org/10.4230/OASIcs.SLATE.2019.23
https://doi.org/10.4230/OASIcs.SLATE.2019.23
Abstract
The architectural pattern of micro-services is being increasingly adopted by developers, facilitating the maintenance and scalability of the systems' code. The adoption and consumption of these micro-services are often seen on the front-end code of the Web applications. Nevertheless, this adoption obliges web designers/developers to know where to look for those web services, to read their documentation and to write the request/response code as well to control the corresponding UI rendering. This whole process is time-consuming and error-prone. This article introduces SeCoGen as an interactive code generator for Web service parsing and consumption. The generator benefits from an HTTP request template, a query normalizer and dynamic UI templates. In order, to validate the generator feasibility and usefulness, a REST API to search for countries is used.
Subject Classification
ACM Subject Classification
- Software and its engineering → Source code generation
Keywords
- Code Generation
- Web services
- micro-services
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References
- P. D. Francesco. Architecting Microservices. In 2017 IEEE International Conference on Software Architecture Workshops (ICSAW), pages 224-229, April 2017. URL: https://doi.org/10.1109/ICSAW.2017.65.
- Robert Miller and Max Goldman. Software Construction. https://ocw.mit.edu/ans7870/6/6.005/s16/classes/18-parser-generators/#reading_18_parser_generators , 2016. Spring 2016. Massachusetts Institute of Technology: MIT OpenCourseWare.
- Ricardo Queirós. PROud - A Gamification Framework Based on Programming Exercises Usage Data. Information, 10(2), 2019. URL: https://doi.org/10.3390/info10020054.
- Gabriele Tomassetti. A Guide to Code Generation. https://tomassetti.me/code-generation/, 2018. Accessed: 2018-11-01.
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Seung-Su Yang, Hyung-Joon Kim, Nam-Uk Lee, and Seok-Cheon Park. Design of Automatic Source Code Generation Based on User Pattern Definition. In James J. Park, Vincenzo Loia, Gangman Yi, and Yunsick Sung, editors, Advances in Computer Science and Ubiquitous Computing, pages 1434-1439, Singapore, 2018. Springer Singapore.
