preprint · 2018
Towards Executable Specifications for Microservices
José Ghislain Quenum, Samir Aknine
Cited by 7Abstract and details only
Abstract
This paper presents an empirical approach for microservice automated testing. With the rise of the agile methodology, automated testing has gained momentum in software development, including using microservices as an architectural style. However, the tests are not always related to the core specifications of the system being developed. In this paper, we discuss an approach to derive the tests, especially the acceptance tests, from the specifications of the systems. To avoid any ambiguity in the specifications, we focus on the formal specifications of the system. To this end, we introduce intelligent agents as a conceptual unit to encapsulate the formal specifications of services. Indeed, a comparison of microservice tenets and the general characterization of agents reveals that both can be thought of as autonomous software entities, driven by goals and evolving within a distributed environment and communicating with one another. Using a real-world application we show how agent formal specifications can be linked to microservice automated testing.
Cite this paper
Quenum, J. G., & Aknine, S. (2018). Towards Executable Specifications for Microservices. https://doi.org/10.1109/scc.2018.00013
Quenum, José Ghislain, and Samir Aknine. “Towards Executable Specifications for Microservices.” 2018, pp. 41–48, https://doi.org/10.1109/scc.2018.00013.
Quenum, José Ghislain, and Samir Aknine. 2018. “Towards Executable Specifications for Microservices.” https://doi.org/10.1109/scc.2018.00013.
Quenum, J.G. and Aknine, S. (2018) ‘Towards Executable Specifications for Microservices’. Available at: https://doi.org/10.1109/scc.2018.00013.
@misc{quenum2018towards,
title = {{Towards Executable Specifications for Microservices}},
author = {Quenum, José Ghislain and Aknine, Samir},
pages = {41--48},
year = {2018},
doi = {10.1109/scc.2018.00013}
}Made from the index record. Check names, capitalisation and page numbers against the paper. Need another style? AI for Research has over 10,000.