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Quality Assessment in DevOps: Automated Analysis of a Tax Fraud Detection System
University of Zaragoza, Spain.ORCID-id: 0000-0002-2736-845x
Netfective Technology, France.
University of Zaragoza, Spain.
2017 (engelsk)Inngår i: Proceedings of the 8th ACM/SPEC on International Conference on Performance Engineering Companion, New York, USA: ACM Press, 2017, s. 133-138Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

The paper presents an industrial application of a DevOps process for a Tax fraud detection system. In particular, we report the influence of the quality assessment during development iterations, with special focus on the fulfillment of performance requirements. We investigated how to guarantee quality requirements in a process iteration while new functionalities are added. The experience has been carried out by practitioners and academics in the context of a project for improving quality of data intensive applications.

sted, utgiver, år, opplag, sider
New York, USA: ACM Press, 2017. s. 133-138
Emneord [en]
DevOps, Model-based QoS, Tax Fraud detection, Data Intensive Applications, Unified Modeling Language
HSV kategori
Forskningsprogram
Datavetenskap, Programvaruteknik
Identifikatorer
URN: urn:nbn:se:lnu:diva-74484DOI: 10.1145/3053600.3053632ISBN: 978-1-4503-4899-7 (digital)OAI: oai:DiVA.org:lnu-74484DiVA, id: diva2:1209364
Konferanse
3rd International Workshop on Quality-Aware DevOps, L'Aquila, Italy, April 22 - 26, 2017
Prosjekter
H2020 DICE
Forskningsfinansiär
EU, Horizon 2020, 644869Tilgjengelig fra: 2018-05-22 Laget: 2018-05-22 Sist oppdatert: 2018-05-23bibliografisk kontrollert

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Forlagets fullteksthttps://dl.acm.org/citation.cfm?doid=3053600.3053632

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Perez-Palacin, Diego

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