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DESIGN METHODS FOR DIAGNOSING AND LOCATING ENTANGLED TECHNICAL DEBT IN DEVOPS FRAMEWORKS

Published online by Cambridge University Press:  19 June 2023

Jose Bonet Faus ,
Pascal Le Masson ,
Ugo Pelissier ,
Nafissa Jibet ,
Antoine Bordas  and
Sebastien Pajot
Jose Bonet Faus*
Affiliation:
Mines de Paris;
Pascal Le Masson
Affiliation:
Mines de Paris;
Ugo Pelissier
Affiliation:
Mines de Paris;
Nafissa Jibet
Affiliation:
Mines de Paris;
Antoine Bordas
Affiliation:
Mines de Paris;
Sebastien Pajot
Affiliation:
Ubisoft
*
Bonet Faus, Jose, Ubisoft, France, [email protected]

Abstract

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In the IT landscape, DevOps is the preferred approach for developing and maintaining rapidly evolving systems that require continuous improvements. Yet, DevOps frameworks do not entirely prevent the accumulation of Technical Debt (TD), and under certain circumstances DevOps can even contribute to generating TD. This paper focuses on a specific type of TD, Entangled Technical Debt (ETD), that corresponds to the implicit complexification of a system's design and the appearance of unintentional couplings in its architecture over time. Our work seeks to inform methods for Diagnosing and Locating ETD in DevOps frameworks. Through a research partnership with Ubisoft's IT branch, an experimental case-study was conducted. It takes the form of an assessment of 6 innovative IT projects and a subsequent in-depth architecture analysis of an individual IT system, which enabled the characterization of the mechanisms linking DevOps to ETD. This allowed us to develop and test practical methods for diagnosing and locating ETD in IT systems.

Keywords

Technical DebtDevOpsDesign theorySystems Engineering (SE)Innovation
Type
Article
Information
Proceedings of the Design Society , Volume 3: ICED23 , July 2023 , pp. 1267 - 1276
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2023. Published by Cambridge University Press

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