Prioritization of DevOps Maturity models using Fuzzy TOPSIS

Proceedings of the 27th International Conference on Evaluation and Assessment in Software Engineering Pub Date : 2023-06-14 DOI:10.1145/3593434.3594241

Ankur Kumar, M. Nadeem, Mohammad Shameem

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引用次数: 1

Abstract

DevOps has become an increasingly popular approach to software development and operations. DevOps has evolved rapidly in recent years, with numerous maturity models being proposed to help organizations assess their level of adoption and identify improvement areas. However, there is no consensus on which model is the most effective, as different models may be more suited to different organizational contexts. This paper compares six popular DevOps maturity models using the Fuzzy TOPSIS Multiple Criteria Decision Making (MCDM) methods. Fuzzy TOPSIS is a popular MCDM technique that can handle imprecise and uncertain information. We analyze each model based on seven criteria: Culture, Automation, Continuous Integration/Continuous Delivery, Monitoring and Feedback, Security, Metrics and Measurement, and Continuous Learning and Improvement, and determine which model is the most suitable according to industry standards. The analysis revealed that Radstaak's DevOps maturity model outperforms the others when evaluated through seven standard criteria for assessing maturity models.

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使用模糊TOPSIS确定DevOps成熟度模型的优先级

DevOps已经成为一种越来越流行的软件开发和操作方法。DevOps近年来发展迅速，提出了许多成熟度模型来帮助组织评估其采用水平并确定改进领域。然而，对于哪种模型最有效并没有达成共识，因为不同的模型可能更适合不同的组织环境。本文使用模糊TOPSIS多准则决策(MCDM)方法比较了六种流行的DevOps成熟度模型。模糊TOPSIS是一种流行的MCDM技术，可以处理不精确和不确定的信息。我们根据文化、自动化、持续集成/持续交付、监控和反馈、安全、度量和测量、持续学习和改进等七个标准分析每个模型，并根据行业标准确定最适合的模型。分析显示，当通过评估成熟度模型的七个标准标准进行评估时，Radstaak的DevOps成熟度模型优于其他模型。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Proceedings of the 27th International Conference on Evaluation and Assessment in Software Engineering

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