
Abstract Context: DevOps responds to the growing need of companies to streamline the software development process and, thus, have experienced a widespread adoption in the past few years. However, successful adoption of DevOps requires companies to address important cultural and organizational changes. Understanding the organizational structure and characteristics of teams adopting DevOps is key, and comprehending the existing theories and representations of team taxonomies is critical to guide companies in a more systematic and structured DevOps adoption process. Objective: This paper presents empirical research on the structure of DevOps teams in software-producing organizations. The goal is to better understand the organizational structure and characteristics of teams adopting DevOps by harmonizing the existing knowledge. Method: To do this, we conducted a grounded theory study, analyzing existing studies on DevOps teams and taxonomies. Results: From the analysis, we built a substantive and analytic theory of DevOps taxonomies. The theory is substantive in that the scope of validity refers to the ten primary studies processed and analytic in that it analyzes “what is” rather than explaining causality or attempting predictive generalizations. A public repository with all the data related to the products resulting from the analysis and generation of the theory is available. Conclusions: We built a theory on DevOps taxonomies and tested whether it harmonizes the existing taxonomies, i.e., whether our theory can instantiate the others. This is the first step to define which taxonomies are best suited to approach DevOps culture and practices according to the companies’ objectives and capabilities.
FOS: Computer and information sciences, Development theory, Inter-coder agreement, Economics, inter-coder agreement, Knowledge management, Empirical research, Epistemology, Agile Software Development in Software Engineering, Grounded theory, Data science, Engineering, Sociology, Qualitative research, Market economy, Interrater Reliability, Scope (computer science), Informática, DevOps, Source Code Analysis, Social science, Computer science, Computer Science Applications, Process (computing), Management science, FOS: Sociology, FOS: Philosophy, ethics and religion, Programming language, Philosophy, Operating system, DevOps taxonomies, Grounded Theory, Computer Science, Physical Sciences, Innovation and Collaboration in Open Source Community, DevOps team structures, Process management, Software, grounded theory, Information Systems, Empirical Studies in Software Engineering
FOS: Computer and information sciences, Development theory, Inter-coder agreement, Economics, inter-coder agreement, Knowledge management, Empirical research, Epistemology, Agile Software Development in Software Engineering, Grounded theory, Data science, Engineering, Sociology, Qualitative research, Market economy, Interrater Reliability, Scope (computer science), Informática, DevOps, Source Code Analysis, Social science, Computer science, Computer Science Applications, Process (computing), Management science, FOS: Sociology, FOS: Philosophy, ethics and religion, Programming language, Philosophy, Operating system, DevOps taxonomies, Grounded Theory, Computer Science, Physical Sciences, Innovation and Collaboration in Open Source Community, DevOps team structures, Process management, Software, grounded theory, Information Systems, Empirical Studies in Software Engineering
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 6 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
