Carla Rocha

Isaque Alves, Carla Rocha

The constant changes in the software industry, practices, and methodologies impose challenges to teaching and learning current software engineering concepts and skills. DevOps is particularly challenging because it covers technical concepts, such as pipeline automation, and non-technical ones, such as team roles and project management. The present study investigates a course setup to introduce these concepts to software engineering undergraduates. We designed the course by employing coding to associate DevOps concepts to Agile, Lean, and Open source practices and tools. We present the main aspects of this project-oriented DevOps course, with 240 students enrolled in it since its first offering in 2016. We conducted an empirical study, with both a quantitative and qualitative analysis, to evaluate this project-oriented course setup. We collected the data from the projects repository and students perceptions from a questionnaire. We mined 148 repositories (corresponding to 72 projects) and obtained 86 valid responses to the questionnaire. We also mapped the concepts which are more challenging to students learn from experience. The results evidence that first-hand experience facilitates the comprehension of DevOps concepts and enriches classes discussions. We present a set of lessons learned, which may help professors better design and conduct project-oriented courses to cover DevOps concepts.

Isaque Alves, Fabio Kon, Jessica Diaz et al.

Software Engineering often adapts theory-building frameworks from the social sciences to address socio-technical complexity. The key phases of the theory-building process are conceptual development, operationalization, testing, and application. Operationalization translates abstract concepts into measurable elements for empirical validation. This phase is essential for delivering the practical utility required by an applied science like Software Engineering. We propose a systematic procedure for the operationalization phase that bridges the gap between abstract concepts and empirical validation, ensuring the resulting theory is both rigorous and practically useful. We extend the operationalization framework proposed by Sjøberg et al. and formulate non-causal hypotheses following Dubin's approach. Our procedure defines variables, selects indicators, and systematically derives hypotheses. We present a replicable, evidence-based methodological guideline that preserves a clear chain of evidence and supports practical validation. We illustrate the procedure using the DevOps Team Taxonomies Theory. This guideline provides a transparent chain of evidence from theory to testable elements, empowering researchers to ground theoretical advancements in empirical evidence and deliver actionable insights for practitioners.

Leonardo Leite, Carla Rocha, Fabio Kon et al.

DevOps is a collaborative and multidisciplinary organizational effort to automate continuous delivery of new software updates while guaranteeing their correctness and reliability. The present survey investigates and discusses DevOps challenges from the perspective of engineers, managers, and researchers. We review the literature and develop a DevOps conceptual map, correlating the DevOps automation tools with these concepts. We then discuss their practical implications for engineers, managers, and researchers. Finally, we critically explore some of the most relevant DevOps challenges reported by the literature.