Systematic Literature Review on Model Transformation for Advanced Generation of Pipelines within DevOps Solutions

Since its inception in 2009, DevOps has driven significant advancements in software development in terms of methodologies and support tools, developed both by industry, as well as a result of academic research. In turn to further enhance software development speed without compromising quality, this paper argues that DevOps as such also requires a digital solution for its automation. While previous studies have extensively explored the evolution of DevOps and its associated methodologies, these efforts have been insufficient. Existing research lacks comprehensive analysis and fails to address the full scope of DevOps formalization challenges and opportunities, which is the key prerequisite for automation. Researchers and practitioners are actively seeking innovative approaches, such as model-driven engineering, to expedite automation of software development processes even further. This systematic literature review aims to fill these gaps by providing a more thorough examination of the literature and offering deeper insights into the potential of combining DevOps and model-driven approaches. The paper investigates literature of the last 15 years on how to streamline DevOps pipeline generation that are grounded in model transformation techniques.