Large scale continuous integration and delivery:Making great software better and faster

Since the inception of continuous integration, and later continuous delivery, the methods of producing software in the industry have changed dramatically over the last two decades. Automated, rapid and frequent compilation, integration, testing, analysis, packaging and delivery of new software versions have become commonplace. This change has had significant impact not only on software engineering practice, but on the way we as consumers and indeed as a society relate to software. Moreover, as we live in an increasingly software-intensive and software-dependent world, the quality and reliability of the systems we use to build, test and deliver that software is a crucial concern. At the same time, it is repeatedly shown that the successful and effective implementation of continuous engineering practices is far from trivial, particularly in a large scale context.This thesis approaches the software engineering practices of continuous integration and delivery from multiple points of view, and is split into three parts, accordingly.Part I focuses on understanding the nature of continuous integration and differences in its interpretation and implementation. In order to address this divergence and provide practitioners and researchers alike with better and less ambiguous methods for describing and designing continuous integration and delivery systems, Part II applies the paradigm of system modeling to continuous integration and delivery. Meanwhile, Part III addresses the problem of traceability. Unique challenges to traceability in the context of continuous practices are highlighted, and possible solutions are presented and evaluated