Engineering Generative AI Software
A practical guide to engineering generative AI-based systems, from requirements and architecture to data management, licensing, feedback loops, and long-term evolution. The book connects current models and platforms with the software engineering practices needed to build dependable AI-enabled products.
Machine Learning Infrastructure and Best Practices for Software Engineers
A software engineering view of machine learning systems: how to move from prototypes to production-quality products. The book covers pipelines, algorithm selection, data quality, infrastructure, testing, and ethical risk management for large-scale ML software.
Automotive Software Architectures: An Introduction
An introduction to the software architecture of modern vehicles, written for practitioners and students who need to understand automotive systems, their constraints, and their architectural trade-offs. The book uses real-world examples and does not require prior automotive background.
Action Research in Software Engineering
A guide to action research for academia-industry collaboration in software engineering. It follows the lifecycle of an action research project, from diagnosis and intervention planning to execution, learning, reporting, and validity assessment.
Software Development Measurement Programs
A book about building software measurement programs that are scientifically grounded, cost-aware, standardized, and useful for decision-making. It connects measurement theory with the organizational work needed to keep measurement systems valuable in practice.