Software Engineering

Build bulletproof Spring Boot microservices—from monolith migration to domain-driven design and event-driven patterns—while mastering the production essentials of resilience, observability, and zero‑downtime delivery. Turn complex domains into clean, scalable services with bounded contexts, aggregates, repositories, and domain events, then ship faster with rate‑limited APIs, backoff‑retries, and Kubernetes rollouts. If leading Java teams to reliable, cloud‑ready microservices is the goal, this is the hands‑on guide that gets systems into production with confidence.

You want to analyse, understand and capture the subject matter of a domain, typically because you want to build a software system in that domain? You're looking for abstractions to describe and ultimately execute said subject matter? Then this book is for you: it's chock-full of experience and practices for tackling this challenge.

Top 3 reasons why a software engineer might be interested to work at capital markets firms1) work with top Hedge Funds, Investment Banks, HFT firms, Algorithmic Trading firms, Exchanges, etc.2) implement smart algorithms and build low-latency, high-performance and mission-critical software with talented engineers3) earn top compensation

“Happily purchased. Handy to have these in one place. Thank you!” — Kent Beck “Excellent new thinking on Domain-Driven Design. It's full of real practical experience in getting the most value from domain modelling. Just like the Eric Evans' DDD book, this gives more insight each time you read it.” — Ian Russell

Modern AI applications are not built from scratch but, instead, by integrating off-the-shelf components: libraries, frameworks, and services. "Applied Artificial Intelligence - An Engingeering Approach" focuses on engineering user friendly, high-performance, and maintainable AI applications.

Build reliable distributed systems with Spring Boot, RabbitMQ and modern Java. Follow OrderFlow as it grows from a simple service into a production-ready event-driven platform, exploring architecture, messaging, observability, containers and the practical trade-offs behind every design decision.

Go beyond C++ syntax and learn to use the STL with confidence. Explore containers, algorithms, iterators, ranges and more through practical examples, performance insights and real-world patterns. Build a deeper understanding of how the STL works, when to use each tool and how to write cleaner, faster and more maintainable C++.

AI coding agents can build, run and break things at machine speed. This book shows you how to contain them safely. From Linux isolation and microVMs to WebAssembly, threat modeling and incident response, you’ll learn how to design production-grade sandboxes that let autonomous agents execute code without putting your systems at risk.

Distributed systems can feel overwhelming until you build one yourself. This book takes you from core networking and concurrency concepts to a complete production-ready platform in Go. Every chapter adds real working code so you learn not just the theory but how reliable systems are built and run at scale.

Whether you're writing your first line of code or building professional applications, this book takes you from the fundamentals to real world Python development. Learn the skills, tools and best practices used by experienced developers to write clean, reliable and scalable code with confidence.

Make ChatGPT, Perplexity, Claude and Google AI cite the sites you build. A code-first AEO/GEO guide for developers and agencies — with a production-tested Next.js boilerplate.

Trunk-based development and branch by abstraction super reference. All the aspects of this industry leading branching model covered.

Ihre Use Cases haben einen neuen Leser: einen KI-Agenten, der sie direkt in Code und Tests umwandelt. Die Implementierung ist mittlerweile kostengünstig, doch die präzise Formulierung der Absicht stellt den Engpass dar. Dieser Leitfaden vermittelt Ihnen, wie Sie Use Cases verfassen, die sowohl für Stakeholder und Ingenieure als auch für die KI-Agenten, die sie umsetzen, funktionieren.

Vector databases give you a similarity metric, an index with four tuning parameters, acompression option and a way to filter — and almost no guidance on what any of it costs. This book builds each one from scratch and measures it. The proximity graph, the invertedfile, the product quantiser: implemented in NumPy, included with the text, and checkedagainst exhaustive search — so every recall figure here is exact rather than estimated.

This textbook is designed for use in introductory Software Engineering courses. Additionally, it can be used by junior developers intending to consolidate their knowledge in the field. It has also a web version available at https://softengbook.org.