Software Design

An engaging, illustrated collection of insights revealing the practices and principles that expert software designers use to create great software. What makes an expert software designer? It is more than experience or innate ability. Expert software designers have specific habits, learned practices, and observed principles that they apply deliberately during their design work. This book offers sixty-six insights, distilled from years of studying experts at work, that capture what successful software designers actually do to create great software. The book presents these insights in a series of two-page illustrated spreads, with the principle and a short explanatory text on one page, and a drawing on the facing page. For example, “Experts generate alternatives” is illustrated by the same few balloons turned into a set of very different balloon animals. The text is engaging and accessible; the drawings are thought-provoking and often playful. Organized into such categories as “Experts reflect,” “Experts are not afraid,” and “Experts break the rules,” the insights range from “Experts prefer simple solutions” to “Experts see error as opportunity.” Readers learn that “Experts involve the user”; “Experts take inspiration from wherever they can”; “Experts design throughout the creation of software”; and “Experts draw the problem as much as they draw the solution.” One habit for an aspiring expert software designer to develop would be to read and reread this entertaining but essential little book. The insights described offer a guide for the novice or a reference for the veteran—in software design or any design profession. A companion web site provides an annotated bibliography that compiles key underpinning literature, the opportunity to suggest additional insights, and more.

Strategies for building large systems that can be easily adapted for new situations with only minor programming modifications. Time pressures encourage programmers to write code that works well for a narrow purpose, with no room to grow. But the best systems are evolvable; they can be adapted for new situations by adding code, rather than changing the existing code. The authors describe techniques they have found effective--over their combined 100-plus years of programming experience--that will help programmers avoid programming themselves into corners. The authors explore ways to enhance flexibility by: Organizing systems using combinators to compose mix-and-match parts, ranging from small functions to whole arithmetics, with standardized interfaces Augmenting data with independent annotation layers, such as units of measurement or provenance Combining independent pieces of partial information using unification or propagation Separating control structure from problem domain with domain models, rule systems and pattern matching, propagation, and dependency-directed backtracking Extending the programming language, using dynamically extensible evaluators

This is a practical guide for software developers, and different than other software architecture books. Here's why: It teaches risk-driven architecting. There is no need for meticulous designs when risks are small, nor any excuse for sloppy designs when risks threaten your success. This book describes a way to do just enough architecture. It avoids the one-size-fits-all process tar pit with advice on how to tune your design effort based on the risks you face. It democratizes architecture. This book seeks to make architecture relevant to all software developers. Developers need to understand how to use constraints as guiderails that ensure desired outcomes, and how seemingly small changes can affect a system's properties. It cultivates declarative knowledge. There is a difference between being able to hit a ball and knowing why you are able to hit it, what psychologists refer to as procedural knowledge versus declarative knowledge. This book will make you more aware of what you have been doing and provide names for the concepts. It emphasizes the engineering. This book focuses on the technical parts of software development and what developers do to ensure the system works not job titles or processes. It shows you how to build models and analyze architectures so that you can make principled design tradeoffs. It describes the techniques software designers use to reason about medium to large sized problems and points out where you can learn specialized techniques in more detail. It provides practical advice. Software design decisions influence the architecture and vice versa. The approach in this book embraces drill-down/pop-up behavior by describing models that have various levels of abstraction, from architecture to data structure design.

Are you working on a codebase where cost overruns, death marches, and heroic fights with legacy code monsters are the norm? Battle these adversaries with novel ways to identify and prioritize technical debt, based on behavioral data from how developers work with code. And that's just for starters. Because good code involves social design, as well as technical design, you can find surprising dependencies between people and code to resolve coordination bottlenecks among teams. Best of all, the techniques build on behavioral data that you already have: your version-control system. Join the fight for better code! Use statistics and data science to uncover both problematic code and the behavioral patterns of the developers who build your software. This combination gives you insights you can't get from the code alone. Use these insights to prioritize refactoring needs, measure their effect, find implicit dependencies between different modules, and automatically create knowledge maps of your system based on actual code contributions. In a radical, much-needed change from common practice, guide organizational decisions with objective data by measuring how well your development teams align with the software architecture. Discover a comprehensive set of practical analysis techniques based on version-control data, where each point is illustrated with a case study from a real-world codebase. Because the techniques are language neutral, you can apply them to your own code no matter what programming language you use. Guide organizational decisions with objective data by measuring how well your development teams align with the software architecture. Apply research findings from social psychology to software development, ensuring you get the tools you need to coach your organization towards better code. If you're an experienced programmer, software architect, or technical manager, you'll get a new perspective that will change how you work with code. What You Need: You don't have to install anything to follow along in the book. TThe case studies in the book use well-known open source projects hosted on GitHub. You'll use CodeScene, a free software analysis tool for open source projects, for the case studies. We also discuss alternative tooling options where they exist.

With this practical book, architects, CTOs, and CIOs will learn a set of patterns for the practice of architecture, including analysis, documentation, and communication. Author Eben Hewitt shows you how to create holistic and thoughtful technology plans, communicate them clearly, lead people toward the vision, and become a great architect or Chief Architect. This book covers each key aspect of architecture comprehensively, including how to incorporate business architecture, information architecture, data architecture, application (software) architecture together to have the best chance for the system’s success. Get a practical set of proven architecture practices focused on shipping great products using architecture Learn how architecture works effectively with development teams, management, and product management teams through the value chain Find updated special coverage on machine learning architecture Get usable templates to start incorporating into your teams immediately Incorporate business architecture, information architecture, data architecture, and application (software) architecture together

Covering a variety of areas including software analysis, design, coding and maintenance, this text details the research conducted since the 1970s in this fast-developing field before going on to define a computer program from the viewpoint of computing and cognitive psychology. The two essential sides of programming, software production and software understanding, are given detailed treatment, with parallels drawn throughout between studies on processing texts written in natural language and processing computer programs. Of particular interest to researchers, practitioners and graduates in cognitive psychology, cognitive ergonomics and computer science.

Today, software engineers need to know not only how to program effectively but also how to develop proper engineering practices to make their codebase sustainable and healthy. This book emphasizes this difference between programming and software engineering. How can software engineers manage a living codebase that evolves and responds to changing requirements and demands over the length of its life? Based on their experience at Google, software engineers Titus Winters and Hyrum Wright, along with technical writer Tom Manshreck, present a candid and insightful look at how some of the world’s leading practitioners construct and maintain software. This book covers Google’s unique engineering culture, processes, and tools and how these aspects contribute to the effectiveness of an engineering organization. You’ll explore three fundamental principles that software organizations should keep in mind when designing, architecting, writing, and maintaining code: How time affects the sustainability of software and how to make your code resilient over time How scale affects the viability of software practices within an engineering organization What trade-offs a typical engineer needs to make when evaluating design and development decisions