"A great book with deep insights into the bridge between programming and the human mind." - Mike Taylor, CGI Your brain responds in a predictable way when it encounters new or difficult tasks. This unique book teaches you concrete techniques rooted in cognitive science that will improve the way you learn and think about code. In The Programmer’s Brain: What every programmer needs to know about cognition you will learn: Fast and effective ways to master new programming languages Speed reading skills to quickly comprehend new code Techniques to unravel the meaning of complex code Ways to learn new syntax and keep it memorized Writing code that is easy for others to read Picking the right names for your variables Making your codebase more understandable to newcomers Onboarding new developers to your team Learn how to optimize your brain’s natural cognitive processes to read code more easily, write code faster, and pick up new languages in much less time. This book will help you through the confusion you feel when faced with strange and complex code, and explain a codebase in ways that can make a new team member productive in days! Foreword by Jon Skeet. About the technology Take advantage of your brain’s natural processes to be a better programmer. Techniques based in cognitive science make it possible to learn new languages faster, improve productivity, reduce the need for code rewrites, and more. This unique book will help you achieve these gains. About the book The Programmer’s Brain unlocks the way we think about code. It offers scientifically sound techniques that can radically improve the way you master new technology, comprehend code, and memorize syntax. You’ll learn how to benefit from productive struggle and turn confusion into a learning tool. Along the way, you’ll discover how to create study resources as you become an expert at teaching yourself and bringing new colleagues up to speed. What's inside Understand how your brain sees code Speed reading skills to learn code quickly Techniques to unravel complex code Tips for making codebases understandable About the reader For programmers who have experience working in more than one language. About the author Dr. Felienne Hermans is an associate professor at Leiden University in the Netherlands. She has spent the last decade researching programming, how to learn and how to teach it. Table of Contents PART 1 ON READING CODE BETTER 1 Decoding your confusion while coding 2 Speed reading for code 3 How to learn programming syntax quickly 4 How to read complex code PART 2 ON THINKING ABOUT CODE 5 Reaching a deeper understanding of code 6 Getting better at solving programming problems 7 Misconceptions: Bugs in thinking PART 3 ON WRITING BETTER CODE 8 How to get better at naming things 9 Avoiding bad code and cognitive load: Two frameworks 10 Getting better at solving complex problems PART 4 ON COLLABORATING ON CODE 11 The act of writing code 12 Designing and improving larger systems 13 How to onboard new developers

This book, originally published in 1992, encapsulates ten years of research at the Open University’s Human Cognition Research Laboratory. The research investigates the problems of novice programmers, and is strongly oriented toward the design and implementation of "programming environments" aimed at eliminating or easing novices’ problems. A range of languages is studied: Pascal, SOLO, Lisp, Prolog and "Knowledge Engineering Programming". The primary emphasis of the empirical studies is to gain some understanding of novices’ "mental models" of the inner workings of computers. Such (erroneous) models are constructed by novices in their own heads to account for the idiosyncrasies of particular programming languages. The primary emphasis of the implementations described in the book is the provision of "automatic debugging aids", i.e. artificial intelligence programs which can analyse novices’ buggy programs, and make sense of them, thereby providing useful advice for the novices. Another related strand taken in some of the work is the concept of "pre-emptive design", i.e. the provision of tools such as syntax-directed editors and graphical tracers which help programmers avoid many frequently-occurring errors. A common thread throughout the book is its Cognitive Science/Artificial Intelligence orientation. AI tools are used, for instance, to construct simulation models of subjects writing programs, in order to provide insights into what their deep conceptual errors are. At the other extreme, AI programs which were developed in order to help student debug their programs are observed empirically in order to ensure that they provide facilities actually needed by real programmers. This book will be of great interest to advanced undergraduate, postgraduate, and professional researchers in Cognitive Science, Artificial Intelligence, and Human-Computer Interaction.

Psychology provides a backdrop for most of the study of human*b1computer interaction. In this volume the psychological issues that pertain to programming, rather than systems design, are examined in four sections: Theoretical and Methodological Issues; Language Design and Skill Acquisition; Expert Programming; and the Future.****The book was inspired by working groups in France and the United Kingdom but also includes work by major North American figures (such as Curtis and Soloway). It is the first comprehensive work on this topic since the early 1980s.

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.

This is an authoritative introduction to Computing Education research written by over 50 leading researchers from academia and the industry.

Parallel to the growth of computer usage in society is the growth of programming instruction in schools. This informative volume unites a wide range of perspectives on the study of novice programmers that will not only inform readers of empirical findings, but will also provide insights into how novices reason and solve problems within complex domains. The large variety of methodologies found in these studies helps to improve programming instruction and makes this an invaluable reference for researchers planning studies of their own. Topics discussed include historical perspectives, transfer, learning, bugs, and programming environments.