The Programmer's Brain: What every programmer needs to know about cognition

by Felienne Hermans

Overview

"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

Product Details

ISBN-13:	9781638356059
Publisher:	Manning
Publication date:	10/05/2021
Sold by:	SIMON & SCHUSTER
Format:	eBook
Pages:	256
File size:	4 MB

About the Author

Dr. Felienne Hermans is an associate professor at Leiden University in the Netherlands. She has spent the last decade researching learning and teaching programming. Felienne is an award-winning educator, the creator of the Hedy programming language for novice programmers, and a host of Software Engineering Radio—one of the world’s largest programming podcasts.

Table of Contents

Foreword xiii

Preface xv

Acknowledgments xvii

About this book xix

About the author xxii

About the cover illustration xxiii

Part 1 On reading code better 1

1 Decoding your confusion while coding 3

1.1 Different kinds of confusion in code 4

Confusion type 1: Lack of knowledge 5

Confusion type 2: Lack of information 5

Confusion type 3: Lack of processing power 6

1.2 Different cognitive processes that affect coding 6

LTM and programming 7

STM and programming 7

Working memory and programming 8

1.3 Cognitive processes in collaboration 9

A brief dissection of how the cognitive processes interacted 9

Cognitive processes regarding programming tasks 10

2 Speed reading for code 13

2.1 Quickly reading code 14

What just happened in your brain? 15

Reexamine your reproduction 16

Reexamining your second attempt at reproducing code 17

Why is reading unfamiliar code hard? 18

2.2 Overcoming size limits in your memory 18

The power of chunking 19

Expert programmers can remember code better than beginners 22

2.3 You see more code than you can read 23

Iconic memory 23

It's not what you remember; it's the way you remember it 25

Practice chunking 30

3 How to learn programming syntax quickly 33

3.1 Tips for remembering syntax 34

Disruptions play havoc with your workflow 34

3.2 How to learn syntax quickly with flashcards 35

When to use the flashcards 36

Expanding the set of flashcards 36

Thinning the set of flashcards 36

3.3 How to not forget things 37

Why do we forget memories? 38

Spaced repetition 39

3.4 How to remember syntax longer 40

Two forms of remembering information 40

Just seeing information is not enough 41

Remembering information strengthens memories 42

Strengthen memories by actively thinking 42

4 How to read complex code 46

4.1 Why it's hard to understand complex code 47

What's the difference between working memory and STM? 48

Types of cognitive load as they relate to programming 49

4.2 Techniques to reduce cognitive load 51

Refactoring 51

Replacing unfamiliar language constructs 52

Code synonyms are great additions to a flashcard deck 55

4.3 Memory aids to use when your working memory is overloaded 56

Creating a dependency graph 56

Using a state table 59

Combining dependency graphs and state tables 61

Part 2 On thinking about code 65

5 Reaching a deeper understanding of code 67

5.1 Roles of variables framework 68

Different variables do different things 68

Eleven roles to cover almost all variables 69

5.2 Roles and paradigms 71

Benefits of roles 72

Hungarian notation 73

5.3 Gaining a deeper knowledge of programs 75

Text knowledge vs. plan knowledge 75

Different stages of program understanding 76

5.4 Reading text is similar to reading code 79

What happens in the brain when we read code? 79

If you can learn French, you can learn Python 81

5.5 Text comprehension strategies applied to code 84

Activating prior knowledge 84

Monitoring 85

Determining the importance of different lines of code 86

Inferring the meaning of variable names 87

Visualizing 88

Questioning 89

Summarizing code 90

6 Getting better at solving programming problems 91

6.1 Using models to think about code 92

The benefits of using models 92

6.2 Mental models 94

Examining mental models in detail 96

Learning new menial models 97

How to use mental models efficiently when thinking about code 97

6.3 Notional machines 102

What is a notional machine? 103

Examples of notional machines 103

Different levels of notional machines 105

6.4 Notional machines and language 106

Expanding sets of notional machines 106

Different notional machines can create conflicting mental models 107

6.5 Notional machines and schemata 108

Why schemata matters 108

Are notional machines semantics? 109

7 Misconceptions: Bugs in thinking 110

7.1 Why learning a second programming language is easier than learning the first one 111

How to increase the chances of benefiting from existing programming knowledge 113

Different forms of transfer 114

Already knowing something: Curse or blessing? 115

The difficulties of transfer 116

7.2 Misconceptions: Bugs in thinking 117

Debugging misconceptions with conceptual change 118

Suppressing misconceptions 119

Misconceptions about programming languages 120

Preventing misconceptions while learning a new programming language 122

Diagnosing misconceptions in a new codebase 122

Part 3 On writing better code 125

8 How to get better at naming things 127

8.1 Why naming matters 128

Why naming matters 129

Different perspectives on naming 129

Initial naming practices have a lasting impact 131

8.2 Cognitive aspects of naming 133

Formatting names supports your STM 133

Clear names help your LTM 134

Variable names can contain different types of information to help you understand them 135

When to evaluate the quality of names 136

8.3 What types of names are easier to understand? 137

To abbreviate or not to abbreviate? 137

Snake case or camel case? 140

8.4 The influence of names on bugs 141

Code with bad names has more bugs 141

8.5 How to choose better names 142

Name molds 142

Feitelson's three-step model for better variable names 145

9 Avoiding bad code and cognitive load: Two frameworks 147

9.1 Why code with code smells creates a lot of cognitive load 148

A brief intro to code smells 148

How code smells harm cognition 151

9.2 The influence of bad names on cognitive load 153

Linguistic antipatterns 154

Measuring cognitive load 155

Linguistic antipatterns and cognitive load 158

Why linguistic antipatterns cause confusion 159

10 Getting better at solving complex problems 160

10.1 What is problem solving? 161

Elements of problem solving 161

Slate space 161

10.2 What is the role of the LTM when you solve programming problems? 162

Is problem solving a cognitive process on its own? 162

How to teach your LTM to solve problems 164

Two types of memories that play a role in problem solving 164

10.3 Automatization: Creating implicit memories 167

Implicit memories over time 168

Why automatization will make you program quicker 170

Improving implicit memories 171

10.4 Learning from code and its explanation 172

A new type of cognitive load: Germane load 173

Using worked examples in your working life 175

Part 4 On collaborating on code 177

11 The act of writing code 179

11.1 Different activities while programming 180

Searching 180

Comprehension 181

Transcription 181

Incrementation 181

Exploration 182

What about debugging? 182

11.2 Programmer interrupted 183

Programming tasks require a warm-up 183

What happens after an interruption? 184

How to better prepare for interruptions 185

When to interrupt a programmer 187

Some thoughts on multitasking 189

12 Designing and improving larger systems 191

12.1 Examining the properties of codebases 192

Cognitive dimensions 192

Using CDCB to improve your codebase 200

Design maneuvers and their trade-offs 201

12.2 Dimensions and activities 202

Impact of dimensions on different activities 202

Optimizing your codebase for expected activities 204

13 How to onboard new developers 205

13.1 Issues in the onboarding process 206

13.2 Differences between experts and novices 207

Beginners' behavior in more depth 207

Difference between seeing concepts concretely and abstractly 211

13.3 Activities for a better onboarding process 213

Limit tasks to one programming activity 213

Support the memory of the onboardee 214

Read code together 216

13.4 Some words to close this book 221

Epilogue 221

Index 223