The practice of programming is more than just writing code. Programmers must also assess tradeoffs, choose among design alternatives, debug and test, improve performance, and maintain software written by themselves and others. At the same time, they must be concerned with issues like compatibility, robustness, and reliability, while meeting specifications.

The Practice of Programming covers all these topics, and more. This book is full of practical advice and real-world examples in C, C++, Java, and a variety of special-purpose languages. It includes chapters on:

• Debugging: finding bugs quickly and methodically
• Testing: guaranteeing that software works correctly and reliably
• Performance: making programs faster and more compact
• Portability: ensuring that programs run everywhere without change
• Design: balancing goals and constraints to decide which algorithms and data structures are best
• Interfaces: using abstraction and information hiding to control the interactions between components
• Style: writing code that works well and is a pleasure to read
• Notation: choosing languages and tools that let the machine do more of the work

Table of contents

Chapter 1: Style

1.1 Names

1.2 Expressions and Statements

1.3 Consistency and Idioms

1.4 Function Macros

1.5 Magic Numbers

1.6 Comments

1.7 Why Bother?

Chapter 2: Algorithms and Data Structures

2.1 Searching

2.2 Sorting

2.3 Libraries

2.4 A Java Quicksort

2.5 O-Notation

2.6 Growing Arrays

2.7 Lists

2.8 Trees

2.9 Hash Tables

2.10 Summary

Chapter 3: Design and Implementation

3.1 The Markov Chain Algorithm

3.2 Data Structure Alternatives

3.3 Building the Data Structure in C

3.4 Generating Output

3.5 Java

3.6 C++

3.7 Awk and Perl

3.8 Performance

3.9 Lessons

Chapter 4: Interfaces

4.1 Comma-Separated Values

4.2 A Prototype Library

4.3 A Library for Others

4.4 A C++ Implementation

4.5 Interface Principles

4.6 Resource Management

4.7 Abort, Retry, Fail?

4.8 User Interfaces

Chapter 5: Debugging

5.1 Debuggers

5.2 Good Clues, Easy Bugs

5.3 No Clues, Hard Bugs

5.4 Last Resorts

5.5 Non-reproducible Bugs

5.6 Debugging Tools

5.7 Other People's Bugs

5.8 Summary

Chapter 6: Testing

6.1 Test as You Write the Code

6.2 Systematic Testing

6.3 Test Automation

6.4 Test Scaffolds

6.5 Stress Tests

6.6 Tips for Testing

6.7 Who Does the Testing?

6.8 Testing the Markov Program

6.9 Summary

Chapter 7: Performance

7.1 A Bottleneck

7.2 Timing and Profiling

7.3 Strategies for Speed

7.4 Tuning the Code

7.5 Space Efficiency

7.6 Estimation

7.7 Summary

Chapter 8: Portability

8.1 Language

8.2 Headers and Libraries

8.3 Program Organization

8.4 Isolation

8.5 Data Exchange

8.6 Byte Order

8.7 Portability and Upgrade

8.8 Internationalization

8.9 Summary

Chapter 9: Notation

9.1 Formatting Data

9.2 Regular Expressions

9.3 Programmable Tools

9.4 Interpreters, Compilers, and Virtual Machines

9.5 Programs that Write Programs

9.6 Using Macros to Generate Code

9.7 Compiling on the Fly

Epilogue

Appendix: Collected Rules

Index