Computer Science

Robert Sedgewick / Kevin Wayne  
Juni 2016
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Computer Science
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Today, learning to program and understanding the basics of computation isn't just indispensable for every science and engineering student: it's crucial for everyone who wants to understand the world they live in. In Computer Science: An Interdisciplinary Approach, pioneering Princeton computer science professors Robert Sedgewick and Kevin Wayne introduce core Java programming techniques in a scientific context, while also demystifying computation and illuminating its intellectual underpinnings.


  • A broad-based, applications-based approach: learn through important and interesting real-world examples from science, mathematics, engineering, and commercial computing
  • Covers elements of programming, functions, modules, object-orientation, algorithms, data structures, and much more
  • Demystifies computation and explains its intellectual underpinnings
  • Includes question-and-answer sections, exercises, and creative exercises throughout
  • From Robert Sedgewick and Kevin Wayne, co-authors of the global best-seller Algorithms and pioneering MOOC instructors who've reached hundreds of thousands of students worldwide
  • Complements the authors' eagerly-anticipated Coursera MOOC on computer science

New to this Edition

This is an extensively expanded and deeply revised version of Sedgewick and Wayne's Introduction to Programming in Java: An Interdisciplinary Approach [9780321498052]; material from the earlier book will appear in the first half of this new text.


This new book will drive a companion Coursera course built on lectures given by the authors at Princeton University, currently in the final stages of obtaining approvals there.

Table of Contents

Preface xiii


Chapter 1: Elements of Programming 1

1.1 Your First Program 2

1.2 Built-in Types of Data 14

1.3 Conditionals and Loops 50

1.4 Arrays 90

1.5 Input and Output 126

1.6 Case Study: Random Web Surfer 170


Chapter 2: Functions and Modules 191

2.1 Defining Functions 192

2.2 Libraries and Clients 226

2.3 Recursion 262

2.4 Case Study: Percolation 300


Chapter 3: Object-Oriented Programming 329

3.1 Using Data Types 330

3.2 Creating Data Types 382

3.3 Designing Data Types 428

3.4 Case Study: N-Body Simulation 478


Chapter 4: Algorithms and Data Structures 493

4.1 Performance 494

4.2 Sorting and Searching 532

4.3 Stacks and Queues 566

4.4 Symbol Tables 624

4.5 Case Study: Small-World Phenomenon 670


Chapter 5: Theory of Computing 715

5.1 Formal Languages 718

5.2 Turing Machines 766

5.3 Universality 786

5.4 Computability 806

5.5 Intractability 822


Chapter 6: A Computing Machine 873

6.1 Representing Information 874

6.2 TOY Machine 906

6.3 Machine-Language Programming 930

6.4 TOY Virtual Machine 958


Chapter 7: Building a Computing Device 985

7.1 Boolean Logic 986

7.2 Basic Circuit Model 1002

7.3 Combinational Circuits 1012

7.4 Sequential Circuits 1048

7.5 Digital Devices 1070


Context 1093


Glossary 1097

Index 1107

APIs 1139


Robert Sedgewick is the William O. Baker Professor of Computer Science at Princeton University, where he was founding chairman of the Department of Computer Science. He has held visiting research positions at Xerox PARC, Institute for Defense Analyses, and INRIA, and served on the board of directors at Adobe Systems. His research interests include analytic combinatorics, design and analysis of algorithms and data structures, and program visualization. He has written seventeen books.


Kevin Wayne is the Phillip Y. Goldman Senior Lecturer in Computer Science at Princeton University, where he has taught since 1998, earning several teaching awards. He is an ACM Distinguished Educator and holds a Ph.D. in operations research and industrial engineering from Cornell University.