Table of Contents

• I. PRELIMINARIES.
• Column 1. Cracking the Oyster. 
• Column 2. Aha! Algorithms.
• Column 3. Data Structures Programs.
• Column 4. Writing Correct Programs.
• Column 5. A Small Matter of Programming.
• II. PERFORMANCE.
• Column 6. Perspective on Performance.
• Column 7. The Back of the Envelope.
• Column 8. Algorithm Design Techniques.
• Column 9. Code Tuning.
• Column 10. Squeezing Space.
• III. THE PRODUCT.
• Column 11. Sorting.
• Column 12. A Sample Problem.
• Column 13. Searching.
• Column 14. Heaps.
• Column 15. Strings of Pearls.
• Appendix 1. A Catalog of Algorithms.
• Appendix 2. An Estimation Quiz.
• Appendix 3. Cost Models for Time and Space.
• Appendix 4. Rules for Code Tuning.
• Appendix 5. C++ Classes for Searching.
• Hints for Selected Problems.
  

About the Author

I. PRELIMINARIES. Column 1. Cracking the Oyster. A Friendly Conversation.Precise Problem Statement.Program Design.Implementation Sketch.Principles.Problems.Further Reading.Column 2. Aha! Algorithms. Three Problems.Ubiquitous Binary Search.The Power of Primitives.Getting It Together: Sorting.Principles * Problems.Further Reading.Implementing an Anagram Program.Column 3. Data Structures Programs. A Survey Program.Form-Letter Programming.An Array of Examples.Structuring Data.Powerful Tools for Specialized Data.Principles.Problems.Further Reading.Column 4. Writing Correct Programs. The Challenge of Binary Search.Writing the Program.Understanding the Program.Principles.The Roles of Program Verification.Problems.Further Reading.Column 5. A Small Matter of Programming. From Pseudocode to C.A Test Harness.The Art of Assertion.Automated Testing.Timing.The Complete Program.Principles.Problems.Further Reading.Debugging.II. PERFORMANCE. Column 6. Perspective on Performance. A Case Study.Design Levels.Principles.Problems.Further Reading.Column 7. The Back of the Envelope. Basic Skills.Performance Estimates.Safety Factors.Little's Law.Principles.Problems.Further Reading.Quick Calculations in Everyday Life.Column 8. Algorithm Design Techniques. The Problem and a Simple Algorithm.Two Quadratic Algorithms.A Divide-and-Conquer Algorithm.A Scanning Algorithm.What Does It Matter?Principles.Problems.Further Reading.Column 9. Code Tuning. A Typical Story.A First Aid Sampler.Major Surgery--Binary Search.Principles.Problems.Further Reading.Column 10. Squeezing Space. The Key--Simplicity.An Illustrative Problem.Techniques for Data Space.Techniques for Code Space.Principles.Problems.Further Reading.A Big Squeeze.III. THE PRODUCT. Column 11. Sorting. Insertion Sort.A Simple Quicksort.Better Quicksorts.Principles.Problems.Further Reading.Column 12. A Sample Problem. The Problem.One Solution.The Design Space.Principles.Problems.Further Reading.Column 13. Searching. The Interface.Linear Structures.Binary Search Trees.Structures for Integers.Principles.Problems.Further Reading.A Real Searching Problem.Column 14. Heaps. The Data Structure.Two Critical Functions.Priority Queues.A Sorting Algorithm.Principles.Problems.Further Reading.Column 15. Strings of Pearls. Words.Phrases.Generating Text.Principles.Problems.Further Reading.Epilog to the First Edition. Epilog to the Second Edition. Appendix 1. A Catalog of Algorithms. Appendix 2. An Estimation Quiz. Appendix 3. Cost Models for Time and Space. Appendix 4. Rules for Code Tuning. Appendix 5. C++ Classes for Searching. Hints for Selected Problems. Solutions to Selected Problems. Index.