Features include:The use of boxes to strengthen the narrative: pieces that provide historical context, descriptions of how the algorithms are used in practice, and excursions for the mathematically sophisticated.

Carefully chosen advanced topics that can be skipped in a standard one-semester course, but can be covered in an advanced algorithms course or in a more leisurely two-semester sequence.

An accessible treatment of linear programming introduces students to one of the greatest achievements in algorithms. An optional chapter on the quantum algorithm for factoring provides a unique peephole into this exciting topic. In addition to the text, DasGupta also offers a Solutions Manual, which is available on the Online Learning Center.

"Algorithms is an outstanding undergraduate text, equally informed by the historical roots and contemporary applications of its subject. Like a captivating novel, it is a joy to read." Tim Roughgarden Stanford University

0 Prologue

1 Algorithms with Numbers

2 Divide-and-Conquer Algorithms

3 Decompositions of Graphs

4 Paths in Graphs

5 Greedy algorithms

6 Dynamic Programming

7 Linear Programming and Reductions

8 NP-complete Problems

9 Coping with NP-completeness

10 Quantum Algorithms