Are you looking for something different in your Algorithms text? Are you looking for an Algorithms text that offers theoretical analysis techniques as well as design patterns and experimental methods for the engineering of algorithms? Michael Goodrich and Roberto Tamassia, authors of the successful, Data Structures and Algorithms in Java, 2/e, have written Algorithm Design, a text designed to provide a comprehensive introduction to the design, implementation and analysis of computer algorithms and data structures from a modern perspective. Written for an undergraduate, junior-senior algorithms course this text offers several implementation case studies and uses Internet applications to motivate many topics such as hashing, sorting and searching.

Table of Contents:
I Fundamental Tools 1 1 Algorithm Analysis 3 1.1 Methodologies for Analyzing Algorithms  5 1.2 Asymptotic Notation 13 1.3 A Quick Mathematical Review  21 1.4 Case Studies in Algorithm Analysis  31 1.5 Amortization  34 1.6 Experimentation  42 1.7 Exercises  47 2 Basic Data Structures 55 2.1 Stack sand Queues  57 2.2 Vectors, Lists, and Sequences  65 2.3 Trees  75 2.4 Priority Queues and Heaps  94 2.5 Dictionaries and Hash Tables  114 2.6 Java Example: Heap  128 2.7 Exercises  131 3 Search Trees and Skip Lists 139 3.1 Ordered Dictionaries and Binary Search Trees  141 3.2 AVL Trees  152 3.3 Bounded-Depth Search Trees  159 3.4 Splay Trees  185 3.5 Sk i p Lists  195 3.6 Java Example: AVL and Red-Black Trees  202 3.7 Exercises  212 4 Sorting, Sets, and Selection 217 4.1 Merge-Sort  219 4.2 The Set Abstract Data Type  225 4.3 Quick -Sort  235 4.4 A Lower Bound on Comparison-Based Sorting  239 4.5 Buck et-Sort and Radix-Sort  241 4.6 Comparison of Sorting Algorithms  244 4.7 Selection  245 4.8 Java Example: In-Place Quick -Sort  248 4.9 Exercises  251 5 Fundamental Techniques 257 5.1 The GreedyMethod  259 5.2 Divide-and-Conquer  263 5.3 Dynamic Programming  274 5.4 Exercises  282 II Graph Algorithms 285 6 Graphs 287 6.1 The Graph Abstract Data Type  289 6.2 Data Structures for Graphs  296 6.3 Graph Traversal  303 6.4 Directed Graphs  316 6.5 Java Example: Depth-First Search  329 6.6 Exercises  335 7 Weighted Graphs 339 7.1 Single-Source Shortest Paths  341 7.2 All-Pairs Shortest Paths  354 7.3 Minimum Spanning Trees  360 7.4 Java Example: Dijk stra’s Algorithm  373 7.5 Exercises  376 8 Network Flow and Matching 381 8.1 Flows and Cuts  383 8.2 Maximum Flow  387 8.3 Maximum BipartiteMatching  396 8.4 Minimum-Cost Flow  398 8.5 Java Example: Minimum-Cost Flow  405 8.6 Exercises  412 III Internet Algorithmics 415 9 Text Processing 417 9.1 Strings and PatternMatching Algorithms  419 9.2 Tries  429 9.3 Text Compression  440 9.4 Text Similarity Testing  443 9.5 Exercises  447 10 Number Theory and Cryptography 451 10.1 Fundamental Algorithms Involving Numbers  453 10.2 Cryptographic Computations  471 10.3 Information Security Algorithms and Protocols  481 10.4 The Fast Fourier Transform  488 10.5 Java Example: FFT  500 10.6 Exercises  508 11 Network Algorithms 511 11.1 ComplexityMeasures and Models  513 11.2 Fundamental Distributed Algorithms  517 11.3 Broadcast and Unicast Routing  530 11.4 Multicast Routing  535 11.5 Exercises  541 IV Additional Topics 545 12 Computational Geometry 547 12.1 Range Trees  549 12.2 Priority Search Trees  556 12.3 Quadtrees and k-D Trees  561 12.4 The Plane Sweep Technique  565 12.5 Convex Hulls  572 12.6 Java Example: Convex Hull  583 12.7 Exercises  587 13 NP-Completeness 591 13.1 P and NP  593 13.2 NP-Completeness  599 13.3 Important NP-Complete Problems  603 13.4 Approximation Algorithms  618 13.5 Back track i ng and Branch-and-Bound  627 13.6 Exercises  638 14 Algorithmic Frameworks 643 14.1 External-Memory Algorithms  645 14.2 Parallel Algorithms  657 14.3 Online Algorithms  667 14.4 Exercises  680 A Useful Mathematical Facts 685 Bibliography 689 Index 698