Some computer science books are classic but not suitable for beginners, and some are the opposite. Donald Knuth‘s The Art Of Computer Programming probably belongs to the former condition, and Robert Sedgewick‘s Algorithms belongs to the latter. Of course, both of their algorithm analysis idea comes down in one continuous line, and they are all the classic and bestselling reference book in the computerized algorithm field.

Algorithms covers 50 Algorithms that every programmer must master, provides a comprehensive introduction to the necessary knowledge about algorithms and data structures, and especially discusses sorting, searching, graph processing, and string processing. This book has concise content, examples presented with rich visual elements, well-designed java-based code implementations (employs a modular programming style, which is easy for the reader to modify and utilize), detailed historical and scientific background knowledge, exercises of various difficulties, and more.

Beyond all question, Introduction to Algorithms places emphasis on mathematical derivation (making people feel sleepy), has beautiful pseudo code, broad and comprehensive coverage, and is superior academically. Algorithms, by contrast, focuses on the implementation of algorithms, comes with much more detailed and vivid explanations, as well as much more specialized practical applications than the former.

On the whole, Algorithms is widely regarded as the single best (and fascinating) introductory book to data structures and algorithms, and much better than the Introduction to Algorithms, which is known as a standard textbook. That’s the very difference between doing academic research and practical engineering. That is, if you’re a software engineer and not a scholar or lecturer at school, then choosing to read Algorithms instead is the only sensible option for you.

// Table Of Contents //

• Chapter 1: Fundamentals 3
  • 1.1 Basic Programming Model 8
  • 1.2 Data Abstraction 64
  • 1.3 Bags, Queues, and Stacks 120
  • 1.4 Analysis of Algorithms 172
  • 1.5 Case Study: Union-Find 216
• Chapter 2: Sorting 243
  • 2.1 Elementary Sorts 244
  • 2.2 Mergesort 270
  • 2.3 Quicksort 288
  • 2.4 Priority Queues 308
  • 2.5 Applications 336
• Chapter 3: Searching 361
  • 3.1 Symbol Tables 362
  • 3.2 Binary Search Trees 396
  • 3.3 Balanced Search Trees 424
  • 3.4 Hash Tables 458
  • 3.5 Applications 486
• Chapter 4: Graphs 515
  • 4.1 Undirected Graphs 518
  • 4.2 Directed Graphs 566
  • 4.3 Minimum Spanning Trees 604
  • 4.4 Shortest Paths 638
• Chapter 5: Strings 695
  • 5.1 String Sorts 702
  • 5.2 Tries 730
  • 5.3 Substring Search 758
  • 5.4 Regular Expressions 788
  • 5.5 Data Compression 810
• Chapter 6: Context 853

// Book Example Codes //

• Algorithms, 4th edition textbook code and libraries download
• Algorithms and clients in the textbook

// Download URLs //

Author	Format	Download	Size
Robert Sedgewick and Kevin Wayne	PDF		11.9 MB
Jeff Erickson	PDF	Everything in one big file (1250 pages) All models lecture notes in one file (125 pages) All algorithms lecture notes in one file (514 pages) All homeworks, labs, and exams in one file (611 pages)	n/a

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