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Algorithms

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The leading introduction to computer algorithms in use today, including fifty algorithms every programmer should know

Princeton Computer Science professors, Robert Sedgewick and Kevin Wayne, survey the most important computer algorithms in use and of interest to anyone working in science, mathematics, and engineering, and those who use computation in the liberal arts. They provide a full treatment of data structures and algorithms for key areas that enable you to confidently implement, debug, and put them to work in any computational environment.

Fundamentals

  • Basic programming models
  • Data abstraction
  • Bags, queues, and stacks
  • Analysis of algorithms

Sorting

  • Elementary sorts
  • Mergesort
  • Quicksort
  • Priority queues
  • Applications

Graphs

  • Undirected graphs
  • Directed graphs
  • Minimum spanning trees
  • Shortest paths

Strings

  • String sorts
  • Tries
  • Substring search
  • Regular expressions
  • Data compression

These algorithms are generally ingenious creations that, remarkably, can each be expressed in just a dozen or two lines of code. As a group, they represent problem-solving power of amazing scope. They have enabled the construction of computational artifacts, the solution of scientific problems, and the development of commercial applications that would not have been feasible without them.

Author(s): Robert Sedgewick, Kevin Wayne
Edition: 4
Publisher: Addison-Wesley Professional
Year: 2011

Language: English
Commentary: [Eleventh Printing][October 2017][True PDF][InformIT]
Pages: 976

Cover
Title Page
Copyright Page
Contents
Preface
1. Fundamentals
1.1 Basic Programming Model
Primitive data types
Loops and conditionals
Arrays
Static methods
Recursion
APIs
Strings
Input and output
Binary search
1.2 Data Abstraction
Objects
Abstract data types
Implementing ADTs
Designing ADTs
1.3 Bags, Queues, and Stacks
APIs
Arithmetic expression evaluation
Resizing arrays
Iterators
Linked lists
1.4 Analysis of Algorithms
Running time
Order-of-growth classifications
1.5 Case Study: Union–Find
Dynamic connectivity
Quick find
Quick union
Weighted quick union
2. Sorting
2.1 Elementary Sorts
Rules of the game
Selection sort
Insertion sort
Shellsort
2.2 Mergesort
Abstract in-place merge
Top-down mergesort
Bottom-up mergesort
2.3 Quicksort
2.4 Priority Queues
Priority queue API
Elementary implementations
Binary heap
Heapsort
2.5 Applications
Comparators
Stability
Median and order statistics
3. Searching
3.1 Symbol Tables
Symbol table API
Ordered symbol table API
Sequential search
Binary search
3.2 Binary Search Trees
Basic implementation
Order-based methods
Deletion
3.3 Balanced Search Trees
2-3 search trees
Red–black BSTs
Deletion
3.4 Hash Tables
Hash functions
Separate chaining
Linear probing
3.5 Applications
Set data type
Whitelist and blacklist filters
Dictionary lookup
Inverted index
File indexing
Sparse matrix-vector multiplication
4. Graphs
4.1 Undirected Graphs
Glossary
Undirected graph type
Adjacency-lists representation
Depth-first search
Breadth-first search
Connected components
Degrees of separation
4.2 Directed Graphs
Glossary
Digraph data type
Depth-first search
Strong connectivity
Kosaraju–Sharir algorithm
Transitive closure
4.3 Minimum Spanning Trees
Cut property
Greedy algorithm
Edge-weighted graph data type
Prim's algorithm
Kruskal's algorithm
4.4 Shortest Paths
Properties of shortest paths
Edge-weighted digraph data types
Generic shortest paths algorithm
Dijkstra's algorithm
Shortest paths in edgeweighted DAGs
Critical-path method
Bellman–Ford algorithm
Negative cycle detection
Arbitrage
5. Strings
5.1 String Sorts
Key-indexed counting
LSD string sort
MSD string sort
3-way string quicksort
5.2 Tries
String symbol table API
R-way tries
Ternary search tries
5.3 Substring Search
Brute–force algorithm
Knuth–Morris–Pratt algorithm
Boyer–Moore algorithm
Rabin-Karp fingerprint algorithm
5.4 Regular Expressions
Describing patterns with REs
Applications
Nondeterministic finite-state automata
Simulating an NFA
Building an NFA corresponding to an RE
5.5 Data Compression
Rules of the game
Reading and writing binary data
Limitations
Run-length coding
Huffman compression
LZW compression
6. Context
Event-Driven Simulation
Hard-disc model
Collision prediction
Collision resolution
B-trees
Cost model
Search and insert
Suffix Arrays
Suffix sorting
Network Flow
Ford–Fulkerson algorithm
Reductions
Sorting
Shortest path
Bipartite matching
Linear programming
Intractability
Longest-paths problem
Boolean satisfiability
NP-completeness
Index
A
B
C
D
E
F
G
H
I
J
K
L
M
N
O
P
Q
R
S
T
U
V
W
Z
Algorithms and Clients