Algorithms and data structures - Info and Reading Options
the basic toolbox
By Kurt Mehlhorn
"Algorithms and data structures" was published by Springer in 2008 - Berlin, it has 300 pages and the language of the book is English.
“Algorithms and data structures” Metadata:
- Title: Algorithms and data structures
- Author: Kurt Mehlhorn
- Language: English
- Number of Pages: 300
- Publisher: Springer
- Publish Date: 2008
- Publish Location: Berlin
“Algorithms and data structures” Subjects and Themes:
- Subjects: ➤ Computer algorithms - Data structures (Computer science) - algorithms - data structures - graphs - hash tables - sorting - Data structures (computer science)
Edition Specifications:
- Format: Hardcover
- Pagination: xii, 300 p. :
Edition Identifiers:
- The Open Library ID: OL21897978M - OL6777805W
- Online Computer Library Center (OCLC) ID: 221217367
- Library of Congress Control Number (LCCN): 2008926816
- ISBN-13: 9783540779773 - 9783540779780
- All ISBNs: 9783540779773 - 9783540779780
AI-generated Review of “Algorithms and data structures”:
"Algorithms and data structures" Table Of Contents:
- 1- Appetizer: Integer Arithmetics
- 2- Addition
- 3- Multiplication: The School Method
- 4- Result Checking
- 5- A Recursive version of the School Method
- 6- Karatsuba Multiplication
- 7- Algorithm Engineering
- 8- The Programs
- 9- Proofs of Lemma 1.5 and Theorem 1.7
- 10- Implementation Notes
- 11- Historical Notes and Further Findings
- 12- Introduction
- 13- Asymptotic Notation
- 14- The Machine Model
- 15- Pseudocode
- 16- Designing Correct Algorithms and Programs
- 17- An Example - Binary Search
- 18- Basic Algorithm Analysis
- 19- Average-Case Analysis
- 20- Randomized Algorithms
- 21- Graphs
- 22- P and NP
- 23- Implementation Notes
- 24- Historical Notes and Further Findings
- 25- Representing Sequences by Arrays and Linked Lists
- 26- Linked Lists
- 27- Unbounded Arrays
- 28- *Amortized Analysis
- 29- Stacks and Queues
- 30- Lists Versus Arrays
- 31- Implementation Notes
- 32- Historical Notes and Further Findings
- 33- Hash Tables and Associative Arrays
- 34- Hashing and Chaining
- 35- Universal Hashing
- 36- Hashing with Linear Probing
- 37- Chaining Versus Linear Probing
- 38- *Perfect Hashing
- 39- Implementation Notes
- 40- Historical Notes and Further Findings
- 41- Sorting and Selection
- 42- Simple Sorters
- 43- Mergesort - an O(n log n) Sorting Algorithm
- 44- A Lower Bound
- 45- Quicksort
- 46- Selection
- 47- Breaking the Lower Bound
- 48- *External Sorting
- 49- Implementation Notes
- 50- Historical Notes and Further Findings
- 51- Priority Queues
- 52- Binary Heaps
- 53- Addressable Priority Queues
- 54- *External Memory
- 55- Implementation Notes
- 56- Historical Notes and Further Findings
- 57- Sorted Sequences
- 58- Binary Search Trees
- 59- (a, b)-Trees and Red-Black Trees
- 60- More Operations
- 61- Amortized Analysis of Update Operations
- 62- Augmented Search Trees
- 63- Implementation Notes
- 64- Historical Notes and Further Findings
- 65- Graph Representation
- 66- Unordered Edge Sequences
- 67- Adjacency Arrays - Static Graphs
- 68- Adjacency Lists - Dynamic Graphs
- 69- The Adjacency Matrix Representation
- 70- Implicit Representations
- 71- Implementation Notes
- 72- Historical Notes and Further Findings
- 73- Graph Traversal
- 74- Breadth-First Search
- 75- Depth-First Search
- 76- Implementation Notes
- 77- Historical Notes and Further Findings
- 78- Shortest Paths
- 79- From Basic Concepts to a Generic Algorithm
- 80- Directed Acyclic Graphs
- 81- Nonnegative Edge Costs (Dijkstra's Algorithm)
- 82- *Average-Case Analysis of Dijkstra's Algorithm
- 83- Monotone Integer Priority Queues
- 84- Arbitrary Edge Costs (Bellman-Ford Algorithm)
- 85- All-Pairs Shortest Paths and Node Potentials
- 86- Shortest-Path Queries
- 87- Implementation Notes
- 88- Historical Notes and Further Findings
- 89- Minimum Spanning Trees
- 90- Cut and Cycle Properties
- 91- The Jarnik-Prim Algorithm
- 92- Kruskal's Algorithm
- 93- The Union-Find Data Structure
- 94- *External Memory
- 95- Applications
- 96- Implementation Notes
- 97- Historical Notes and Further Findings
- 98- Generic Approaches to Optimization
- 99- Linear Programming - a Black-Box Solver
- 100- Greedy Algorithms - Never Look Back
- 101- Dynamic Programming - Building It Piece by Piece
- 102- Systematic Search - When in Doubt, Use Brute Force
- 103- Local Search - Think Globally, Act Locally
- 104- Evolutionary Algorithms
- 105- Implementation Notes
- 106- Historical Notes and Further Findings
- 107- Appendix
- 108- Mathematical Symbols
- 109- Mathematical Concepts
- 110- Basic Probability Theory
- 111- Useful Formulae
- 112- References
- 113- Index
"Algorithms and data structures" Description:
Open Data:
"This book is a concise introduction addressed to students and professionals familiar with programming and basic mathematical language. Individual chapters cover arrays and linked lists, hash tables and associative arrays, sorting and selection, priority queues, sorted sequences, graph representation, graph traversal, shortest paths, minimum spanning trees, and optimization. The algorithms are presented in a modern way, with explicitly formulated invariants, and comment on recent trends such as algorithm engineering, memory hierarchies, algorithm libraries and certifying algorithms. The authors use pictures, words and high-level pseudocode to explain the algorithms, and then they present more detail on efficient implementations using real programming languages like C++ and Java."--Jacket
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