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Algorithm Design and Analysis
There are both practical and theoretical reasons to study algorithms. From a practical standpoint, you have to know a standard set of important algorithms from different areas of computing; in addition, you should be able to design new algorithms and analyze their efficiency. From the theoretical standpoint, the study of algorithms, sometimes called algorithmics, has come to be as the cornerstone of computer science.
- Author
- Godfry Justo
- Publisher
- African Virtual University
- Source
- LibreTexts
- License
- CC BY-SA
- Language
- EN
- Category
- Information Technology
Contents· 20 sections
- 01: Fundamental Design and Analysis Techniques
- 1.01: Activity 1 - Overview of Algorithm Design and Analysis
- 1.02: Activity 2 - Recursion and Recursive Backtracking
- 1.03: Activity 3 - Dynamic Programming
- 1.04: Unit Summary
- 02: Searching Binary Search Trees and Heaps
- 2.01: Activity 1 - Searching Techniques
- 2.02: Activity 2 - Binary Search Tree
- 2.03: Activity 3 - Heaps
- 2.04: Unit Summary
- 03: Sorting Algorithms
- 3.01: Activity 1 - Sorting Algorithms by insertion method
- 3.02: Activity 2 - Sorting Algorithms by selection method
- 3.03: Activity 3 - Sorting Algorithms by Merge and Partition methods
- 3.04: Unit Summary
- 04: Hash Tables Graphs and Graph Algorithms
- 4.01: Activity 1 - Hash Tables
- 4.02: Activity 2 - Graphs
- 4.03: Activity 3 - Graph Algorithms
- 4.04: Unit Summary