An Illustrative Introduction to Algorithms


An Illustrative
Introduction to Algorithms
Authors: Dino Cajic
ISBN-10 书号: 1686863268
ISBN-13 书号: 9781686863264
Publisher Finelybook 出版日期: 2019-08-16
pages 页数: 363 pages


Book Description
This book was written to fill the gap that exists when Computer Science students,and programmers,attempt to learn and analyze the different algorithms that currently exist. I took a course on Algorithms and was disappointed in the type of material that’s currently available. There are two types of books that I kept running into: 1). First,the overly complex book. This book seems like it’s designed for people that are already fluent in the topics and wanted a more detailed and mathematical approach to algorithms. 2). Second,the overly simple book. A basic introduction to algorithms. This is a high-level overview of some algorithms,and most complex algorithms are not mentioned. After completion,the person is still incapable of showing how the algorithm runs when a problem is presented. This book is designed for undergraduate upper-class students and programmers that want to expand their horizon. It can be used as a supplementary book alongside the complex book. Readers will gain the knowledge necessary to solve those mathematically intensive algorithmic problems that were presented in the complex book.Each chapter consists of a brief description of how the algorithm works followed by a detailed example or two. No steps are skipped during the traversal process. The reader is presented with a clear,simplified approach to solving the algorithm that the chapter is dedicated to. Each chapter follows a natural progression from the previous chapter. If certain algorithms rely heavily on prior knowledge,the previous chapter covers that topic. For example,Kruskal’s algorithm relies heavily on prior knowledge of Minimum Spanning Trees and Greedy Algorithms. Each of those topics receives a chapter of its own.
Chapter 0: Introduction
Chapter 1: Big O Complexity
Chapter 2: Lower Bounds
Chapter 3: Master Theorem
Chapter 4: Bubble Sort
Chapter 5: Insertion Sort
Chapter 6: Divide and Conquer
Chapter 7: Merge Sort
Chapter 8: Quick Sort
Chapter 9: Heap Data Structure
Chapter 10: Heap Sort
Chapter 11: Selection Sort
Chapter 12: Adjacency Matrix
Chapter 13: Adjacency List
Chapter 14: Edge List
Chapter 15: Depth First Search (DFS)
Chapter 16: Topological Sorting
Chapter 17: Breadth First Search(BFS)
Chapter 18: Greedy Algorithms
Chapter 19: Minimum Spanning Trees(MST)
Chapter 20: Kruskal's Algorithm
Chapter 21: Prim's Algorithm
Chapter 22: Binary Tree Traversal-Depth First-In Order
Chapter 23: Binary Tree Insertion/Deletion
Chapter 24: Planar Graphs
Chapter 25: Dynamic Programming: Longest Common Subsequence
Chapter 26: All-Pairs Shortest Path Matrix Multiplication
Chapter 27: All-Pairs Shortest Path Matrix Multiplication (Floyd-Warshall)
Chapter 28: Dijkstra's Algorithm: Single Source Shortest Path
Chapter 29: Bellman-Ford
Chapter 30: Johnson's Algorithm
Chapter 31: Clockwise and Counterclockwise Line Segment Intersection
Chapter 32: Graham's Scan
Chapter 33: Closest Pair of Points on a Plane-Divide and Conquer
Chapter 34: Voronoi graph and Delaunay Triangulation
Chapter 35: Maximum Independent Set
Chapter 36: Minimum Vertex Cover
Chapter 37: Maximum Clique
References

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