Roaaemaduldin

This package include some of the content of "Algorithms Analysis and Design" Course. In this package, you will find a detailed explanation of "Greedy Algorithms", "Dynamic Programming", "Hashing", a simple summary of "Red-Black Tree Insertion and Deletion" and some examples on how to find the "Recurrence Relations" of some algorithms.

This document summarizes the steps to be implemented that are needed when inserting a new element into the tree or deleting an existing element from the tree.

This document provides some examples and their solutions for analyzing algorithms and deducing their recurrence relations.

This document provides an explanation of the definition of HASHING, how to use it, some of its types and how to avoid COLLISION that may occur due to using some hash functions.

Hashing is a way of storing the data in more efficient way that needs less space or memory according to the hash function used. This document explains what is meant by hashing, how it is implemented and provides a summary of some types of hashing with illustrating.

A greedy algorithm is an algorithmic strategy that makes the optimal choice at each small stage (subproblem), with the goal of eventually leading to globally optimum solution. This document explains the definition of a greedy algorithm, the difference between greedy algorithm and dynamic programming and it provides a explanation of some greedy algorithms as Huffman Encoding, Minimum Spanning Tree (MST) and its different algorithms, graph review and Shortest-Path algorithm.

Dynamic Programming is a computer technique where an algorithmic problem is first broken down into subproblems, the results are saved and then the subproblems are optimized to find the overall solution. This document describes and explains the definition of dynamic programming, the main idea it is based on, where to use it, how to use it and provides multiple examples with simple explanation.