Introduction

the aim of this book, Algorithms in C by R. Sedgewick, is to give a solid introduction to several fields which are in the core of computer science, and other ones that are more specialized and advanced ones.

Fundamental Algorithms [5/9]

This part is just a setup of the required stuff in upcoming chapters, this includes:

• [X] Key-features of the C Programming Language
• [X] Arrays
• [X] Linked Lists
• [X] Stacks
• [X] Queues
• [ ] Trees
• [ ] Recursion
• [ ] Analysis of Algorithms
• [ ] Implementation of Algorithms

Sorting Algorithms [0/3]

Sorting is based on rearranging things in a particular order, which is a fundamental problem in Computer Science. Although, some of these is the basis of other ones in further chapters, so basic ones are based on:

• [ ] Priority-Queues Sorts
• [ ] Selection Sorts
• [ ] Merging Sorts

Searching Algorithms [0/6]

Searching has a fundamental importance. It’s aim is to find something in side a set of things. advanced search methods are based on trees and digital key

• [ ] Binary-Search Trees
• [ ] Balanced Trees
• [ ] Hashing
• [ ] Digital Search Trees and Tries
• [ ] Methods for very large files
• [ ] Analysis of similarities between methods

String Processing Algorithms [0/3]

String is usually a sequence, a long sequence, of characters, which are another fundamental data-type.

• [ ] Pattern matching
• [ ] File Compression
• [ ] Cryptology

Geometric Algorithms [0/5]

Geometry has to do with points and lines, or other simple geometric objects.

• [ ] Finding the convex hull of a set o points
• [ ] Intersection among geometric objects
• [ ] Closest Point Problems
• [ ] Multidimensional Searching
• [ ] Integration with other search and sort algorithms

Graph Algorithms [0/4]

Graphs are a real important domain in mathematics and indeed Computer Science. Graph algorithms are based om fundamental connectivity problems, and solved using just the same data structures developed earlier.

• [ ] Shortest path
• [ ] Minimum Spinning Tree
• [ ] Network Flow
• [ ] Matching

Mathematical Algorithms [0/4]

This covers arithmetic and numerical analysis, polynomials and matrices, and use that knowledge to solve problems like

• [ ] Random Number Generation
• [ ] Simultaneous equations
• [ ] Data fitting?
• [ ] Integration?

Advanced Algorithms [0/5]

This is like the glue to all of the book algorithms.

• [ ] Special-purpose hardware
• [ ] Dynamic Programming
• [ ] Linear Programming
• [ ] Exhaustive search
• [ ] NP-completeness