Gain insights into connecting discrete mathematics with programming. Explore variables, expressions, data structures, and algorithm design to enhance your problem-solving and implementation skills.

Discrete Mathematical Algorithms and Data Structures-02-02.png

momoexp4.tar.gz

java and C++

OnlyPython

OnlyJava

OnlyCplusplus

OnlyC

JavaLang3

Discrete mathematics is the basis of several popular algorithms. This course shows the discreteness of data structures and algorithms. It can benefit programmers with a non-CS background looking to strengthen their foundations by connecting theoretical concepts with practical programming scenarios.

The course starts with discussing relating discrete mathematics with algorithms and data structures. You will have examples demonstrating variables, conditional expressions, and arrays as basic building blocks of programming. Then, you will use classes and objects to define and implement linear data structures. You will also learn about the binary tree traversals and templates and the topics of time complexity, set difference, and rearranging the values in a string.

By the end of the course, you will have a strong grasp of algorithm design, data structure implementation, and overall problem-solving.

Programming Discrete Math Concepts for Beginners

# The preorder traversal method
Preorder tree traversal is very useful and efficient for copying tree-like data structures. To perform preorder tree traversal, we use a method like `preOrder()` that will take the node object as a parameter and call itself.

# Iterative preorder traversal

Let’s look at an iterative preorder tree traversal code snippet, which will give us a clear picture of how we can implement our algorithm. This shows how we can traverse the tree without recursion. 

We start spanning the tree with the root node; after that, we visit the left subtree, and next, we visit the right subtree. Each subtree is also visited in the preorder way. That means it starts from the root of the subtree and then goes to the left subtree, and the process continues until we reach a leaf node.




The traversal pattern clearly tells us that this tree traversal is a good candidate for recursion. After visiting the root node, we can recursively visit the left subtree and then visit the right subtree again.

Still, recursion is not the only way. We can also do the traversal using iteration. The following code snippet shows how:

 Learn more about preorder traversal and how to code it iteratively and recursively.


Course Introduction

Programming Language and Boolean Algebra

Logical Expressions and Algorithms

Arrays and Discrete Mathematics

Classes, Objects, and Methods

Linear Data Structures

Tree, Algorithms, and Templates

Time Complexity

Propositional Logic

Combinatorics

Wrapping Up

Solving Sudoku and the 8-Queens Puzzle as Constraint Satisfaction

Preorder Traversal