This is a respository of potential data structures and algorithms and their implementations in multiple programming languages. This was created to be a resource for anyone learning computer science, preparing for a job interview, or just for educational purposes for those that are curious. Over time, I hope this will be an excellent resource for those that need to learn this information. If you have something to add to this repository please feel free to contribute.
You should be able to see multiple languages in this repository as it becomes fleshed out in further detail. Such programming languages that this repository will include the following:
- C
- C++
- C#
- Python
- JavaScript
Data Structures and Algorithms are two of the most fundamental concepts in computer science. They form the building blocks for creating efficient software systems and are critical for optimizing performance and solving complex computational problems.
A data structure is a way of organizing data in a computer's memory to facilitate efficient access and manipulation. Some of the most common data structures include arrays, linked lists, stacks, queues, trees, and graphs. Each of these structures has its own unique properties and use cases, and the choice of data structure depends on the specific requirements of the problem being solved.
Algorithms, on the other hand, are step-by-step procedures for solving a problem or performing a task. An algorithm takes inputs, processes them, and produces an output. A good algorithm should be correct, efficient, and have a well-defined set of inputs and outputs.
When designing algorithms, it is important to consider both time and space complexity. Time complexity refers to the amount of time an algorithm takes to run, while space complexity refers to the amount of memory used by an algorithm. A good algorithm should have a low time and space complexity.
One of the most important concepts in algorithms is the idea of a sorting algorithm. Sorting algorithms are used to arrange data in a particular order, such as ascending or descending. Some common sorting algorithms include bubble sort, insertion sort, selection sort, merge sort, and quick sort. Each of these algorithms has its own strengths and weaknesses, and the choice of sorting algorithm depends on the specific requirements of the problem being solved.
Another important concept in algorithms is searching. Searching algorithms are used to find a particular item in a collection of data. Some common searching algorithms include linear search and binary search. Linear search is a simple technique that searches for an item by checking each item in the collection one by one, while binary search is a more efficient algorithm that takes advantage of the sorted nature of the data to quickly find the item being searched for.
Data Structures and Algorithms form the foundation of computer science. Understanding these concepts is crucial for developing efficient and effective software systems. Whether you are a computer science student or a professional software developer, having a solid understanding of data structures and algorithms is an essential part of your skillset.
Further, more programming languages will be added as I become more familiar with them and have the resources to handle them.
The manner of which these code examples are organized is a work in progress, however, here is a small outline of what is contained in this repository.
- Array Manipulation Algorithms
- Binary Search Algorithms
- Hash Tables
- Data Structures
- Linked List
- Image Processing
- Mathematics Algorithms
- Miscelleanous
- Sets
- String Manipulation Algorithms
As well, these algorithms or questions do not come from any one external source. While some may be inspired by what I find on the Internet many of these questions will be either widely known accepted questions or sufficently unique as they are modified from other sources.