https://github.com/danielbatres/algorithmic-complexity-javascript
This project is aimed at learning about algorithmic complexity with JavaScript, to assess algorithms using Big O notation and considering both time complexity and space complexity.
https://github.com/danielbatres/algorithmic-complexity-javascript
algorithm-analysis algorithms big-o big-o-notation complexity javascript nodejs
Last synced: 10 months ago
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This project is aimed at learning about algorithmic complexity with JavaScript, to assess algorithms using Big O notation and considering both time complexity and space complexity.
- Host: GitHub
- URL: https://github.com/danielbatres/algorithmic-complexity-javascript
- Owner: danielbatres
- License: mit
- Created: 2023-10-17T02:34:13.000Z (about 2 years ago)
- Default Branch: main
- Last Pushed: 2023-10-18T17:22:58.000Z (about 2 years ago)
- Last Synced: 2025-01-19T00:00:10.053Z (11 months ago)
- Topics: algorithm-analysis, algorithms, big-o, big-o-notation, complexity, javascript, nodejs
- Language: JavaScript
- Homepage:
- Size: 7.81 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Algorithmic complexity with JavaScript and Big O notation
## Algorithmic Complexity Evaluation with JavaScript
This project focuses on the evaluation of time and space complexity of algorithms using Big O notation, and employs a concise and simplified evaluation approach.
### Evaluation Methods
JavaScript is used to perform the evaluations, making use of the following functions:
- `console.time()`
- `console.timeEnd()`
- `performance.now()`
These functions assist in measuring the execution time of algorithms. It's important to note that the data obtained may not be entirely precise, but they offer a practical way to estimate algorithm performance.