This is a compilation about all topics related with the Algorithms that I'm learning everyday
Description | URL |
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JS Bin | http://jsbin.com/tutacox/edit?js,console |
JS Play Ground | https://stephengrider.github.io/JSPlaygrounds/ |
Stack Blitz | https://stackblitz.com/ |
Code Pen | https://codepen.io/ |
GreatFrontend | https://www.greatfrontend.com/ |
Description | URL |
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Code fast and code well with JavaScript | http://www.codewars.com/ |
Try to solve many problems using JavaScript | https://coderbyte.com/ |
Solve challenges online using JavaScript | https://www.codingame.com/start |
CodeFights with JavaScript become in a Hero | https://codefights.com/ |
Formulas for combinatory | http://www.vitutor.com/pro/1/a_f.html |
HackerRank one of the best pages for challenges | https://www.hackerrank.com |
Exercism | http://exercism.io/ |
Code Chef | https://www.codechef.com/wiki/tutorials |
LeetCode is the best platform to help you enhance your skill | https://leetcode.com/ |
LeetCode solutions explained | https://jeantimex.gitbooks.io/solve-leetcode-problems/content/ |
LeetCode solutions in Java | https://legacy.gitbook.com/book/tenderleo/leetcode-solutions-/details |
Platform to take coding test for companies | https://app.codility.com/programmers/ |
Freecode Camp | https://www.freecodecamp.org/learn |
Description | URL |
---|---|
Data Structures explained | https://medium.freecodecamp.org/10-common-data-structures-explained-with-videos-exercises-aaff6c06fb2b |
Big O Cheat Sheet | https://www.bigocheatsheet.com/ |
Algorithms Visualization | https://www.cs.usfca.edu/~galles/visualization/Algorithms.html |
Big O Array JavaScript | https://dev.to/lukocastillo/time-complexity-big-0-for-javascript-array-methods-and-examples-mlg |
Complexity | Notation | Description |
---|---|---|
Constant Time | 1 | No matter how many elements we're working with, the algorithm/operation/whatever will always take the same amount of time |
Logarithmic Time | log(n) | You have this if doubling the number of elements you are iterating over doesn't double the amount of work. Always assume that searching operations are log(n) |
Linear Time | n | Iterating through all elements in a collecion of data. If you see a foor loop spanning from 0 to array.length, you probably have 'n' or linear runtime |
Quasilinear Time | n * log(n) | You have this if doubling the number of elements you are iterating over doesnt's the amount of work. Always assume that any sorting operation is n * log(n) |
Quadratic Time | 2 ^ n | Every element in a collection has to be compared to every other element. The 'handshake problem' |
Exponential Time | n ^ 2 | If you add a 'single' element to a collection, the processing power requires doubles |
- Because I love the time and time is gold, that's why I've decided to use Intellij as my favorite IDE. Here I will put some useful links in order to optimize the time coding.
Description | URL |
---|---|
Basics in Intellij | https://www.jetbrains.com/help/idea/discover-intellij-idea.html |
Pro Tips in Intellij | https://www.jetbrains.com/help/idea/intellij-idea-pro-tips.html |
IntelliJ Course | https://javaspecialists.teachable.com/p/intellij-wizardry |
I have studied these contents from the next resources: