Data Structures and Algorithms

Big O notation:

- Worst case execution complexity

O(1) : access the data at first lookup

O(n) : lookup a data in a list of n items (linear complexity).

O(n^2): nested loops(2loops)

O(n!) : loop for each item in the list of data

- Space complexity

Good code:

- Readable

- Scalable (speed and Memory)

For Quick Overview : https://drive.google.com/drive/folders/1t75vJEgzndUVp_Jndh9O7tPN9xTu5s57?usp=sharing

For Distributed design : http://book.mixu.net/distsys/intro.html

Google Interview Prep Requirements : http://steve-yegge.blogspot.com/2008/03/get-that-job-at-google.html

P-NP readings : https://www.quora.com/How-do-you-explain-NP-Complete-and-NP-hard-to-a-child and https://stackoverflow.com/questions/1857244/what-are-the-differences-between-np-np-complete-and-np-hard