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ZTM - Interview Prep (technical) - Coggle Diagram
ZTM - Interview Prep (technical)
Big O notation
Performance
performance.now()
The bigger how problem grows, how many more operations we need to do?
O(n)
Linear Time
The number of operations increases linearly with the inputs
Simplifying Big O
Worst case scenario
Remove constants
Different terms for inputs
Drop non dominants
O(n^2)
Quadratic time
The number of operations increase quadratically with the inputs
O(n!)
Adding a loop for each input element
What is good code
In detail
Scalable
Speed
Memory
Space complexity
Variables
Data Structures
Function Call
Allocations
Readable
3 pillars of good code
Readable
Time Complexity
Space Complexity
What we need to know
Data Structures
Arrays
Stacks
Queues
Linked Lists
Trees
Tries
Graphs
Hash Tables
Algorithms
Sorting
Dynamic Programming
BFS + DFS (Searching)
Recursion
Interview Cheat Sheet
Data Structures
How computers store data
Persistent and non-persistent storage
32 bits of memory
Integer overflow
Each data structure has advantages and disadvantages for the operations we want to do