Data structures and Algorithms in Javascript
- O(1) Constant- no loops
- O(log N) Logarithmic- usually searching algorithms have log n if they are sorted (Binary Search)
- O(n) Linear- for loops, while loops through n items
- O(n log(n)) Log Liniear- usually sorting operations
- O(n^2) Quadratic- every element in a collection needs to be compared to ever other element. Two nested loops
- O(2^n) Exponential- recursive algorithms that solves a problem of size N
- O(n!) Factorial- you are adding a loop for every element
- Iterating through half a collection is still O(n)
- Two separate collections: O(a + b)
- Two nested collections: O(a * b)
- Operations (+, -, *, /)
- Comparisons (<, >, ==)
- Looping (for, while)
- Outside Function call (function())
- Rule 1: Always worst Case
- Rule 2: Remove Constants
- Rule 3: Different inputs should have different variables. O(a+b). A and B arrays nested would be O(a*b).
- Rule 4: Drop Non-dominant terms
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Variables
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Data Structures
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Function Call
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Allocations
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Big-O Complexity Chart
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Common Data Structure Operations
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Array Sorting Algorithms
