Grokking Algorithm Complexity and Big-O
Ask Author
Back to course home

0% completed

Quadratic Space: O(n²)
Table of Contents

Contents are not accessible

Contents are not accessible

Contents are not accessible

Contents are not accessible

Contents are not accessible

Quadratic Space Complexity O(n^2) describes algorithms where the memory usage grows proportionally to the square of the input size. This type of complexity is common in dynamic programming (DP) problems that require a 2D table to store intermediate results, especially when solving problems involving grids or pairs.

Key Characteristics

In an algorithm with O(n^2) space complexity:

  • Memory usage grows with the square of the input size.
  • This is typical in algorithms that use a 2D array or matrix to store information for each pair of elements or each cell in a grid.

.....

.....

.....

Like the course? Get enrolled and start learning!

Table of Contents

Contents are not accessible

Contents are not accessible

Contents are not accessible

Contents are not accessible

Contents are not accessible