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Grokking the Coding Interview Patterns in Python

Solution: Triangle

Understand how to apply dynamic programming to find the minimum path sum in a triangle array. Learn the bottom-up approach that optimizes overlapping subproblems and achieves efficient computation with O(n²) time and O(n) space complexity.

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Statement

Given an array, triangle, return the minimum path sum from top to bottom.

You may move to an adjacent number in the row below at each step. More formally, if you are at index ii in the current row, you may move to either index ii or index i+1i + 1 in the next row.

Constraints:

  • 1≤1 \leq triangle.length ...