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Grokking the Coding Interview Patterns in Go

Solution: Triangle

Explore how to solve the minimum path sum problem in a triangular array using dynamic programming. Understand the bottom-up approach that calculates optimal path costs from the base to the top by iteratively updating a one-dimensional array. Gain insights into the time and space complexity of this efficient solution.

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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 ...