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Leetcode #2139: Minimum Moves to Reach Target Score

In this guide, we solve Leetcode #2139 Minimum Moves to Reach Target Score in Python and focus on the core idea that makes the solution efficient.

You will see the intuition, the step-by-step method, and a clean Python implementation you can use in interviews.

Leetcode

Problem Statement

You are playing a game with integers. You start with the integer 1 and you want to reach the integer target.

Quick Facts

  • Difficulty: Medium
  • Premium: No
  • Tags: Greedy, Math

Intuition

A locally optimal choice leads to a globally optimal result for this structure.

That means we can commit to decisions as we scan without backtracking.

Approach

Sort or preprocess if needed, then repeatedly take the best available local choice.

Maintain the minimal state necessary to validate the greedy decision.

Steps:

  • Sort or preprocess as needed.
  • Iterate and pick the best local option.
  • Track the current solution.

Example

Input: target = 5, maxDoubles = 0 Output: 4 Explanation: Keep incrementing by 1 until you reach target.

Python Solution

class Solution: def minMoves(self, target: int, maxDoubles: int) -> int: if target == 1: return 0 if maxDoubles == 0: return target - 1 if target % 2 == 0 and maxDoubles: return 1 + self.minMoves(target >> 1, maxDoubles - 1) return 1 + self.minMoves(target - 1, maxDoubles)

Complexity

The time complexity is O(min⁡(log⁡target,maxDoubles))O(\min(\log target, maxDoubles))O(min(logtarget,maxDoubles)), and the space complexity is O(min⁡(log⁡target,maxDoubles))O(\min(\log target, maxDoubles))O(min(logtarget,maxDoubles)). The space complexity is O(min⁡(log⁡target,maxDoubles))O(\min(\log target, maxDoubles))O(min(logtarget,maxDoubles)).

Edge Cases and Pitfalls

Watch for boundary values, empty inputs, and duplicate values where applicable. If the problem involves ordering or constraints, confirm the invariant is preserved at every step.

Summary

This Python solution focuses on the essential structure of the problem and keeps the implementation interview-friendly while meeting the constraints.


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