#2974

Easy

LeetCode Problem Workspace

Minimum Number Game

The Minimum Number Game involves simulating moves by Alice and Bob on an array, sorting elements and appending them to a new array in alternating turns.

array sorting heap priority queue simulation

Problem Statement

You are given an even-length integer array nums. Alice and Bob play a game where they take turns removing and appending elements from nums to a new array arr. Alice always removes the smallest available number, and Bob removes the next smallest. After removing, they append their picks to arr in the order they removed the numbers.

Your task is to return the array arr after all the rounds. Each round consists of Alice removing and appending the smallest element, followed by Bob removing and appending the next smallest element, until all elements are removed.

Examples

Example 1

Input: nums = [5,4,2,3]

Output: [3,2,5,4]

In round one, first Alice removes 2 and then Bob removes 3. Then in arr firstly Bob appends 3 and then Alice appends 2. So arr = [3,2]. At the begining of round two, nums = [5,4]. Now, first Alice removes 4 and then Bob removes 5. Then both append in arr which becomes [3,2,5,4].

Example 2

Input: nums = [2,5]

Output: [5,2]

In round one, first Alice removes 2 and then Bob removes 5. Then in arr firstly Bob appends and then Alice appends. So arr = [5,2].

Constraints

2 <= nums.length <= 100
1 <= nums[i] <= 100
nums.length % 2 == 0

Solution Approach

Sorting the Array

Sort the array nums in increasing order before starting the game. This ensures that the smallest numbers are picked first by Alice, followed by the next smallest picked by Bob.

Simulating the Turns

After sorting, simulate the game by alternating between Alice and Bob. Alice picks the smallest remaining number, and Bob picks the next smallest. Append their selections to the result array arr in the order they picked.

Efficient Solution with Heap

To optimize, use a min-heap or priority queue to efficiently get the smallest elements during each turn. This reduces the need to sort repeatedly during the game simulation.

Complexity Analysis

Metric	Value
Time	Depends on the final approach
Space	Depends on the final approach

The time complexity depends on the sorting step, which is O(n log n) where n is the length of the array. Using a heap for the simulation can reduce the complexity for picking elements to O(log n) per operation. Overall, the approach remains efficient within the problem's constraints.

What Interviewers Usually Probe

Ensure the candidate uses sorting as a first step to solve the problem.
Look for the candidate's understanding of simulation and alternating turns.
Check if the candidate can optimize using heaps or priority queues.

Common Pitfalls or Variants

Common pitfalls

Forgetting to sort the array before simulating the game, which leads to incorrect answers.
Improper simulation of the turns, such as not appending the elements in the correct order.
Not using efficient data structures like heaps, resulting in higher time complexity.

Follow-up variants

Modify the problem to have Alice and Bob pick elements based on a different rule, such as alternating picks instead of smallest-first.
Change the number of players and adjust the game mechanics accordingly.
Introduce a condition where players can pick from a specific range of numbers rather than from the entire sorted array.

FAQ

What is the best approach for solving the Minimum Number Game?

Sorting the array initially and then simulating the turns with alternating picks between Alice and Bob is the best approach. Optionally, use heaps for optimization.

How do I handle the game simulation in the Minimum Number Game?

You simulate the game by alternating between Alice and Bob, where Alice always picks the smallest remaining number and Bob picks the next smallest.

What data structure should I use to optimize the solution for the Minimum Number Game?

Using a heap (priority queue) allows efficient removal of the smallest elements during each turn, reducing the time complexity of picking elements.

How do I ensure the correct order of elements in the result array for the Minimum Number Game?

After sorting the array, append Alice's and Bob's selections to the result array in the order they picked them during the game simulation.

What are the time and space complexities of the Minimum Number Game solution?

The time complexity is O(n log n) for sorting, with additional complexity for heap operations if used. The space complexity depends on the data structure used for simulation, typically O(n).

terminal

Solution

Solution 1: Simulation + Priority Queue (Min Heap)

We can put the elements of the array $\textit{nums}$ into a min heap one by one. Each time, we take out two elements $a$ and $b$ from the min heap, and then sequentially put $b$ and $a$ into the answer array until the min heap is empty.

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class Solution:
    def numberGame(self, nums: List[int]) -> List[int]:
        heapify(nums)
        ans = []
        while nums:
            a, b = heappop(nums), heappop(nums)
            ans.append(b)
            ans.append(a)
        return ans

Solution 2: Sorting + Swapping

We can sort the array $\textit{nums}$, and then iterate through the array, swapping adjacent elements each time until the iteration is complete, and return the swapped array.

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class Solution:
    def numberGame(self, nums: List[int]) -> List[int]:
        heapify(nums)
        ans = []
        while nums:
            a, b = heappop(nums), heappop(nums)
            ans.append(b)
            ans.append(a)
        return ans

Continue Practicing

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