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This approach involves simulating the game as described. In each round, compare the first two elements. The larger element stays at the front, while the smaller one is moved to the end. Track the number of consecutive wins for the current maximum element. The game terminates once an element wins k consecutive games, or we can conclude the maximum element will always win once it has dominated for enough rounds due to its magnitude relative to other elements.
Time Complexity: O(n) where n is the length of the array.
Space Complexity: O(1) as we use only constant space.
1#include <vector>
2#include <iostream>
3using namespace std;
4
5int getWinner(vector<int>& arr, int k) {
6 int max = arr[0];
7 int win_count = 0;
8 for (size_t i = 1; i < arr.size(); ++i) {
9 if (max > arr[i]) {
10 ++win_count;
11 } else {
12 max = arr[i];
13 win_count = 1;
14 }
15 if (win_count == k)
16 return max;
17 }
18 return max;
19}
20
21int main() {
22 vector<int> arr{2, 1, 3, 5, 4, 6, 7};
23 int k = 2;
24 cout << "Winner: " << getWinner(arr, k) << endl;
25 return 0;
26}The algorithm is similar to the C solution but utilizes C++'s vector container. It iterates over the elements, updates the current maximum and its consecutive win count, and stops when a maximum wins k times consecutively, returning this as the winner.
This variant uses a concept very similar to the simulation approach but adds a breaking condition for improved efficiency. It exploits the game's characteristics by noting if the current maximum wins continuously even before counting to k, it will naturally reach the conclusion. This allows early termination if the maximum element becomes apparent quickly.
Time Complexity: O(n), potentially terminating faster.
Space Complexity: O(1).
1
By utilizing JavaScript for enhancement, the iteration notices early exits based on infeasibility of alteration, effectively trimming cycles when a conclusion appears avowed.