Is Count Dominant Indices easy or hard?

Count Dominant Indices is typically classified as an Easy problem. The brute force approach is straightforward, and recognizing the reverse traversal optimization reduces the complexity to O(n). It mainly tests basic array traversal and observation of suffix properties.

Count Dominant Indices Python/Java solution

The implementation is identical across languages: iterate from the end of the array, track maxSoFar, and increment a counter whenever the current element exceeds it. FleetCode provides implementations in Python, Java, C++, Go, and TypeScript using the same O(n) reverse traversal logic.

How to solve Count Dominant Indices in O(n)?

Use reverse traversal. Start from the last element and maintain a variable maxSoFar that stores the maximum value encountered so far. If nums[i] is greater than maxSoFar, increment the dominant index count and update maxSoFar. This avoids repeatedly scanning the suffix of the array.

What is the best approach for Count Dominant Indices?

The optimal approach is reverse traversal with a running maximum. Traverse the array from right to left and keep track of the largest value seen so far. If the current element is greater than that maximum, it dominates all elements to its right. This method runs in O(n) time and O(1) space.

Is Count Dominant Indices asked at Google/Amazon/Meta?

Array scanning and suffix-maximum patterns frequently appear in interviews at companies like Amazon and Google. Variants of the 'array leaders' or dominant element problems test your ability to optimize from O(n²) enumeration to O(n) single-pass solutions.

What data structure is used in Count Dominant Indices?

The problem primarily uses arrays and simple variables. The optimized solution relies on maintaining a running maximum during reverse traversal rather than additional data structures such as heaps or hash maps.

What is the time complexity of Count Dominant Indices?

The optimal solution runs in O(n) time because the array is scanned once from right to left. Only constant-time comparisons and updates are performed for each element. Space complexity is O(1) since only a running maximum and a counter are stored.

3833. Count Dominant Indices - Practice Online

You are given an integer array nums of length n.

An element at index i is called dominant if: nums[i] > average(nums[i + 1], nums[i + 2], ..., nums[n - 1])

Your task is to count the number of indices i that are dominant.

The average of a set of numbers is the value obtained by adding all the numbers together and dividing the sum by the total number of numbers.

Note: The rightmost element of any array is not dominant.

Example 1:

Input: nums = [5,4,3]

Output: 2

Explanation:

At index i = 0, the value 5 is dominant as 5 > average(4, 3) = 3.5.
At index i = 1, the value 4 is dominant over the subarray [3].
Index i = 2 is not dominant as there are no elements to its right. Thus, the answer is 2.

Example 2:

Input: nums = [4,1,2]

Output: 1

Explanation:

At index i = 0, the value 4 is dominant over the subarray [1, 2].
At index i = 1, the value 1 is not dominant.
Index i = 2 is not dominant as there are no elements to its right. Thus, the answer is 1.

Constraints:

1 <= nums.length <= 100
1 <= nums[i] <= 100