Is Valid Elements in an Array easy or hard?

The problem is generally classified as Easy because the logic relies on basic array traversal and preprocessing. Once you recognize the prefix maximum and suffix minimum pattern, the implementation becomes straightforward with linear time complexity.

Valid Elements in an Array Python/Java solution

Implement the O(n) solution by first computing a suffix minimum array, then scanning from left to right while maintaining the maximum value so far. At each index, check whether the current element lies strictly between the prefix maximum and suffix minimum. The same logic works in Python, Java, and C++ with simple loops.

How to solve Valid Elements in an Array in O(n)?

Precompute a suffix minimum array where each position stores the smallest value to its right. Traverse the array from left to right while maintaining the maximum value seen so far. For each element, check if prefixMax < arr[i] < suffixMin[i+1]. This ensures the element satisfies both constraints in constant time per index.

What is the best approach for Valid Elements in an Array?

The most efficient approach uses prefix maximum and suffix minimum preprocessing. Compute the maximum value to the left of every index and the minimum value to the right. An element is valid if it is greater than the left maximum and smaller than the right minimum. This runs in O(n) time with O(n) extra space.

Is Valid Elements in an Array asked at Google/Amazon/Meta?

Problems involving prefix maximum and suffix minimum preprocessing appear frequently in interviews at large tech companies including Google and Amazon. The exact problem title may vary, but the pattern of validating elements based on left and right constraints is a common array interview concept.

What data structure is used in Valid Elements in an Array?

The problem mainly uses arrays for prefix and suffix preprocessing. A suffix minimum array stores the smallest value to the right of each index, while a running variable or prefix array tracks the maximum value seen on the left side.

What is the time complexity of Valid Elements in an Array?

The optimal solution runs in O(n) time because it processes the array in a few linear passes. One pass builds the suffix minimum array, another tracks prefix maximum values while checking validity. The brute force approach takes O(n^2) time due to repeated left and right scans.

3912. Valid Elements in an Array - Practice Online

Q: What is the best approach for Valid Elements in an Array?

The most efficient approach uses prefix maximum and suffix minimum preprocessing. Compute the maximum value to the left of every index and the minimum value to the right. An element is valid if it is greater than the left maximum and smaller than the right minimum. This runs in O(n) time with O(n) extra space.

Q: Is Valid Elements in an Array asked at Google/Amazon/Meta?

Problems involving prefix maximum and suffix minimum preprocessing appear frequently in interviews at large tech companies including Google and Amazon. The exact problem title may vary, but the pattern of validating elements based on left and right constraints is a common array interview concept.

Q: What data structure is used in Valid Elements in an Array?

The problem mainly uses arrays for prefix and suffix preprocessing. A suffix minimum array stores the smallest value to the right of each index, while a running variable or prefix array tracks the maximum value seen on the left side.

Q: What is the time complexity of Valid Elements in an Array?

The optimal solution runs in O(n) time because it processes the array in a few linear passes. One pass builds the suffix minimum array, another tracks prefix maximum values while checking validity. The brute force approach takes O(n^2) time due to repeated left and right scans.

You are given an integer array nums.

An element nums[i] is considered valid if it satisfies at least one of the following conditions:

It is strictly greater than every element to its left.
It is strictly greater than every element to its right.

The first and last elements are always valid.

Return an array of all valid elements in the same order as they appear in nums.

Example 1:

Input: nums = [1,2,4,2,3,2]

Output: [1,2,4,3,2]

Explanation:

nums[0] and nums[5] are always valid.
nums[1] and nums[2] are strictly greater than every element to their left.
nums[4] is strictly greater than every element to its right.
Thus, the answer is [1, 2, 4, 3, 2].

Example 2:

Input: nums = [5,5,5,5]

Output: [5,5]

Explanation:

The first and last elements are always valid.
No other elements are strictly greater than all elements to their left or to their right.
Thus, the answer is [5, 5].

Example 3:

Input: nums = [1]

Output: [1]

Explanation:

Since there is only one element, it is always valid. Thus, the answer is [1].

Constraints:

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