Find the Power of K-Size Subarrays I

Find the Power of K-Size Subarrays I

1. What is this problem about?

The Find the Power of K-Size Subarrays I interview question involves evaluating specific segments of an array. The "power" of a subarray of size $k$ is defined as its maximum element IF the elements are consecutive and sorted in ascending order. If the subarray is not consecutive or not sorted, its power is -1. Your task is to return an array of power values for all contiguous subarrays of length $k$.

2. Why is this asked in interviews?

Companies like Meta and Bloomberg ask the Find the Power of K-Size Subarrays I coding problem to test a candidate's proficiency with Sliding Window interview patterns. It evaluates whether you can maintain a property (consecutiveness) efficiently as the window moves across the array, rather than re-checking the entire window from scratch at every step.

3. Algorithmic pattern used

This problem is solved using the Sliding Window pattern with a Counter.

• Consecutive Check: Maintain a counter of "how many adjacent elements are consecutive so far."
• Logic: Two elements nums[i-1] and nums[i] are consecutive if nums[i] == nums[i-1] + 1.
• Window Property: A window of size $k$ is valid if it contains $k-1$ consecutive pairs.
• Linear Scan: Traverse the array. Every time you find a consecutive pair, increment the counter. If not, reset it. If the counter is $\geq k-1$, the current window ending at $i$ is valid, and its power is nums[i].

4. Example explanation

Array: [1, 2, 3, 5, 6], $k = 3$.

• index 0-2: [1, 2, 3]. Sorted and consecutive. Power = 3.
• index 1-3: [2, 3, 5]. 3 and 5 are not consecutive. Power = -1.
• index 2-4: [3, 5, 6]. 3 and 5 are not consecutive. Power = -1. Result: [3, -1, -1].

5. Common mistakes candidates make

• $O(N \cdot K)$ Brute Force: Checking every window of size $k$ independently. While okay for small $k$, it's not optimal.
• Incorrect "Consecutive" definition: Missing the requirement that the values must increase exactly by 1.
• Off-by-one: Mistakes in resetting the consecutive counter when a gap is found.

6. Interview preparation tip

Practice using "Running Count" optimizations. Many sliding window problems that look for a specific sequence property can be solved by tracking the number of valid "links" or "pairs" currently inside the window. This is a core Array interview pattern.