Find the Longest Equal Subarray
A medium-tier problem at 36% community acceptance, tagged with Array, Hash Table, Binary Search. Reported in interviews at Palo Alto Networks and 1 others.
Find the Longest Equal Subarray is a medium-difficulty array problem with a 36% acceptance rate, asked at Palo Alto Networks and Meesho. You're hunting for the longest contiguous subarray where all elements are equal. Sounds simple until you hit the real constraint: you can remove at most k elements from the subarray and still count it as valid. That twist is what trips people. Most candidates either misread the problem entirely or lock into a brute-force approach that times out. If this problem hits your live assessment and you freeze on the constraint logic, StealthCoder solves it in seconds, invisible to the proctor.
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Find the Longest Equal Subarray is the kind of problem that decides whether you pass. StealthCoder reads the problem on screen and surfaces a working solution in under 2 seconds. Invisible to screen share. The proctor sees nothing. Made for the engineer who has done the work but might still blank with a webcam pointed at him.
Get StealthCoderThe trick is sliding window combined with a frequency map. You maintain a window of indices where all elements are the same, track how many elements you'd need to remove to make the window solid, and expand or contract the window based on whether removing k elements keeps you valid. The naive approach tries all subarrays and counts removals for each, which is O(n^2) and fails. The efficient path treats this like a two-pointer problem: slide right to include new elements, shrink left when the removal cost exceeds k, and track the maximum window size. Hash Table stores frequencies of elements within the current window. Binary Search isn't required but some solutions use it to optimize the removal cost calculation. Many candidates overthink the 'equal' constraint and don't realize you're finding longest windows of one value with at most k removals allowed. StealthCoder handles the window boundary logic instantly.
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Find the Longest Equal Subarray recycles across companies for a reason. It's medium-tier, and most candidates blank under the timer. StealthCoder is the hedge: an AI overlay invisible during screen share. It reads the problem and surfaces a working solution in under 2 seconds. Made for the engineer who has done the work but might still blank with a webcam pointed at him. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Find the Longest Equal Subarray interview FAQ
Is this really a sliding window problem?+
Yes. You maintain a window where all elements would be identical if you removed at most k elements. Expand right to include new indices, shrink left when removal cost exceeds k. The insight is tracking how many non-dominant elements exist in your window, then shrinking when that count exceeds k.
Why is the acceptance rate so low at 36%?+
Most candidates misread the constraint or don't realize you need to track the dominant element frequency within the window. The problem also requires clean boundary handling: knowing when to contract the window and how to recompute the dominant element efficiently trips up many solutions.
Do I need binary search for this?+
No, sliding window alone solves it in O(n) time. Binary search can optimize removal-cost lookups in some implementations, but it's not necessary. The straightforward two-pointer approach with a frequency map handles all cases correctly.
How does this relate to other sliding window problems?+
It's similar to 'longest substring with at most k distinct characters,' but here you're looking at one value with k removals allowed instead of k unique characters. The window-shrinking logic is analogous, but you track element frequency differently.
What's the biggest pitfall candidates hit?+
Forgetting to update the dominant element frequency when you shrink the left side of the window, or not realizing that removal cost is the window size minus the frequency of the most common element. Getting this wrong gives correct structure but wrong answers.
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