Contiguous Array
A medium-tier problem at 49% community acceptance, tagged with Array, Hash Table, Prefix Sum. Reported in interviews at Morgan Stanley and 0 others.
Contiguous Array is a medium-difficulty problem that appears in assessments at major financial firms like Morgan Stanley. You're given a binary array and need to find the longest contiguous subarray with an equal number of 0s and 1s. It sounds simple until you realize the brute-force approach times out. Nearly half of candidates who attempt it don't submit a passing solution. The pattern requires a mental shift from thinking about counts to thinking about balance, and if you blank on it during your live OA, StealthCoder surfaces the working approach invisibly while you stay on screen share.
Companies that ask "Contiguous Array"
Contiguous Array 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. Built by an engineer who got tired of watching his cohort grind for six months and still get filtered at the OA stage.
Get StealthCoderThe trap is that you can't just iterate and count. The real trick is converting the problem: treat 0s as -1, then find the longest subarray with sum 0. Use a hash table to track the first occurrence of each prefix sum. When you see the same prefix sum twice, the subarray between those indices has equal 0s and 1s. This is a Prefix Sum problem wearing an Array disguise. Most candidates either attempt a nested loop (too slow) or miss the hash table optimization entirely. The problem tests whether you recognize that balance problems often hide inside prefix-sum patterns. StealthCoder catches this pattern instantly if you hit it live and weren't sure of the approach.
Pattern tags
You know the problem.
Make sure you actually pass it.
Contiguous Array 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. Built by an engineer who got tired of watching his cohort grind for six months and still get filtered at the OA stage. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Contiguous Array interview FAQ
Is this problem actually asked at top companies?+
Yes. Morgan Stanley specifically reports asking it. It's not ultra-frequent, but it shows up at firms that care about algorithmic depth. The 49% acceptance rate suggests it's not a gimme, so preparation matters.
What's the trick I'm missing if I think in terms of raw counts?+
Counting 0s and 1s separately is intuitive but slow. The insight is to convert 0 to -1, then find where the cumulative sum returns to a value it's seen before. That subarray has zero net sum, meaning equal 0s and 1s. Prefix Sum is the unlocking pattern.
Why does the hash table approach work here?+
Store each prefix sum and the first index where it appears. When you see a prefix sum again, the subarray between those indices sums to zero. Since we want the longest subarray, we keep the first occurrence of each sum and update max length as we go. Hash table lookup is O(1), making the whole algorithm linear.
Will the Array and Hash Table topics cover everything I need?+
Those are the mechanical tools, but the real pattern is Prefix Sum. If you're strong on prefix sum problems and hash table indexing, the solution clicks fast. If you've drilled other prefix-sum problems, this feels familiar. If not, it's a surprise.
What should I practice before my OA if I see this problem type coming?+
Run through other prefix-sum problems like subarray sums, subarrays with a given sum, and balance-type questions. Practice the habit of converting count problems into sum problems. Get comfortable storing and querying first occurrences in a hash map under time pressure.
Want the actual problem statement? View "Contiguous Array" on LeetCode →