N-Repeated Element in Size 2N Array
A easy-tier problem at 77% community acceptance, tagged with Array, Hash Table. Reported in interviews at Akamai and 0 others.
You're given an array of size 2N containing N-1 distinct elements and one element that appears exactly N times. Find the repeated element. It's an easy problem on paper, but it's a speed check at Akamai and similar shops. The acceptance rate is solid at 77%, but that doesn't mean you won't freeze on the live assessment if you overcomplicate it. The trap is overthinking a trivial constraint: you don't need to optimize memory or runtime to pass. StealthCoder surfaces the working solution in seconds if you blank during screen share.
Companies that ask "N-Repeated Element in Size 2N Array"
N-Repeated Element in Size 2N 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 at a top-10 tech company who can solve these problems cold but didn't want to trust himself in a 90-minute screen share.
Get StealthCoderThe problem hands you a huge mathematical hint: if an element appears N times in a 2N array, it dominates the space. You can solve this three ways: brute force with a hash table, a set-based approach, or pure math. Most candidates go hash table on reflex because topics list Array and Hash Table. The real trick is noticing the constraint makes the problem almost insultingly simple. Count frequencies, return the one with count N. No edge cases. No tricky bit manipulation. The common pitfall is writing clean, over-engineered code when a four-line solution passes. If you hit this live and your brain goes sideways, StealthCoder runs invisibly and hands you a working answer so you can move on without eating time.
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N-Repeated Element in Size 2N Array recycles across companies for a reason. It's easy-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 at a top-10 tech company who can solve these problems cold but didn't want to trust himself in a 90-minute screen share. Works on HackerRank, CodeSignal, CoderPad, and Karat.
N-Repeated Element in Size 2N Array interview FAQ
Is this problem actually asked at real interviews?+
Yes. Akamai has confirmed it. It's low-frequency and usually shows up early in a phone screen or online assessment to separate who can code fast from who can't. Treat it as a gimme, not a deep-dive.
What's the trick I'm missing?+
There isn't one. The array size and element frequency are designed to make the problem trivial. Use a hash table, count occurrences, return the element with count N. That's it. The only trap is overthinking.
Do I need to optimize for space or time?+
No. The problem has no optimization constraints listed. A hash table solution runs in O(n) time and O(n) space. That passes. Candidates who try to use constant space or clever bit tricks usually just waste time.
How does this relate to the topics Array and Hash Table?+
It's a basic hash table problem applied to an array. You iterate the array once, build a frequency map, then scan the map. Neither operation is advanced. It's a warm-up, not a hard problem.
Should I study this problem if I'm prepping for Akamai?+
Skim it. If you know hash tables, you can solve this in under two minutes cold. Spend more time on medium problems from their problem history. This one is a confidence builder, not a blocker.
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