Top K Frequent Words
A medium-tier problem at 59% community acceptance, tagged with Array, Hash Table, String. Reported in interviews at Pocket Gems and 13 others.
Top K Frequent Words is a medium-difficulty problem that appears regularly at Amazon, Netflix, Robinhood, and ServiceNow. You're given a list of words and need to return the K most frequent ones, sorted lexicographically when frequencies tie. The trap is thinking you need a complex solution. Most candidates either overthink the sorting step or build a heap wrong, burning 15 minutes on a problem that should take 8. If this hits your live assessment and you blank on the optimal pattern, StealthCoder surfaces a working solution instantly while the proctor sees nothing.
Companies that ask "Top K Frequent Words"
Top K Frequent Words 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 pattern is straightforward but has teeth: count word frequencies with a hash table, then extract the top K. Where candidates stumble is the extraction step. A max heap won't work here because you need min-heap behavior (keep K smallest by frequency, eject the rest). The slick move is using a min heap of size K, or bucket sort if you want to avoid heap overhead entirely. Bucket sort is underrated here: since frequency maxes out at word count, you can create buckets indexed by frequency and iterate backward. Most fail because they implement a standard sort on the hash table counts, which is O(n log n) instead of O(n + K log n). When you hit this live and the bruteforce feels clunky, StealthCoder gives you the heap or bucket solution with clean code in seconds.
Pattern tags
You know the problem.
Make sure you actually pass it.
Top K Frequent Words 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.
Top K Frequent Words interview FAQ
Is this really asked at top companies or just in LeetCode curated lists?+
It's asked at Amazon, Netflix, Robinhood, ServiceNow, and 10 other named firms in the data. This is a real problem, not niche. High acceptance rate (59%) means it's not a trap, just a test of whether you know the heap or bucket pattern.
What's the trick that trips people up in the interview?+
Lexicographic tiebreaking. When two words have the same frequency, you must return them sorted alphabetically. Candidates often forget this constraint or implement it wrong, using the wrong heap comparator. It's a one-line fix if you catch it; a 5-minute rewrite if you don't.
Should I use a heap or bucket sort here?+
Both work. Heap is O(n log K) and intuitive; bucket sort is O(n) but requires thinking in buckets. In an interview, heap is safer because it's more familiar. Bucket sort impresses but risks off-by-one errors under pressure.
How does this relate to the other Hash Table and Heap topics?+
Hash Table counts frequencies. Heap extracts top K in sorted order. Together they're the core pattern for 'top K' variants. If you've drilled Kth Largest Element or Top K Frequent Elements, this is a sibling. Same mental toolkit, different surface.
Is this easier or harder than other medium problems on the assessment?+
With a 59% acceptance rate, it's on the easier end of medium. Most failures are careless (wrong heap type, missed tiebreaker), not algorithmic blindness. If you know heap basics and hash tables, you should pass.
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