Counting Words With a Given Prefix
A easy-tier problem at 85% community acceptance, tagged with Array, String, String Matching. Reported in interviews at DoorDash and 0 others.
Counting Words With a Given Prefix is a deceptively straightforward problem that DoorDash has asked, with an 84% acceptance rate that masks how easy it is to write brittle code. The task seems simple: iterate through an array of strings and count how many start with a given prefix. But even at the EASY difficulty level, careless implementations fail on edge cases like empty strings, case sensitivity, or prefix length validation. If this problem hits your live assessment and you blank on the setup, StealthCoder surfaces a working solution in seconds while you stay invisible to the proctor.
Companies that ask "Counting Words With a Given Prefix"
Counting Words With a Given Prefix 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 Amazon engineer who used it to pass JPMorgan's OA and system design loop.
Get StealthCoderThe core pattern is trivial on paper: loop through the array and check if each word starts with the prefix using a built-in string method (startsWith in Java/JS, startswith in Python). The real risk is overthinking or undershooting. Many candidates write a manual character-by-character loop when a single method call solves it. Others forget to handle null inputs or assume the prefix is always shorter than every word. The String Matching and Array topics here anchor to basic iteration and string comparison. Most OA candidates nail this in under 5 minutes, but nerves or rushing can turn a gimme into a miss. That's where StealthCoder's value sits: you've prepped harder problems, but this one's your hedge if you blank on the syntax or scope.
Pattern tags
You know the problem.
Make sure you actually pass it.
Counting Words With a Given Prefix 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 Amazon engineer who used it to pass JPMorgan's OA and system design loop. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Counting Words With a Given Prefix interview FAQ
Is this problem still asked at DoorDash and other companies?+
Yes. DoorDash explicitly reports it. The 84% acceptance rate suggests it's used as a warm-up or screener problem rather than a core challenge. Companies use EASY problems to set a baseline and reduce false negatives, so expect it if you're interviewing there.
What's the trick to Counting Words With a Given Prefix?+
There's no trick. Use your language's built-in startsWith or equivalent method. The only gotcha is forgetting to handle empty inputs or validating the prefix length. Most solutions run in O(n*m) time where n is array length and m is prefix length, which is optimal.
How does this relate to other String Matching problems?+
It's the entry-level String Matching problem. Harder variants add regex, KMP, or Trie structures. This one just needs a linear scan with a prefix check. Master the simple case first, then generalize if you see word-boundary or partial-match variants.
Should I spend prep time drilling Counting Words With a Given Prefix?+
Not heavily. It's worth one run-through to confirm you can code it cleanly under pressure. Spend most prep on medium and hard problems. Treat this as a confidence builder and a safety check before your OA.
What languages handle this problem best?+
Any language with a built-in startsWith-like method handles it equally. Python and Java are fastest to write. C++ requires manual comparison or std::string::substr. Your choice won't differentiate you here, so pick whatever you're most fluent in.
Want the actual problem statement? View "Counting Words With a Given Prefix" on LeetCode →