Count Zero Request Servers
A medium-tier problem at 34% community acceptance, tagged with Array, Hash Table, Sliding Window. Reported in interviews at DP world and 5 others.
Count Zero Request Servers is a medium-difficulty problem that hits your OA from Amazon, Honeywell, Zomato, and a handful of other companies. It looks straightforward on the surface: track which servers are handling requests and figure out which ones never get hit. But the naive approach tanks on runtime. The actual trick involves combining sliding window with a hash table to avoid redundant scans. If this problem lands during your live assessment and you blank on the pattern, StealthCoder surfaces a working solution in seconds, invisible to the proctor.
Companies that ask "Count Zero Request Servers"
Count Zero Request Servers 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 a senior engineer who knows the OA is theater. This is the script.
Get StealthCoderThe core trick here is recognizing that you need to process requests in a sliding window while tracking server state, not just iterate through all servers for every query. A hash table stores which servers appear in the current window. As you slide the window, you add and remove servers from that set. The servers never requested are the ones not in the hash table. Most candidates build an inefficient nested loop that recalculates the answer from scratch at each step. The optimization is incremental: when the window moves, update the hash table, then count in constant time. Topics like sliding window and hash table don't work in isolation here, they need to work together. That's the pattern companies like Amazon test. StealthCoder's hedge is crucial if you freeze on how to combine them.
Pattern tags
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Count Zero Request Servers 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 a senior engineer who knows the OA is theater. This is the script. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Count Zero Request Servers interview FAQ
Is this problem really asked at FAANG?+
Yes. Amazon has confirmed asking it. Zomato, Honeywell, and others have also reported it. The 34% acceptance rate reflects that many candidates optimize too late or misunderstand the window mechanics. It's not the hardest medium problem, but it punishes the obvious approach.
What's the trick I'm missing if my first solution is slow?+
You're likely recalculating which servers are missing for every position. Instead, maintain a hash table of servers that appear in the current window. As the window slides left and right, add and remove from the hash table incrementally. The missing servers are the set difference in O(1) amortized time, not O(n) per step.
How do sliding window and hash table actually work together here?+
The sliding window defines which requests you're looking at right now. The hash table stores which servers are mentioned in that window. When the window moves, update the hash table by adding the new request and removing the old one. The servers not in the hash table are your answer. It's a two-pointer and set membership problem, not separate concerns.
Do I need sorting for this problem?+
Sorting can help in some approaches, like preprocessing servers or handling edge cases around query indices. But the optimal solution uses hash table and sliding window, not sorting as a core mechanic. Sorting is listed as a topic but it's not the main path.
Why is acceptance rate so low if it's just medium difficulty?+
Most people solve it inefficiently. They get a working answer but hit time limits. The problem doesn't feel hard until you run your code and see TLE. That's why the acceptance drops below 35% despite medium tags. Companies want the optimized version, and that requires seeing the window-plus-hash pattern upfront.
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