Average Waiting Time
A medium-tier problem at 73% community acceptance, tagged with Array, Simulation. Reported in interviews at Instacart and 1 others.
Average Waiting Time is a medium-difficulty problem that Instacart and DE Shaw have both asked in their online assessments. It's the kind of problem that looks straightforward until you miss the simulation detail that breaks the naive approach. The 73% acceptance rate is high, but that masks a trap: most solutions that fail aren't wrong on logic, they're wrong on what "waiting time" actually means in the context. If you get this in a live OA and blank on the timing calculation, StealthCoder surfaces a working solution in seconds, invisible to the proctor.
Companies that ask "Average Waiting Time"
Average Waiting Time 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 is understanding that waiting time compounds across customers. A naive candidate writes a simple loop and calculates time per customer, but misses that each customer's wait depends on the service time of everyone before them. You need to simulate the process: track when each customer finishes, calculate the gap between their arrival and when they're actually served, then average. The simulation itself is straightforward, but candidates often confuse "service time" with "waiting time" or forget to account for idle periods. Array iteration and state tracking are your tools. This is where StealthCoder earns its keep: if you hit this live and the pattern doesn't click, the solution appears in real time, freeing you to move on.
Pattern tags
You know the problem.
Make sure you actually pass it.
Average Waiting Time 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.
Average Waiting Time interview FAQ
Is this just a simple math problem or do I need a real simulation?+
You need a real simulation. You can't shortcut it with a formula. Track when each customer arrives, when they start service, when they finish, then calculate individual waits. The simulation approach is clean and handles edge cases (idle servers, different arrival times) naturally.
What's the difference between waiting time and service time here?+
Waiting time is the gap between arrival and service start. Service time is how long the work takes. Many candidates conflate them and end up with wrong answers. Track both separately in your simulation.
Is this still asked at Instacart and DE Shaw?+
Both companies have confirmed this problem in their assessments. It's a stable problem because it tests fundamentals: array iteration, state tracking, and the ability to model a real-world process. Not flashy, but essential.
What topics should I study before attempting this?+
Array basics and simulation. You need to iterate through data in order, track cumulative state (when servers become free), and calculate derived values (waiting time). No advanced data structures needed.
Why do smart people still fail this in interviews?+
Overcomplication and misreading. Candidates try to optimize too early or misunderstand the problem statement. The simulation is straightforward, but you have to be crystal clear on definitions and edge cases like empty periods.
Want the actual problem statement? View "Average Waiting Time" on LeetCode →