Best Meeting Point
A hard-tier problem at 61% community acceptance, tagged with Array, Math, Sorting. Reported in interviews at X and 3 others.
Best Meeting Point shows up in live assessments at X, Applied Intuition, DoorDash, and Samsung. On paper it looks like a geometry problem, but it's a hidden sorting and median trick disguised as optimization. Most candidates start building distance matrices or trying to minimize Euclidean distance directly, then run into time-limit walls. The acceptance rate sits at 61%, meaning smart test-takers are solving it but a solid chunk aren't finding the pattern. If this problem hits your live OA and you blank on the median insight, StealthCoder surfaces the working solution in seconds, invisible to the proctor.
Companies that ask "Best Meeting Point"
Best Meeting Point 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 trick is that you don't optimize 2D coordinates together. You decompose the problem into two independent 1D problems: find the best x-coordinate, then find the best y-coordinate. For each dimension separately, the optimal meeting point is the median. Once you realize that, the solution collapses to sorting the x-values, sorting the y-values, grabbing the medians, and calculating the Manhattan distance. Most candidates waste 20 minutes chasing 2D Euclidean formulas or trying brute force with nested loops before hitting the time limit. The Array, Sorting, and Math topics signal that decomposition and median selection are central. If you've drilled median-finding problems, you'll spot this fast. If not, StealthCoder catches you when intuition fails during the live assessment.
Pattern tags
You know the problem.
Make sure you actually pass it.
Best Meeting Point recycles across companies for a reason. It's hard-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.
Best Meeting Point interview FAQ
Is Best Meeting Point really a hard problem?+
The 61% acceptance rate suggests it's moderate in execution but trips up candidates who don't recognize the median decomposition trick immediately. Once you see it, implementation is straightforward. The hard part is pattern recognition under time pressure, not code complexity.
Why does decomposing into two 1D problems work here?+
Manhattan distance separates: the total distance is the sum of x-distance and y-distance. So minimizing total distance is equivalent to minimizing x-distance and y-distance independently. The optimal point for each coordinate is its median, a well-known result from statistics.
What's the most common wrong approach?+
Trying to solve it as a true 2D optimization problem using Euclidean distance or brute-force iteration over all grid points. That scales badly and misses the insight. The problem is actually about 1D median selection, repeated twice.
Do I need to memorize the median trick?+
Not if you understand why it works. But you should know that for 1D, the point minimizing sum of distances is the median. If you've seen Kth Largest Element or similar problems, you're already thinking in the right framework.
How does this relate to matrix and array topics?+
Input is usually a 2D array of coordinates. Sorting and extracting the median from the array of x-coords and y-coords separately is the core operation. Math comes in because you're applying a statistical property, not a brute-force search.
Want the actual problem statement? View "Best Meeting Point" on LeetCode →