Distribute Elements Into Two Arrays II
A hard-tier problem at 29% community acceptance, tagged with Array, Binary Indexed Tree, Segment Tree. Reported in interviews at Autodesk and 0 others.
Distribute Elements Into Two Arrays II is a hard problem that's hit Autodesk's assessments. With a 29% acceptance rate, it's the kind of problem that splits candidates fast. The trick isn't the distribution logic itself; it's tracking order relationships efficiently enough that your solution doesn't timeout on large inputs. Most people see "distribute" and write a simulation that works on examples, then watch it TLE on the real test. If this problem shows up in your OA and you blank on the data structure choice, StealthCoder surfaces a working solution in seconds, invisible to the proctor.
Companies that ask "Distribute Elements Into Two Arrays II"
Distribute Elements Into Two Arrays II 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 realized the OA tests how well you memorized 200 problems, not how well you code.
Get StealthCoderThe core challenge is distributing elements while maintaining constraints that depend on previously placed elements. Naive simulation works for small inputs but explodes on larger ones because you're checking relationships repeatedly. The real pattern: you need a data structure that answers range queries or tracks order without full rescans. Binary Indexed Tree and Segment Tree both solve this, but the tree choice matters for your specific constraints. Many candidates default to simulation, hit TLE at 80%, panic, and rewrite under pressure. The pattern requires thinking in terms of "how many elements satisfy property X up to position Y" rather than "check each element individually." StealthCoder is your hedge if you freeze on the tree choice during the live assessment.
Pattern tags
You know the problem.
Make sure you actually pass it.
Distribute Elements Into Two Arrays II 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 an Amazon engineer who realized the OA tests how well you memorized 200 problems, not how well you code. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Distribute Elements Into Two Arrays II interview FAQ
Is this still asked at FAANG or just Autodesk?+
The data shows Autodesk as the reported company so far. That doesn't mean it's exclusive to them. Hard problems with 29% acceptance typically cycle through multiple tech companies. It's rare enough that you won't encounter it in most prep materials, but common enough that you should know the pattern if you're targeting hard-level assessments.
What makes this hard? Simulation doesn't work?+
Simulation is correct but not efficient. You can distribute elements correctly by checking constraints after each placement, but on large inputs this becomes O(n^2) or worse. The hard part is realizing simulation will TLE and switching to a Binary Indexed Tree or Segment Tree to answer range queries in O(log n) per operation.
Should I use a Binary Indexed Tree or Segment Tree?+
Both work. Binary Indexed Tree is lighter and faster to code under pressure. Segment Tree is more flexible if constraints change mid-interview. Binary Indexed Tree is the pragmatic choice for a 45-minute OA. Pick one, practice it, and commit. Don't decide on the clock.
How does this relate to Array and Simulation topics?+
Simulation is the obvious approach and teaches the problem logic. But simulation alone fails hard problems. Array manipulation is the base skill, but you need to step up to a data structure that queries the array efficiently without rescanning. That gap between simulation and optimized tree logic is where candidates stall.
What's the key insight I'm missing if I TLE?+
You're likely recalculating counts or positions for each element instead of querying a structure that maintains them. Stop rescanning. Build a tree (BIT or Segment Tree) that lets you query "how many placed elements satisfy my constraint" in O(log n). That's the shift from TLE to AC.
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