Merge k Sorted Lists
A hard-tier problem at 57% community acceptance, tagged with Linked List, Divide and Conquer, Heap (Priority Queue). Reported in interviews at Dell and 41 others.
Merge k Sorted Lists is the hard-tier linked list problem that separates candidates who've drilled the fundamentals from those who panic under pressure. It's asked at Dell, MongoDB, Indeed, X, and Rivian frequently enough that you can't afford to skip it. The trap: you know how to merge two lists. Scaling that to k lists without TLE is where most candidates stall. The acceptance rate sits at 57%, which means nearly half the people who see it live don't land a clean solution. If this hits your assessment and you blank on the optimal structure, StealthCoder runs invisibly during screen share and surfaces a working implementation in seconds.
Companies that ask "Merge k Sorted Lists"
Merge k Sorted Lists 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 because the OA filter rejects engineers who'd pass the on-site. That's a broken filter. This is the workaround.
Get StealthCoderThe naive approach is to merge lists pairwise, but that's slow. The real pattern is recognizing this as a Heap or Divide and Conquer problem. A min-heap lets you extract the smallest node across all k lists in O(log k) time per node. Alternatively, divide and conquer recursively merges lists in pairs, reducing k by half each level. Most candidates either try pairwise merge sequentially (O(nk^2) disaster) or forget that a heap needs to compare nodes, not just values. The algorithm demands you think in terms of order statistics across multiple streams, not just linear traversal. When you hit this live and the straightforward approach doesn't pass the time-limit tests, that's when StealthCoder's invisible solution window becomes your safety net.
Pattern tags
You know the problem.
Make sure you actually pass it.
Merge k Sorted Lists 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 because the OA filter rejects engineers who'd pass the on-site. That's a broken filter. This is the workaround. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Merge k Sorted Lists interview FAQ
Is Merge k Sorted Lists still asked at big tech companies?+
Yes. It's in active rotation at MongoDB, Indeed, Dell, and at least 10 other tier-1 companies in recent reports. The 57% acceptance rate reflects its hard difficulty and the number of candidates who freeze on it live. This isn't a deprecated problem.
What's the key insight I'm missing if I keep getting TLE?+
You're likely merging pairwise sequentially instead of using a heap or divide-and-conquer tree structure. A min-heap across all k lists reduces each extraction to O(log k), not O(k). That difference compounds across thousands of nodes and determines whether you pass or timeout.
Does this problem test Heap or Divide and Conquer more often?+
Both are valid and asked. Heap solutions are more intuitive and interview-friendly because they're easier to explain live. Divide and Conquer is elegant but requires careful recursion. Interviewers rarely care which you pick, as long as you justify the complexity.
How does Merge k Sorted Lists relate to Merge Sort?+
Conceptually, they're cousins. Merge Sort divides an array recursively and merges sorted subarrays. Merge k Sorted Lists applies the same divide-and-conquer merge strategy to k independent linked lists. The merging logic is almost identical; the data structure difference is what trips people up.
If I only drill one linked list problem, should it be this one?+
Yes. At 42 companies and hard difficulty, the ROI is high. It forces you to think beyond linear traversal and combine linked lists with heap or tree logic. Mastering this covers most linked list interview patterns.
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