Minimum Index Sum of Two Lists
A easy-tier problem at 58% community acceptance, tagged with Array, Hash Table, String. Reported in interviews at Yelp and 0 others.
Yelp asks this one and it looks easy on the surface, but a lot of candidates overcomplicate it or miss the actual constraint. You've got two lists of strings, each with an implicit index, and you need to find which strings appear in both lists, then return the ones with the lowest combined index sum. The trap is overthinking the return format or the index logic itself. Half the candidates who attempt this don't convert their solution cleanly enough to handle ties or edge cases with confidence. If you hit this during an assessment and blank on the exact tie-break behavior, StealthCoder surfaces the working solution in seconds.
Companies that ask "Minimum Index Sum of Two Lists"
Minimum Index Sum of Two 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 algorithm is straightforward: hash the first list with indices, iterate the second list, find overlaps, track the minimum sum. The real snag is the return format. Most people build a result array correctly but then stumble on how to handle multiple strings with the same minimum sum. You need to filter for equality, not just grab the first match. Another common miss: people hash both lists separately and then cross-reference, which wastes space when you could just mark matches on the first pass. The Array and Hash Table topics are the meat here. String handling is minimal. If you've done two-pointer sum problems before, the indexing logic feels natural. The acceptance rate is just under 58 percent, which means roughly four in ten candidates either return the wrong subset or fail an edge case. During your live assessment, if the logic doesn't click fast, StealthCoder runs invisibly and hands you a verified solution so you can move forward.
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Minimum Index Sum of Two Lists recycles across companies for a reason. It's easy-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.
Minimum Index Sum of Two Lists interview FAQ
What's the actual trick to this problem?+
There's no mathematical trick. The hard part is cleanly returning all strings tied for the minimum index sum, not just one. Hash the first list with indices, iterate the second list, track overlaps and the minimum sum, then filter for all strings matching that sum at the end.
Is this really an easy problem?+
Officially yes, but the acceptance rate is under 58 percent, which signals a gap between difficulty label and real-world execution. Most failures come from incomplete tie-handling or off-by-one index mistakes, not algorithmic misunderstanding.
Do I need to optimize for space or time?+
Neither is the bottleneck here. A single hash table pass plus one filter is linear and fast. Focus on correctness: correctly map indices, correctly identify minimum sum, correctly return all tied results.
Does Yelp still ask this question?+
It's the only company in the data asking it. Yelp does ask coding problems during hiring, so familiarity with the exact behavior on this one could be an edge if you interview there.
What if both lists are identical?+
All strings appear in both lists. The minimum index sum for a string at position i in both lists is 2i. Return all strings where their index sum equals the global minimum across all matching pairs.
Want the actual problem statement? View "Minimum Index Sum of Two Lists" on LeetCode →