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Divide & Conquer Interview Questions

Merge sort is the archetype: split, recurse, and do the real work in the merge step. The pattern shows up in median-of-two-sorted-arrays and in counting inversions, where the combine step answers the actual question. When a problem demands better than O(n²) and sorting alone does not get you there, this is usually the route.

Recognise it when you see

A problem that halves cleanly, or a required O(log n) / O(n log n) bound.

6 problems. Each one runs in an in-browser editor against real test cases, with hints and a worked solution.

Easy1

Convert Sorted Array to Balanced BSTPremium

EasyTreesBinary Search

Medium2

Maximum SubarrayPremium

MediumDynamic Programming

Kth Largest Element in an ArrayPremium

MediumHeap / Priority QueueSorting

Hard3

Median of Two Sorted ArraysPremium

HardBinary Search

Merge k Sorted ListsPremium

HardLinked ListHeap / Priority Queue

Count of Smaller Numbers After SelfPremium

HardSorting

Learn the triggers, not just the templates

The patterns cheat sheet covers all of these in one page - what each one looks like in a problem statement, and the template that follows.

Interview patterns cheat sheet Big-O cheat sheet All coding problems

Divide & Conquer Interview Questions

Merge sort is the archetype: split, recurse, and do the real work in the merge step. The pattern shows up in median-of-two-sorted-arrays and in counting inversions, where the combine step answers the actual question. When a problem demands better than O(n²) and sorting alone does not get you there, this is usually the route.