Managing overlapping timelines, meeting rooms, and range merges
Sort ranges by start (or end) time so overlapping relationships can be resolved linearly by comparing adjacent pairs.
Core Invariant: Once sorted by start time (`start_i <= start_j`), interval J overlaps with interval I if and only if `start_j <= end_i`. When overlapping, merged end is `max(end_i, end_j)`.
Intervals cannot be sorted or endpoints are infinite/continuous without discrete ordering.
def merge_intervals(intervals: list[list[int]]) -> list[list[int]]:
if not intervals:
return []
# Sort primarily by start time
intervals.sort(key=lambda x: x[0])
merged = [intervals[0]]
for start, end in intervals[1:]:
last_end = merged[-1][1]
if start <= last_end:
# Overlapping intervals: merge by taking the max end
merged[-1][1] = max(last_end, end)
else:
# Non-overlapping: append as separate interval
merged.append([start, end])
return merged# | Problem | Difficulty | Top Companies↓ | Frequency | Acceptance | |
|---|---|---|---|---|---|---|
| #56 | Medium | 100% | 52.3% | |||
| #253 | Meeting Rooms II ArrayTwo PointersGreedySortingHeap (Priority Queue)Prefix Sum | Medium | 100% | 52.7% | ||
| #435 | Non-overlapping Intervals ArrayDynamic ProgrammingGreedySorting | Medium | 90% | 57.4% | ||
| #57 | Insert Interval Array | Medium | 76% | 45.5% | ||
| #2402 | Meeting Rooms III ArrayHash TableSortingHeap (Priority Queue)Simulation | Hard | 63% | 0.5% | ||
| #759 | Employee Free Time ArraySweep LineSortingHeap (Priority Queue) | Hard | 75% | 73.0% | ||
| #252 | Meeting Rooms ArraySortingQuicksort | Easy | 60% | 59.5% | ||
| #986 | Interval List Intersections ArrayTwo PointersSweep Line | Medium | 100% | 73.1% | ||
| #1094 | Car Pooling ArraySortingHeap (Priority Queue)SimulationPrefix Sum | Medium | 89% | 56.4% | ||
| #729 | My Calendar I ArrayBinary SearchDesignSegment TreeOrdered Set | Medium | 75% | 58.3% | ||
| #452 | Minimum Number of Arrows to Burst Balloons ArrayGreedySorting | Medium | 100% | 0.6% | ||
| #2472 | Maximum Number of Non-overlapping Palindrome Substrings Two PointersStringDynamic ProgrammingGreedy | Hard | 88% | 44.9% | ||
| #2054 | Two Best Non-Overlapping Events ArrayBinary SearchDynamic ProgrammingSortingHeap (Priority Queue) | Medium | 100% | 64.0% | ||
| #2406 | Divide Intervals Into Minimum Number of Groups ArrayTwo PointersGreedySortingHeap (Priority Queue)Prefix Sum | Medium | 88% | 63.6% | ||
| #689 | Maximum Sum of 3 Non-Overlapping Subarrays ArrayDynamic ProgrammingSliding WindowPrefix Sum | Hard | 63% | 59.9% | ||
| #1288 | Remove Covered Intervals ArraySorting | Medium | 61% | 60.0% | ||
| #1523 | Easy | 38% | 54.6% | |||
| #495 | Teemo Attacking ArraySimulation | Easy | 100% | 57.9% | ||
| #3414 | Maximum Score of Non-overlapping Intervals ArrayBinary SearchDynamic ProgrammingSorting | Hard | 95% | 31.8% | ||
| #1851 | Minimum Interval to Include Each Query IntervalsArrayBinary SearchSweep LineSortingHeap (Priority Queue) | Hard | 60% | 0.5% | ||
| #1024 | Video Stitching ArrayDynamic ProgrammingGreedy | Medium | 88% | 52.8% | ||
| #2276 | Count Integers in Intervals DesignSegment TreeOrdered Set | Hard | 63% | 36.1% | ||
| #436 | Find Right Interval ArrayBinary SearchSorting | Medium | 25% | 56.1% | ||
| #1477 | Find Two Non-overlapping Sub-arrays Each With Target Sum ArrayHash TableBinary SearchDynamic ProgrammingSliding Window | Medium | 25% | 0.5% | ||
| #2479 | Maximum XOR of Two Non-Overlapping Subtrees TreeDepth-First SearchGraph TheoryTrie | Hard | 100% | 52.2% | ||
| #1031 | Maximum Sum of Two Non-Overlapping Subarrays ArrayDynamic ProgrammingSliding Window | Medium | 86% | 0.6% | ||
| #1124 | Longest Well-Performing Interval ArrayHash TableStackMonotonic StackPrefix Sum | Medium | 75% | 37.9% | ||
| #731 | My Calendar II ArrayBinary SearchDesignSegment TreePrefix SumOrdered Set | Medium | 30% | 63.3% | ||
| #1520 | Maximum Number of Non-Overlapping Substrings Hash TableStringGreedySorting | Hard | 25% | 0.7% | ||
| #1621 | Number of Sets of K Non-Overlapping Line Segments MathDynamic ProgrammingCombinatoricsPrefix Sum | Medium | 25% | 0.7% | ||
| #352 | Data Stream as Disjoint Intervals Hash TableBinary SearchUnion-FindDesignData StreamOrdered Set | Hard | 13% | 60.3% | ||
| #4016 | Maximum Area of Two Non-Overlapping Square Submatrices ArrayBinary SearchDynamic ProgrammingMatrix | Medium | 100% | 0.4% | ||
| #2121 | Medium | 100% | 48.1% | |||
| #3893 | Medium | 50% | 44.4% | |||
| #497 | Random Point in Non-overlapping Rectangles ArrayMathBinary SearchReservoir SamplingPrefix SumOrdered SetRandomized | Medium | 30% | 40.1% | ||
| #915 | Medium | 13% | 49.5% | |||
| #3323 | Minimize Connected Groups by Inserting Interval ArrayBinary SearchSliding WindowSorting | Medium | 75% | 50.1% | ||
| #1272 | Remove Interval Array | Medium | 25% | 67.3% | ||
| #732 | My Calendar III Binary SearchDesignSegment TreePrefix SumOrdered Set | Hard | 25% | 72.0% | ||
| #1546 | Maximum Number of Non-Overlapping Subarrays With Sum Equals Target ArrayHash TableGreedyPrefix Sum | Medium | 25% | 49.1% | ||
| #3975 | Filter Occupied Intervals ArraySorting | Medium | 17% | 46.1% |
Browse company-specific interview problem lists and recency breakdowns:
Master core algorithmic patterns tested in FAANG & Big Tech coding interviews.
Managing overlapping timelines, meeting rooms, and range merges It is categorized under Data Structures and features 41 curated interview problems across Easy (3), Medium (27), and Hard (11) difficulties.
Companies frequently asking Intervals & Overlap Scheduling questions include Google, Amazon, Microsoft, Bloomberg, Meta, NeetCode 150.
Start by studying the algorithmic strategy and template code, then practice Easy and Medium problems before attempting Hard problems under timed conditions.