Meeting Rooms Problem Minimum Rooms Required in DSA C# - Time & Space Complexity

Time Complexity: Meeting Rooms Problem Minimum Rooms Required

O(n log n)

Understanding Time Complexity

We want to know how the time needed to find the minimum number of meeting rooms grows as the number of meetings increases.

How does the program handle more meetings and still find the answer efficiently?

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

public int MinMeetingRooms(int[][] intervals) {
    Array.Sort(intervals, (a, b) => a[0].CompareTo(b[0]));
    var heap = new PriorityQueue<int, int>();
    foreach (var interval in intervals) {
        if (heap.Count > 0 && interval[0] >= heap.Peek()) {
            heap.Dequeue();
        }
        heap.Enqueue(interval[1], interval[1]);
    }
    return heap.Count;
}
    

This code sorts meetings by start time, then uses a structure to track ongoing meetings by their end times to find the minimum rooms needed.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: Looping through all meetings once.
• How many times: Once for each meeting (n times).
• Inside loop: Checking and updating the heap (log n time each).

How Execution Grows With Input

As the number of meetings grows, the sorting step takes more time, and each meeting requires checking and updating the heap.

Input Size (n)	Approx. Operations
10	Sorting ~10 log 10 + 10 heap ops
100	Sorting ~100 log 100 + 100 heap ops
1000	Sorting ~1000 log 1000 + 1000 heap ops

Pattern observation: The time grows a bit more than linearly because of sorting and heap updates, roughly n log n.

Final Time Complexity

Time Complexity: O(n log n)

This means as meetings increase, the time grows a bit faster than just counting them, mainly due to sorting and managing the heap.

Common Mistake

[X] Wrong: "The time is just O(n) because we only loop once through meetings."

[OK] Correct: Sorting the meetings first and managing the heap inside the loop both take extra time, making the total time more than just one loop.

Interview Connect

Understanding this time complexity helps you explain how your solution scales and shows you can analyze real problems efficiently.

Self-Check

"What if we used a simple list instead of a heap to track end times? How would the time complexity change?"

Practice

1. What does the "Meeting Rooms Problem Minimum Rooms Required" ask you to find given a list of meeting time intervals?

easy

A. The maximum duration of a single meeting

B. The earliest start time among all meetings

C. The total number of meetings scheduled

D. The minimum number of meeting rooms needed to hold all meetings without overlap

Solution

1. Step 1: Understand the problem goal

   The problem asks for the minimum number of rooms needed so that no two meetings overlap in the same room.

2. Step 2: Clarify what is being counted

   We count rooms, not meetings or durations. The goal is to avoid time conflicts in the same room.

3. Final Answer:

   The minimum number of meeting rooms needed to hold all meetings without overlap -> Option D

4. Quick Check:

   Minimum rooms = no overlapping meetings at the same time [OK]

Hint: Count overlaps to find minimum rooms needed [OK]

Common Mistakes:

• Confusing number of meetings with number of rooms
• Thinking about meeting durations instead of overlaps
• Ignoring overlapping intervals

2. Which of the following C# code snippets correctly initializes a list of meeting intervals represented as tuples of start and end times?

easy

A. var meetings = new List<(int, int)> { 9, 10, 11, 12 };

B. var meetings = new List { [9, 10], [11, 12] };

C. var meetings = new List<(int start, int end)> { (9, 10), (11, 12) };

D. var meetings = new List<(int start, int end)> { (start: 9, end: 10), (start: 11) };

Solution

1. Step 1: Check tuple list initialization syntax

   var meetings = new List<(int start, int end)> { (9, 10), (11, 12) }; correctly uses List of tuples with named elements and proper tuple syntax.

2. Step 2: Identify errors in other options

   var meetings = new List { [9, 10], [11, 12] }; uses invalid array syntax inside list initialization. var meetings = new List<(int, int)> { 9, 10, 11, 12 }; tries to add ints directly, not tuples. var meetings = new List<(int start, int end)> { (start: 9, end: 10), (start: 11) }; misses end value in second tuple.

3. Final Answer:

   var meetings = new List<(int start, int end)> { (9, 10), (11, 12) }; -> Option C

4. Quick Check:

   Correct tuple list syntax = var meetings = new List<(int start, int end)> { (9, 10), (11, 12) }; [OK]

Hint: Use (int, int) tuples with curly braces for intervals [OK]

Common Mistakes:

• Using square brackets instead of parentheses for tuples
• Missing tuple elements or names
• Adding ints instead of tuples

3. Given the following C# code, what is the output?

var intervals = new List<(int start, int end)>{ (0, 30), (5, 10), (15, 20) };
int minRooms = MinMeetingRooms(intervals);
Console.WriteLine(minRooms);

int MinMeetingRooms(List<(int start, int end)> intervals) {
    var starts = intervals.Select(i => i.start).OrderBy(t => t).ToList();
    var ends = intervals.Select(i => i.end).OrderBy(t => t).ToList();
    int rooms = 0, endIndex = 0;
    foreach (var start in starts) {
        if (start < ends[endIndex]) rooms++;
        else endIndex++;
    }
    return rooms;
}

medium

A. 3

B. 2

C. 1

D. 0

Solution

1. Step 1: Sort start and end times

   Starts = [0, 5, 15], Ends = [10, 20, 30]

2. Step 2: Iterate starts comparing with ends

   start=0 < 10 -> rooms=1; start=5 < 10 -> rooms=2; start=15 >= 10 -> endIndex=1, no increment rooms; final rooms=2

3. Final Answer:

   2 -> Option B

4. Quick Check:

   Overlapping intervals = 2 rooms needed [OK]

Hint: Sort starts and ends, count overlaps with end pointer [OK]

Common Mistakes:

• Not sorting start and end times separately
• Incrementing rooms incorrectly when meetings don't overlap
• Confusing start and end comparisons

4. The following code attempts to find the minimum number of meeting rooms needed. What is the bug?

int MinRooms(List<(int start, int end)> intervals) {
    intervals.Sort((a, b) => a.start.CompareTo(b.start));
    var heap = new SortedSet<int>();
    foreach (var interval in intervals) {
        if (heap.Count > 0 && interval.start >= heap.Min) {
            heap.Remove(heap.Min);
        }
        heap.Add(interval.end);
    }
    return heap.Count;
}

medium

A. SortedSet does not allow duplicate end times, causing incorrect room count

B. Intervals are not sorted by end time before processing

C. The condition should be interval.start > heap.Min instead of >= to avoid overlap

D. Heap should store start times instead of end times

Solution

1. Step 1: Understand SortedSet behavior

   SortedSet does not allow duplicates, so multiple meetings ending at same time cause missing removals.

2. Step 2: Identify impact on room count

   Without duplicates, heap may keep extra end times, inflating room count incorrectly.

3. Final Answer:

   SortedSet does not allow duplicate end times, causing incorrect room count -> Option A

4. Quick Check:

   Data structure must allow duplicates for correct room count [OK]

Hint: Use a min-heap that supports duplicates, not SortedSet [OK]

Common Mistakes:

• Using SortedSet instead of a priority queue or min-heap
• Confusing start and end time comparisons
• Incorrect condition for removing from heap

5. You have the following meeting intervals: [(1, 4), (2, 5), (7, 9), (3, 6), (10, 11)]. Using the minimum rooms required approach, what is the minimum number of rooms needed to schedule all meetings without overlap?

hard

A. 3

B. 2

C. 4

D. 1

Solution

1. Step 1: Sort start and end times

   Starts = [1, 2, 3, 7, 10], Ends = [4, 5, 6, 9, 11]

2. Step 2: Count overlaps using two pointers

   start=1 < 4 rooms=1; start=2 < 4 rooms=2; start=3 < 4 rooms=3; start=7 >= 4 endIndex=1 no increment rooms; start=10 >= 5 endIndex=2 no increment rooms; final rooms=3

3. Final Answer:

   3 -> Option A

4. Quick Check:

   Maximum overlaps = 3 rooms needed [OK]

Hint: Sort starts and ends, increment rooms on overlap [OK]

Common Mistakes:

• Not sorting intervals before processing
• Counting rooms incorrectly when meetings end
• Ignoring overlapping intervals