Meeting Rooms Problem Minimum Rooms Required in DSA Go - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is the main goal of the Meeting Rooms Problem Minimum Rooms Required?

To find the minimum number of meeting rooms needed to hold all meetings without overlap.

beginner

In the Meeting Rooms Problem, why do we sort the meetings by their start time?

Sorting by start time helps us process meetings in the order they begin, making it easier to check for overlaps and allocate rooms efficiently.

intermediate

What data structure is commonly used to track the end times of meetings currently using rooms?

A min-heap (priority queue) is used to keep track of the earliest finishing meeting, so we can reuse rooms when possible.

intermediate

How does the min-heap help reduce the number of rooms needed in the Meeting Rooms Problem?

By always knowing the meeting that ends earliest, we can free up a room and assign it to the next meeting if it starts after that end time, reducing total rooms needed.

intermediate

What is the time complexity of the optimal solution for the Meeting Rooms Problem Minimum Rooms Required?

O(n log n), where n is the number of meetings. Sorting takes O(n log n), and each meeting is pushed and popped from the heap at most once.

What is the first step in solving the Meeting Rooms Problem Minimum Rooms Required?

A Sort meetings by start time

B Sort meetings by end time

C Use a stack to track meetings

D Count total meetings

Sorting meetings by their start time allows us to process them in chronological order.

Which data structure helps efficiently track the earliest finishing meeting?

A Queue

B Min-heap

C Stack

D Array

A min-heap keeps the smallest end time at the top, helping to reuse rooms.

If a meeting starts after the earliest ending meeting, what should we do?

A Reuse the room of the earliest ending meeting

B End all meetings

C Ignore the meeting

D Allocate a new room

We can reuse the room because the previous meeting has ended.

What does the size of the min-heap represent at any point?

A Number of meetings starting

B Number of meetings finished

C Total meetings

D Number of rooms currently in use

The heap size shows how many rooms are occupied at that time.

What is the overall time complexity of the optimal Meeting Rooms solution?

A O(n)

B O(n^2)

C O(n log n)

D O(log n)

Sorting and heap operations lead to O(n log n) complexity.

Explain step-by-step how to find the minimum number of meeting rooms required given a list of meeting intervals.

Think about how to track overlapping meetings efficiently.

Describe how a min-heap helps optimize room allocation in the Meeting Rooms Problem.

Focus on how the heap manages meeting end times.

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 earliest meeting start time

B. The maximum length of a single meeting

C. The minimum number of meeting rooms needed so no meetings overlap

D. The total number of meetings scheduled

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 how many meetings happen at the same time to find the minimum rooms required.

3. Final Answer:

   The minimum number of meeting rooms needed so no meetings overlap -> Option C

4. Quick Check:

   Minimum rooms = max overlapping meetings [OK]

Hint: Count max overlapping intervals to find rooms needed [OK]

Common Mistakes:

• Confusing total meetings with rooms needed
• Ignoring overlapping times
• Thinking earliest start time is the answer

2. Which Go data structure is best to store meeting intervals for solving the minimum rooms problem?

easy

A. [][]int

B. string

C. map[int]int

D. chan int

Solution

1. Step 1: Identify suitable data structure for intervals

   Meeting intervals have start and end times, so a slice of slices ([][]int) is ideal to store pairs.

2. Step 2: Check other options

   map[int]int is less natural for intervals, string can't hold numeric ranges, chan int is for concurrency, not intervals.

3. Final Answer:

   [][]int -> Option A

4. Quick Check:

   Intervals stored as pairs in [][]int [OK]

Hint: Use [][]int to hold start and end times pairs [OK]

Common Mistakes:

• Using map which doesn't keep order
• Trying to store intervals as strings
• Using channels which are unrelated here

3. What is the output of the following Go code snippet that calculates minimum meeting rooms needed?

intervals := [][]int{{0, 30}, {5, 10}, {15, 20}}
rooms := minMeetingRooms(intervals)
fmt.Println(rooms)

func minMeetingRooms(intervals [][]int) int {
    starts := []int{}
    ends := []int{}
    for _, interval := range intervals {
        starts = append(starts, interval[0])
        ends = append(ends, interval[1])
    }
    sort.Ints(starts)
    sort.Ints(ends)
    rooms, endIndex := 0, 0
    for i := 0; i < len(starts); i++ {
        if starts[i] < ends[endIndex] {
            rooms++
        } else {
            endIndex++
        }
    }
    return rooms
}

medium

A. 1

B. 2

C. 3

D. 0

Solution

1. Step 1: Sort start and end times

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

2. Step 2: Iterate and count rooms

   At start=0 < end=10, rooms=1; start=5 < end=10, rooms=2; start=15 >= end=10, endIndex++, rooms=2

3. Final Answer:

   2 -> Option B

4. Quick Check:

   Max overlapping meetings = 2 [OK]

Hint: Sort starts and ends, count overlaps to find rooms [OK]

Common Mistakes:

• Not sorting start and end times
• Incrementing rooms incorrectly
• Confusing start and end comparisons

4. Find the bug in this Go function for minimum meeting rooms:

func minMeetingRooms(intervals [][]int) int {
    starts := []int{}
    ends := []int{}
    for _, interval := range intervals {
        starts = append(starts, interval[0])
        ends = append(ends, interval[1])
    }
    sort.Ints(starts)
    sort.Ints(ends)
    rooms := 0
    endIndex := 0
    for i := 0; i <= len(starts); i++ {
        if starts[i] < ends[endIndex] {
            rooms++
        } else {
            endIndex++
        }
    }
    return rooms
}

medium

A. Loop condition should be i < len(starts), not <= to avoid out-of-range

B. Should sort starts and ends in descending order

C. Should compare starts[i] > ends[endIndex] instead

D. Should initialize rooms to 1 instead of 0

Solution

1. Step 1: Check loop boundary

   The loop uses i <= len(starts), which causes index out-of-range error because valid indices are 0 to len(starts)-1.

2. Step 2: Correct loop condition

   Change to i < len(starts) to safely iterate over all elements.

3. Final Answer:

   Loop condition should be i < len(starts), not <= to avoid out-of-range -> Option A

4. Quick Check:

   Index error fixed by proper loop bounds [OK]

Hint: Use < not <= in loops to avoid index errors [OK]

Common Mistakes:

• Using <= instead of < in for loops
• Sorting in wrong order
• Wrong comparison operators

5. Given meeting intervals [[1,4],[2,5],[7,9],[6,8],[9,10]], what is the minimum number of meeting rooms required?

hard

A. 3

B. 1

C. 4

D. 2

Solution

1. Step 1: Sort start and end times

   Starts = [1,2,6,7,9], Ends = [4,5,8,9,10]

2. Step 2: Count overlaps to find rooms

   i=0 start=1 < end=4 rooms=1 i=1 start=2 < end=4 rooms=2 i=2 start=6 >= end=4 endIndex=1 rooms=2 i=3 start=7 >= end=5 endIndex=2 rooms=2 i=4 start=9 >= end=8 endIndex=3 rooms=2

3. Final Answer:

   2 -> Option D

4. Quick Check:

   Max overlaps = 2 rooms needed [OK]

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

Common Mistakes:

• Not sorting intervals before processing
• Miscounting overlaps at boundaries
• Assuming one room per meeting always