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

Time Complexity: Meeting Rooms Problem Minimum Rooms Required

O(n^3 log n)

Understanding Time Complexity

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

How does the code handle more meetings and what costs increase the most?

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

function minMeetingRooms(intervals) {
  intervals.sort((a, b) => a[0] - b[0]);
  const heap = [];
  for (const interval of intervals) {
    if (heap.length && heap[0] <= interval[0]) {
      heap.shift();
    }
    heap.push(interval[1]);
    heap.sort((a, b) => a - b);
  }
  return heap.length;
}
    

This code sorts meetings by start time, then uses a list to track end times of ongoing meetings 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: Sorting the heap array each time, which depends on the current heap size.

How Execution Grows With Input

As the number of meetings grows, the sorting inside the loop grows too because the heap can grow up to n in size.

Input Size (n)	Approx. Operations
10	About 10 times sorting small arrays (up to 10 elements)
100	About 100 times sorting arrays that can grow up to 100 elements
1000	About 1000 times sorting arrays that can grow up to 1000 elements

Pattern observation: The sorting inside the loop causes the total work to grow roughly with the cube of the input size.

Final Time Complexity

Time Complexity: O(n^3 log n)

This means the time needed grows very quickly as the number of meetings increases, mainly because sorting happens inside the loop.

Common Mistake

[X] Wrong: "Sorting once at the start means the whole code runs in O(n log n)."

[OK] Correct: Sorting inside the loop for each meeting adds extra cost, making the total time much larger than just the initial sort.

Interview Connect

Understanding how nested sorting affects time helps you explain and improve solutions in interviews confidently.

Self-Check

"What if we used a priority queue (min-heap) instead of sorting the heap array each time? 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 minimum number of meeting rooms needed so no meetings overlap

B. The maximum length of a single meeting

C. The total number of meetings scheduled

D. The earliest meeting start time

Solution

1. Step 1: Understand the problem goal

   The problem asks for the minimum number of rooms required 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 needed.

3. Final Answer:

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

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 of the following JavaScript code snippets correctly sorts an array of meeting intervals by their start time? Assume intervals is an array of objects with 'start' and 'end' properties.

easy

A. intervals.sort((a, b) => b.end - a.end);

B. intervals.sort((a, b) => b.start - a.start);

C. intervals.sort((a, b) => a.end - b.end);

D. intervals.sort((a, b) => a.start - b.start);

Solution

1. Step 1: Identify sorting by start time

   We want to sort intervals by their start property in ascending order.

2. Step 2: Check the sort function

   The comparator (a, b) => a.start - b.start sorts ascending by start time.

3. Final Answer:

   intervals.sort((a, b) => a.start - b.start); -> Option D

4. Quick Check:

   Ascending start time sort = intervals.sort((a, b) => a.start - b.start); [OK]

Hint: Sort intervals by start ascending: (a,b) => a.start - b.start [OK]

Common Mistakes:

• Sorting by end time instead of start
• Sorting descending when ascending needed
• Using incorrect comparator syntax

3. What is the minimum number of meeting rooms required for the following intervals?
const intervals = [{start: 0, end: 30}, {start: 5, end: 10}, {start: 15, end: 20}];

medium

A. 1

B. 2

C. 3

D. 4

Solution

1. Step 1: Analyze overlapping intervals

   Meetings: [0-30], [5-10], [15-20]. The first overlaps with the second and third.

2. Step 2: Count max overlaps

   At time 5-10, two meetings overlap (0-30 and 5-10). At 15-20, two meetings overlap (0-30 and 15-20). Max overlap is 2.

3. Final Answer:

   2 -> Option B

4. Quick Check:

   Max overlapping meetings = 2 rooms needed [OK]

Hint: Find max overlaps by checking intervals start and end times [OK]

Common Mistakes:

• Counting total meetings instead of overlaps
• Assuming 3 rooms because 3 meetings exist
• Ignoring overlap intervals

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

function minMeetingRooms(intervals) {
  intervals.sort((a, b) => a.start - b.start);
  let rooms = [];
  for (let meeting of intervals) {
    if (rooms.length === 0 || meeting.start < rooms[rooms.length - 1]) {
      rooms.push(meeting.end);
    } else {
      rooms[rooms.length - 1] = meeting.end;
    }
  }
  return rooms.length;
}

medium

A. It returns the wrong value (should return rooms array)

B. It sorts intervals by end time instead of start time

C. It compares meeting.start with a number incorrectly (rooms array stores end times, but comparison is wrong)

D. It uses push instead of unshift on rooms array

Solution

1. Step 1: Understand rooms array usage

   Rooms array stores end times of meetings currently occupying rooms.

2. Step 2: Check comparison logic

   Comparing meeting.start with rooms[rooms.length - 1] (last end time) is incorrect because rooms should be a min-heap or sorted structure, not just last element.

3. Final Answer:

   It compares meeting.start with a number incorrectly (rooms array stores end times, but comparison is wrong) -> Option C

4. Quick Check:

   Incorrect comparison of start with last end time causes bug [OK]

Hint: Use a min-heap or sorted structure for end times, not last element [OK]

Common Mistakes:

• Comparing start with last end time without sorting
• Not using a priority queue for room end times
• Returning wrong variable

5. Given the intervals [[1,4],[2,5],[7,9],[6,10],[8,11]], what is the minimum number of meeting rooms required? Explain your reasoning.

hard

A. 3

B. 2

C. 4

D. 5

Solution

1. Step 1: Sort intervals by start time

   Sorted intervals: [1,4], [2,5], [6,10], [7,9], [8,11]

2. Step 2: Track overlapping meetings

   Between 1-5, two meetings overlap ([1,4] and [2,5]). Between 6-11, three meetings overlap ([6,10], [7,9], [8,11]). Max overlap is 3.

3. Final Answer:

   3 -> Option A

4. Quick Check:

   Max overlapping meetings = 3 rooms needed [OK]

Hint: Find max overlaps by checking intervals start and end times carefully [OK]

Common Mistakes:

• Not sorting intervals before checking overlaps
• Counting total meetings instead of max overlaps
• Missing overlaps in later intervals