Merge Overlapping Intervals in DSA C++ - Time & Space Complexity

Time Complexity: Merge Overlapping Intervals

O(n log n)

Understanding Time Complexity

We want to understand how the time needed to merge overlapping intervals changes as the number of intervals grows.

How does the program's work increase when we have more intervals to merge?

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

#include <vector>
#include <algorithm>
using namespace std;

vector<vector<int>> mergeIntervals(vector<vector<int>> &intervals) {
    sort(intervals.begin(), intervals.end());
    vector<vector<int>> merged;
    for (auto &interval : intervals) {
        if (merged.empty() || merged.back()[1] < interval[0]) {
            merged.push_back(interval);
        } else {
            merged.back()[1] = max(merged.back()[1], interval[1]);
        }
    }
    return merged;
}
    

This code sorts intervals and then merges any that overlap into one combined interval.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: Sorting the list of intervals and then looping through each interval once.
• How many times: Sorting takes multiple comparisons depending on number of intervals (n), and the loop runs exactly n times.

How Execution Grows With Input

Sorting grows faster than just looping, so it dominates the time needed.

Input Size (n)	Approx. Operations
10	About 10 * log 10 ≈ 33 operations
100	About 100 * log 100 ≈ 664 operations
1000	About 1000 * log 1000 ≈ 9966 operations

Pattern observation: As input size grows, operations grow a bit faster than just doubling, because sorting costs increase with n log n.

Final Time Complexity

Time Complexity: O(n log n)

This means the time needed grows a little faster than the number of intervals because sorting takes extra work, but merging after sorting is just a simple pass.

Common Mistake

[X] Wrong: "The merging loop alone decides the time complexity, so it is O(n)."

[OK] Correct: Sorting the intervals first takes more time than the loop, so the sorting step actually controls the overall time needed.

Interview Connect

Understanding how sorting affects the merging process helps you explain your solution clearly and shows you know how to analyze combined steps in algorithms.

Self-Check

"What if the intervals were already sorted? How would the time complexity change?"

Practice

1. What is the main purpose of the Merge Overlapping Intervals algorithm?

easy

A. To find the maximum interval length

B. To combine all intervals that overlap into a single continuous interval

C. To sort intervals in descending order

D. To remove all intervals that overlap

Solution

1. Step 1: Understand the problem goal

   The algorithm aims to merge intervals that share common parts so they become one continuous interval.

2. Step 2: Clarify what merging means

   Merging means combining overlapping intervals into one that covers the entire range of those intervals.

3. Final Answer:

   To combine all intervals that overlap into a single continuous interval -> Option B

4. Quick Check:

   Merge overlapping intervals = combine overlaps [OK]

Hint: Think of joining overlapping time slots into one [OK]

Common Mistakes:

• Confusing merging with sorting
• Thinking it removes intervals instead of combining
• Assuming it finds max length only

2. Which of the following C++ code snippets correctly sorts a vector of intervals by their start time before merging?

easy

A. std::sort(intervals.begin(), intervals.end(), [](auto &a, auto &b) { return a[0] < b[0]; });

B. std::sort(intervals.begin(), intervals.end(), [](auto &a, auto &b) { return a[1] > b[1]; });

C. std::sort(intervals.begin(), intervals.end(), [](auto &a, auto &b) { return a[1] < b[1]; });

D. std::sort(intervals.begin(), intervals.end(), [](auto &a, auto &b) { return a[0] > b[0]; });

Solution

1. Step 1: Identify sorting by start time

   We need to sort intervals by their first element (start time) in ascending order.

2. Step 2: Check lambda comparator correctness

   std::sort(intervals.begin(), intervals.end(), [](auto &a, auto &b) { return a[0] < b[0]; }); uses a lambda that compares a[0] < b[0], which sorts ascending by start time correctly.

3. Final Answer:

   std::sort(intervals.begin(), intervals.end(), [](auto &a, auto &b) { return a[0] < b[0]; }); -> Option A

4. Quick Check:

   Sort by start ascending = a[0] < b[0] [OK]

Hint: Sort intervals by start ascending using a lambda [OK]

Common Mistakes:

• Sorting by end time instead of start time
• Sorting in descending order
• Using default sort without comparator on vector of vectors

3. What is the output of the following C++ code that merges overlapping intervals?

std::vector intervals = {{1,3},{2,6},{8,10},{15,18}};
// After merging overlapping intervals
// Print merged intervals
for (auto &interval : merged) {
    std::cout << "[" << interval[0] << "," << interval[1] << "] ";
}

medium

A. [1,6] [8,10] [15,18]

B. [1,3] [2,6] [8,10] [15,18]

C. [1,6] [2,6] [8,10] [15,18]

D. [1,3] [8,10] [15,18]

Solution

1. Step 1: Sort intervals by start time

   Sorted intervals: [1,3], [2,6], [8,10], [15,18]

2. Step 2: Merge overlapping intervals

   [1,3] and [2,6] overlap, merge to [1,6]. Others remain separate.

3. Final Answer:

   [1,6] [8,10] [15,18] -> Option A

4. Quick Check:

   Merged intervals = [1,6], [8,10], [15,18] [OK]

Hint: Merge intervals by expanding end if overlap found [OK]

Common Mistakes:

• Not merging overlapping intervals
• Printing original intervals without merge
• Merging incorrectly leaving duplicates

4. Identify the bug in this C++ code snippet for merging intervals:

std::vector mergeIntervals(std::vector &intervals) {
    std::vector merged;
    for (auto &interval : intervals) {
        if (merged.empty() || merged.back()[1] < interval[0]) {
            merged.push_back(interval);
        } else {
            merged.back()[1] = std::max(merged.back()[1], interval[1]);
        }
    }
    return merged;
}

medium

A. Pushing intervals without checking overlap

B. Using std::max incorrectly

C. Intervals are not sorted before merging

D. Returning merged by reference instead of value

Solution

1. Step 1: Check preconditions for merging

   Merging requires intervals sorted by start time to work correctly.

2. Step 2: Identify missing sorting step

   The code does not sort intervals before merging, so overlapping intervals may be missed.

3. Final Answer:

   Intervals are not sorted before merging -> Option C

4. Quick Check:

   Sort intervals first to merge correctly [OK]

Hint: Always sort intervals by start before merging [OK]

Common Mistakes:

• Skipping sorting step
• Assuming input is sorted
• Misusing std::max function

5. Given intervals [[1,4],[4,5],[7,9],[8,10]], what is the merged output after applying the merge overlapping intervals algorithm?

hard

A. [[1,10]]

B. [[1,4],[4,5],[7,9],[8,10]]

C. [[1,4],[5,7],[8,10]]

D. [[1,5],[7,10]]

Solution

1. Step 1: Sort intervals by start time

   Intervals are already sorted: [1,4], [4,5], [7,9], [8,10]

2. Step 2: Merge overlapping or touching intervals

   [1,4] and [4,5] touch at 4, merge to [1,5]. [7,9] and [8,10] overlap, merge to [7,10].

3. Final Answer:

   [[1,5],[7,10]] -> Option D

4. Quick Check:

   Touching intervals merge too [OK]

Hint: Merge intervals that overlap or touch at boundaries [OK]

Common Mistakes:

• Not merging intervals that touch at endpoints
• Leaving intervals separate when they overlap
• Merging all intervals incorrectly into one