Merge Sort Algorithm in DSA C - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is the main idea behind the Merge Sort algorithm?

Merge Sort divides the list into two halves, sorts each half, and then merges the two sorted halves back together.

beginner

What is the time complexity of Merge Sort in the average and worst cases?

The time complexity of Merge Sort is O(n log n) in both average and worst cases.

intermediate

Why does Merge Sort use extra space during sorting?

Merge Sort uses extra space because it creates temporary arrays to hold the divided parts and to merge them back in sorted order.

beginner

Show the step-by-step merge process for merging two sorted arrays: [1, 4, 7] and [2, 3, 6].

Start comparing first elements: 1 < 2, so 1 goes first. Then 4 > 2, so 2 goes next. Then 4 > 3, so 3 goes next. Then 4 < 6, so 4 goes next. Then 7 > 6, so 6 goes next. Finally, 7 goes last. Result: [1, 2, 3, 4, 6, 7].

beginner

What is the base case in the recursive Merge Sort algorithm?

The base case is when the list has one or zero elements, which means it is already sorted and no further division is needed.

What technique does Merge Sort use to sort an array?

A Divide and conquer

B Greedy approach

C Dynamic programming

D Brute force

Merge Sort splits the array into halves, sorts them, and merges them back, which is divide and conquer.

What is the space complexity of Merge Sort?

A O(1)

B O(n)

C O(log n)

D O(n log n)

Merge Sort requires extra space proportional to the size of the array for temporary arrays during merging.

Which of the following is true about Merge Sort's stability?

A Merge Sort is stable

B Merge Sort is unstable

C Merge Sort stability depends on implementation

D Merge Sort is never stable

Merge Sort preserves the order of equal elements, so it is stable.

What happens when the array size reaches 1 in Merge Sort?

A The algorithm stops completely

B The array is merged immediately

C The array is split further

D The array is considered sorted

An array with one element is already sorted, so recursion stops dividing further.

Which step is NOT part of the Merge Sort algorithm?

A Merging sorted halves

B Sorting each half recursively

C Swapping adjacent elements repeatedly

D Splitting the array into halves

Swapping adjacent elements repeatedly is a characteristic of Bubble Sort, not Merge Sort.

Explain how Merge Sort works step-by-step on an unsorted array.

Think about breaking down the problem and combining solutions.

Describe the advantages and disadvantages of using Merge Sort.

Consider time, space, and stability.

Practice

1. What is the main idea behind the Merge Sort algorithm?

easy

A. Insert elements one by one into a sorted sublist

B. Divide the array into halves, sort each half, then merge them

C. Select a pivot and partition the array around it

D. Sort the array by repeatedly swapping adjacent elements

Solution

1. Step 1: Understand the divide and conquer approach

   Merge Sort splits the array into two halves recursively until single elements remain.

2. Step 2: Merge sorted halves

   It then merges these sorted halves to produce a fully sorted array.

3. Final Answer:

   Divide the array into halves, sort each half, then merge them -> Option B

4. Quick Check:

   Merge Sort = Divide and conquer [OK]

Hint: Remember: split, sort halves, then merge [OK]

Common Mistakes:

• Confusing Merge Sort with Bubble Sort
• Thinking Merge Sort uses a pivot like Quick Sort
• Believing Merge Sort sorts in place without extra space

2. Which of the following is the correct way to declare the merge function header in C for Merge Sort?

easy

A. void merge(int arr[], int left, int mid, int right);

B. int merge(int arr, int left, int mid, int right);

C. void merge(int arr, int left, int mid, int right);

D. int merge(int arr[], int left, int right);

Solution

1. Step 1: Check parameter types for merge function

   The array should be passed as int arr[] and indices as integers.

2. Step 2: Confirm return type

   Merge function usually returns nothing (void) as it modifies the array in place.

3. Final Answer:

   void merge(int arr[], int left, int mid, int right); -> Option A

4. Quick Check:

   Correct signature = void merge(int arr[], int left, int mid, int right); [OK]

Hint: Array as int arr[], return void for merge [OK]

Common Mistakes:

• Passing array as int arr instead of int arr[]
• Using int return type instead of void
• Missing the mid parameter needed for merging

3. What will be the output of the following code snippet after calling mergeSort(arr, 0, 4); on int arr[] = {5, 3, 8, 4, 2};?

void merge(int arr[], int left, int mid, int right) {
    int n1 = mid - left + 1;
    int n2 = right - mid;
    int L[n1], R[n2];
    for (int i = 0; i < n1; i++) L[i] = arr[left + i];
    for (int j = 0; j < n2; j++) R[j] = arr[mid + 1 + j];
    int i = 0, j = 0, k = left;
    while (i < n1 && j < n2) {
        if (L[i] <= R[j]) arr[k++] = L[i++];
        else arr[k++] = R[j++];
    }
    while (i < n1) arr[k++] = L[i++];
    while (j < n2) arr[k++] = R[j++];
}

void mergeSort(int arr[], int left, int right) {
    if (left < right) {
        int mid = left + (right - left) / 2;
        mergeSort(arr, left, mid);
        mergeSort(arr, mid + 1, right);
        merge(arr, left, mid, right);
    }
}

medium

A. [3, 5, 4, 2, 8]

B. [5, 3, 8, 4, 2]

C. [2, 3, 4, 5, 8]

D. [8, 5, 4, 3, 2]

Solution

1. Step 1: Understand recursive splitting

   The array is split into halves recursively until single elements remain: [5,3,8,4,2] -> [5,3,8] and [4,2], then further splits.

2. Step 2: Merge sorted halves step-by-step

   After sorting and merging, the final array becomes sorted in ascending order: [2, 3, 4, 5, 8].

3. Final Answer:

   [2, 3, 4, 5, 8] -> Option C

4. Quick Check:

   Sorted array = [2,3,4,5,8] [OK]

Hint: Merge Sort always returns sorted array ascending [OK]

Common Mistakes:

• Assuming original array remains unchanged
• Confusing mergeSort with other sorting algorithms
• Forgetting to merge after recursive calls

4. Identify the error in the following merge function snippet used in Merge Sort:

void merge(int arr[], int left, int mid, int right) {
    int n1 = mid - left + 1;
    int n2 = right - mid;
    int L[n1], R[n2];
    for (int i = 0; i <= n1; i++) L[i] = arr[left + i];
    for (int j = 0; j <= n2; j++) R[j] = arr[mid + 1 + j];
    int i = 0, j = 0, k = left;
    while (i < n1 && j < n2) {
        if (L[i] <= R[j]) arr[k++] = L[i++];
        else arr[k++] = R[j++];
    }
    while (i < n1) arr[k++] = L[i++];
    while (j < n2) arr[k++] = R[j++];
}

medium

A. The array sizes n1 and n2 are calculated incorrectly

B. The merge function should return an int instead of void

C. The while loops conditions should be i <= n1 and j <= n2

D. The for loops use <= instead of < causing out-of-bounds access

Solution

1. Step 1: Check for loop boundary errors

   The for loops use <= which causes the loop to run one extra time, leading to out-of-bounds array access.

2. Step 2: Correct loop conditions

   Changing <= to < fixes the loops to iterate exactly n1 and n2 times without overflow.

3. Final Answer:

   The for loops use <= instead of < causing out-of-bounds access -> Option D

4. Quick Check:

   Loop boundary off by one = The for loops use <= instead of < causing out-of-bounds access [OK]

Hint: Use <, not <=, for array index loops [OK]

Common Mistakes:

• Using <= in loops causing overflow
• Confusing return type of merge function
• Changing while loop conditions incorrectly

5. Given an array int arr[] = {12, 11, 13, 5, 6, 7};, how many total merge operations will be performed during a full Merge Sort on this array?

hard

A. 5

B. 7

C. 6

D. 8

Solution

1. Step 1: Understand merge operations count

   For an array of size n, Merge Sort performs n-1 merge operations combining subarrays stepwise.

2. Step 2: Calculate for n=6

   Here, n=6, so total merges = 6 - 1 = 5 merges.

3. Step 3: Count merges carefully

   Levels: - Level 1: 3 merges (pairs of size 1) - Level 2: 2 merges (subarrays of size 2 and 3) Total merges = 3 + 2 = 5 merges.

4. Final Answer:

   5 -> Option A

5. Quick Check:

   Count merges per level = 5 [OK]

Hint: Count merges per level, sum all levels [OK]

Common Mistakes:

• Assuming merges = n-1 without counting levels
• Counting only one level of merges
• Confusing merge operations with comparisons