Next Permutation of Array in DSA Python - Time & Space Complexity

Time Complexity: Next Permutation of Array

O(n)

Understanding Time Complexity

We want to understand how the time needed to find the next permutation changes as the array size grows.

Specifically, how many steps does the algorithm take when the array gets bigger?

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

def next_permutation(nums):
    i = len(nums) - 2
    while i >= 0 and nums[i] >= nums[i + 1]:
        i -= 1
    if i >= 0:
        j = len(nums) - 1
        while nums[j] <= nums[i]:
            j -= 1
        nums[i], nums[j] = nums[j], nums[i]
    nums[i + 1:] = reversed(nums[i + 1:])

This code finds the next lexicographical permutation of the input list of numbers.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: Two while loops scanning parts of the array and one slice reversal.
• How many times: Each loop runs at most once from the end towards the start, scanning up to n elements.

How Execution Grows With Input

As the array size grows, the loops and reversal may scan more elements, but each step still goes through the array at most once.

Input Size (n)	Approx. Operations
10	Up to about 30 steps
100	Up to about 300 steps
1000	Up to about 3000 steps

Pattern observation: The number of steps grows roughly in direct proportion to the input size.

Final Time Complexity

Time Complexity: O(n)

This means the time to find the next permutation grows linearly with the size of the array.

Common Mistake

[X] Wrong: "The algorithm checks all possible permutations, so it must be factorial time."

[OK] Correct: The algorithm smartly finds the next permutation by scanning the array only a few times, not generating all permutations.

Interview Connect

Understanding this linear time approach shows you can handle array manipulation efficiently, a skill often needed in real coding problems.

Self-Check

"What if the input array is already the highest permutation? How does that affect the time complexity?"

Practice

1. What does the next permutation of an array represent?

easy

A. The next lexicographically greater arrangement of the array elements

B. The array sorted in ascending order

C. The array reversed

D. The smallest element moved to the front

Solution

1. Step 1: Understand the concept of permutation order

   Permutations can be ordered lexicographically like words in a dictionary.

2. Step 2: Define next permutation meaning

   The next permutation is the next arrangement that is just greater than the current one in this order.

3. Final Answer:

   The next lexicographically greater arrangement of the array elements -> Option A

4. Quick Check:

   Next permutation = next bigger arrangement [OK]

Hint: Next permutation means next bigger order arrangement [OK]

Common Mistakes:

• Thinking next permutation is just sorting ascending
• Confusing next permutation with reversing the array
• Assuming next permutation always moves smallest element front

2. Which of the following Python code snippets correctly swaps two elements arr[i] and arr[j] in an array?

easy

A. arr[i], arr[j] = arr[j], arr[i]

B. arr[i] = arr[j]; arr[j] = arr[i]

C. swap(arr[i], arr[j])

D. arr[i] = arr[j]

Solution

1. Step 1: Recall Python tuple unpacking for swapping

   Python allows swapping two variables in one line using tuple unpacking.

2. Step 2: Check each option

   arr[i], arr[j] = arr[j], arr[i] correctly swaps using arr[i], arr[j] = arr[j], arr[i]. arr[i] = arr[j]; arr[j] = arr[i] overwrites arr[i] before assigning arr[j]. swap(arr[i], arr[j]) is invalid syntax without a defined function. arr[i] = arr[j] only assigns one element.

3. Final Answer:

   arr[i], arr[j] = arr[j], arr[i] -> Option A

4. Quick Check:

   Python swap uses tuple unpacking [OK]

Hint: Use tuple unpacking to swap in Python [OK]

Common Mistakes:

• Overwriting one element before swapping
• Using undefined swap function
• Assigning only one element instead of both

3. What is the output of the following code snippet?

arr = [1, 3, 2]
# Apply next permutation logic
# Step 1: Find first decreasing element from right (index 0)
# Step 2: Find element just larger than arr[0] from right (index 2)
# Step 3: Swap arr[0] and arr[2]
# Step 4: Reverse elements after index 0

arr[0], arr[2] = arr[2], arr[0]
arr[1:] = arr[1:][::-1]
print(arr)

medium

A. [3, 1, 2]

B. [2, 1, 3]

C. [1, 2, 3]

D. [2, 3, 1]

Solution

1. Step 1: Identify the first decreasing element from right

   From right, arr[1]=3 > arr[2]=2 (not decreasing), arr[0]=1 < arr[1]=3 (decreasing at index 0)

2. Step 2: Find element just larger than arr[0] from right

   From right, arr[2]=2 > arr[0]=1, so index 2 chosen

3. Step 3: Swap arr[0] and arr[2]

   Swap 1 and 2 -> arr becomes [2, 3, 1]

4. Step 4: Reverse elements after index 0

   Reverse arr[1:] -> arr[1:] = [3,1] reversed to [1,3]

5. Final Answer:

   [2, 1, 3] -> Option B

6. Quick Check:

   Next permutation of [1,3,2] = [2,1,3] [OK]

Hint: Swap pivot with next bigger, then reverse suffix [OK]

Common Mistakes:

• Not reversing suffix after swap
• Swapping wrong elements
• Confusing increasing and decreasing order

4. The following code attempts to find the next permutation of arr = [3, 2, 1]. What is the error?

def next_permutation(arr):
    i = len(arr) - 2
    while i >= 0 and arr[i] >= arr[i + 1]:
        i -= 1
    if i >= 0:
        j = len(arr) - 1
        while arr[j] <= arr[i]:
            j -= 1
        arr[i], arr[j] = arr[j], arr[i]
    arr[i + 1:] = reversed(arr[i + 1:])

arr = [3, 2, 1]
next_permutation(arr)
print(arr)

medium

A. The while loop condition is incorrect

B. Swapping elements is done in wrong order

C. Using reversed() returns an iterator, not a list, causing wrong assignment

D. The function does not handle empty arrays

Solution

1. Step 1: Analyze the reversal line

   The line arr[i + 1:] = reversed(arr[i + 1:]) assigns an iterator to a list slice, which expects a list.

2. Step 2: Identify correct usage

   To assign reversed elements properly, convert iterator to list: arr[i + 1:] = list(reversed(arr[i + 1:])).

3. Final Answer:

   Using reversed() returns an iterator, not a list, causing wrong assignment -> Option C

4. Quick Check:

   reversed() needs list() for slice assignment [OK]

Hint: Use list(reversed(...)) when assigning slices [OK]

Common Mistakes:

• Assigning reversed() iterator directly to list slice
• Ignoring empty array edge case
• Swapping elements incorrectly

5. Given the array arr = [1, 5, 1], what is the next permutation after applying the standard algorithm? Consider duplicates carefully.

hard

A. [5, 1, 5]

B. [1, 1, 5]

C. [1, 5, 1]

D. [5, 1, 1]

Solution

1. Step 1: Find first decreasing element from right

   From right: arr[1]=5 > arr[2]=1 (not decreasing), arr[0]=1 < arr[1]=5 (decreasing at index 0)

2. Step 2: Find element just larger than arr[0] from right

   From right, arr[2]=1 not > 1, arr[1]=5 > 1, so index 1 chosen

3. Step 3: Swap arr[0] and arr[1]

   Swap 1 and 5 -> arr becomes [5, 1, 1]

4. Step 4: Reverse elements after index 0

   Reverse arr[1:] -> arr[1:] = [1,1] reversed is same [1,1]

5. Final Answer:

   [5, 1, 1] -> Option D

6. Quick Check:

   Duplicates handled, next permutation = [5,1,1] [OK]

Hint: Swap pivot with next bigger, reverse suffix even with duplicates [OK]

Common Mistakes:

• Ignoring duplicates when finding next bigger element
• Not reversing suffix after swap
• Assuming next permutation is sorted ascending always