Generate All Permutations of Array in DSA Rust - Time & Space Complexity

Time Complexity: Generate All Permutations of Array

O(n!)

Understanding Time Complexity

When we generate all permutations of an array, we want to know how the time needed grows as the array gets bigger.

We ask: How does the number of steps change when the array length increases?

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

fn permute(nums: &mut Vec<i32>, start: usize, result: &mut Vec<Vec<i32>>) {
    if start == nums.len() {
        result.push(nums.clone());
        return;
    }
    for i in start..nums.len() {
        nums.swap(start, i);
        permute(nums, start + 1, result);
        nums.swap(start, i);
    }
}

This code generates all possible orderings (permutations) of the input array by swapping elements recursively.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: Recursive calls generating permutations by swapping elements.
• How many times: The recursion explores every possible ordering, which is factorial in number of elements.

How Execution Grows With Input

Each time we add one more element, the number of permutations multiplies by that new number.

Input Size (n)	Approx. Operations
3	6 (3 x 2 x 1)
5	120 (5 x 4 x 3 x 2 x 1)
7	5,040 (7 x 6 x 5 x 4 x 3 x 2 x 1)

Pattern observation: The number of operations grows very fast, multiplying by the new input size each time.

Final Time Complexity

Time Complexity: O(n!)

This means the time needed grows very fast as the array gets bigger, because we must check every possible order.

Common Mistake

[X] Wrong: "Generating permutations is just like looping through the array once, so it should be O(n)."

[OK] Correct: Each element can be in many positions, so we must explore all combinations, which grows factorially, not linearly.

Interview Connect

Understanding this complexity helps you explain why some problems need careful handling when input size grows, showing your grasp of algorithm limits.

Self-Check

"What if we only wanted permutations of length k from n elements? How would the time complexity change?"

Practice

1. What does the process of generating all permutations of an array mean?

easy

A. Listing all possible orders of the array elements

B. Sorting the array in ascending order

C. Removing duplicate elements from the array

D. Finding the maximum element in the array

Solution

1. Step 1: Understand permutations

   Permutations are all possible ways to arrange elements in order.

2. Step 2: Apply to array elements

   Generating all permutations means listing every possible order of the array elements.

3. Final Answer:

   Listing all possible orders of the array elements -> Option A

4. Quick Check:

   Permutations = all orders [OK]

Hint: Permutations = all possible orders of elements [OK]

Common Mistakes:

• Confusing permutations with sorting
• Thinking permutations remove duplicates
• Assuming permutations find max element

2. Which Rust code snippet correctly starts generating permutations of a vector vec![1, 2, 3] using recursion?

easy

A. fn permute(arr: &mut Vec<i32>, start: usize) { if start == arr.len() { println!("{:?}", arr); } else { for i in start..arr.len() { arr.swap(start, i); permute(arr, start + 1); arr.swap(start, i); } } }

B. fn permute(arr: Vec<i32>) { for i in 0..arr.len() { println!("{:?}", arr[i]); } }

C. fn permute(arr: &Vec<i32>) { println!("{:?}", arr); }

D. fn permute(arr: &mut Vec<i32>) { arr.sort(); println!("{:?}", arr); }

Solution

1. Step 1: Identify recursive permutation logic

   fn permute(arr: &mut Vec<i32>, start: usize) { if start == arr.len() { println!("{:?}", arr); } else { for i in start..arr.len() { arr.swap(start, i); permute(arr, start + 1); arr.swap(start, i); } } } uses recursion with swapping and backtracking to generate permutations.

2. Step 2: Check other options

   Options B, C, and D do not generate permutations; they only print or sort.

3. Final Answer:

   fn permute(arr: &mut Vec<i32>, start: usize) { if start == arr.len() { println!("{:?}", arr); } else { for i in start..arr.len() { arr.swap(start, i); permute(arr, start + 1); arr.swap(start, i); } } } -> Option A

4. Quick Check:

   Recursive swap + backtrack = fn permute(arr: &mut Vec<i32>, start: usize) { if start == arr.len() { println!("{:?}", arr); } else { for i in start..arr.len() { arr.swap(start, i); permute(arr, start + 1); arr.swap(start, i); } } } [OK]

Hint: Look for recursion with swap and backtrack [OK]

Common Mistakes:

• Not using mutable reference for swapping
• Missing recursive call
• Printing elements instead of permutations

3. What is the output of this Rust code snippet?

fn permute(arr: &mut Vec<i32>, start: usize) {
    if start == arr.len() {
        println!("{:?}", arr);
    } else {
        for i in start..arr.len() {
            arr.swap(start, i);
            permute(arr, start + 1);
            arr.swap(start, i);
        }
    }
}

fn main() {
    let mut v = vec![1, 2];
    permute(&mut v, 0);
}

medium

A. [1, 2]

B. [1, 2]
[2, 1]

C. [2, 1]

D. Compilation error

Solution

1. Step 1: Trace recursive calls for vec![1, 2]

   Start at index 0, swap with 0 and 1: - Swap(0,0): [1,2], print when start=2 - Swap(0,1): [2,1], print when start=2

2. Step 2: Confirm output lines

   Both permutations [1, 2] and [2, 1] are printed in order.

3. Final Answer:

   [1, 2] [2, 1] -> Option B

4. Quick Check:

   All permutations of [1,2] printed [OK]

Hint: Small array permutations = factorial length outputs [OK]

Common Mistakes:

• Expecting only one permutation output
• Confusing swap order
• Assuming compilation error

4. Identify the bug in this Rust code for generating permutations and select the fix:

fn permute(arr: Vec<i32>, start: usize) {
    if start == arr.len() {
        println!("{:?}", arr);
    } else {
        for i in start..arr.len() {
            let mut arr = arr.clone();
            arr.swap(start, i);
            permute(arr, start + 1);
        }
    }
}

fn main() {
    let v = vec![1, 2, 3];
    permute(v, 0);
}

medium

A. No bug, code works fine

B. Add mut keyword to v in main

C. Replace arr.swap with arr.reverse

D. Change parameter to mutable reference: arr: &mut Vec<i32> and remove cloning

Solution

1. Step 1: Analyze cloning and mutation

   Cloning arr each loop causes performance issues and unnecessary copies.

2. Step 2: Fix by using mutable reference

   Passing &mut Vec<i32> allows swapping in place and backtracking without cloning.

3. Final Answer:

   Change parameter to mutable reference: arr: &mut Vec<i32> and remove cloning -> Option D

4. Quick Check:

   Use mutable reference to avoid cloning [OK]

Hint: Use &mut Vec to swap without cloning [OK]

Common Mistakes:

• Cloning inside loop causes inefficiency
• Not using mutable reference for swaps
• Thinking adding mut to main vector fixes logic

5. Given a vector vec![1, 2, 2], how many unique permutations will the standard recursive swap method print without filtering duplicates?

hard

A. 2

B. 3

C. 6

D. 1

Solution

1. Step 1: Calculate total permutations without filtering

   For 3 elements, total permutations = 3! = 6.

2. Step 2: Consider duplicates in array

   Standard recursive swap method does not filter duplicates, so all 6 permutations including duplicates print.

3. Final Answer:

   6 -> Option C

4. Quick Check:

   3! = 6 permutations printed [OK]

Hint: Without filtering, duplicates cause factorial count [OK]

Common Mistakes:

• Assuming duplicates reduce output automatically
• Confusing unique permutations with total permutations
• Thinking output is 3 or 2 without filtering