Count Inversions in Array in DSA Rust - Time & Space Complexity

Time Complexity: Count Inversions in Array

O(n log n)

Understanding Time Complexity

We want to understand how long it takes to count inversions in an array as the array grows.

Specifically, how the number of steps changes when the array size increases.

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

fn merge_sort_count(arr: &mut [i32]) -> usize {
    let n = arr.len();
    if n <= 1 {
        return 0;
    }
    let mid = n / 2;
    let mut count = merge_sort_count(&mut arr[..mid]);
    count += merge_sort_count(&mut arr[mid..]);
    count += merge(arr, mid);
    count
}

fn merge(arr: &mut [i32], mid: usize) -> usize {
    let mut count = 0;
    let left = arr[..mid].to_vec();
    let right = arr[mid..].to_vec();
    let (mut i, mut j, mut k) = (0, 0, 0);
    while i < left.len() && j < right.len() {
        if left[i] <= right[j] {
            arr[k] = left[i];
            i += 1;
        } else {
            arr[k] = right[j];
            count += left.len() - i;
            j += 1;
        }
        k += 1;
    }
    while i < left.len() {
        arr[k] = left[i];
        i += 1;
        k += 1;
    }
    while j < right.len() {
        arr[k] = right[j];
        j += 1;
        k += 1;
    }
    count
}

This code counts how many pairs of elements are out of order by using a merge sort approach.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: Recursive splitting of the array and merging while counting inversions.
• How many times: The array is split into halves repeatedly until size 1, then merged back, processing all elements each time.

How Execution Grows With Input

Each time the array size doubles, the number of operations grows a bit more than double because of the merging steps.

Input Size (n)	Approx. Operations
10	About 50 steps
100	About 700 steps
1000	About 10,000 steps

Pattern observation: The operations grow a bit faster than linear but much slower than quadratic, roughly n times log n.

Final Time Complexity

Time Complexity: O(n log n)

This means the time to count inversions grows proportionally to the size of the array times the number of times it can be split in half.

Common Mistake

[X] Wrong: "Counting inversions must check every pair, so it always takes n squared time."

[OK] Correct: The merge sort method cleverly counts inversions while sorting, avoiding checking every pair directly, so it runs faster than n squared.

Interview Connect

Understanding this method shows you can combine sorting and counting efficiently, a skill useful in many algorithm problems.

Self-Check

"What if we used a simple nested loop to count inversions instead? How would the time complexity change?"

Practice

1. What does the term inversion mean in the context of an array?

easy

A. A pair of elements where the first is greater than the second and appears before it

B. A pair of elements where the first is smaller than the second and appears before it

C. The total number of elements in the array

D. The sum of all elements in the array

Solution

1. Step 1: Understand the definition of inversion

   An inversion is a pair of elements where the first element is greater than the second and appears before it in the array.

2. Step 2: Compare options with definition

   A pair of elements where the first is greater than the second and appears before it matches this definition exactly, while others describe different concepts.

3. Final Answer:

   A pair of elements where the first is greater than the second and appears before it -> Option A

4. Quick Check:

   Inversion = pair (i, j) with i < j and arr[i] > arr[j] [OK]

Hint: Inversion means earlier bigger number than a later one [OK]

Common Mistakes:

• Confusing inversion with sorted order
• Thinking inversion counts total elements
• Mixing up greater and smaller element order

2. Which Rust code snippet correctly declares a function to count inversions in an array slice?

easy

A. fn count_inversions(arr: &[i32]) -> i32 { 0 }

B. fn count_inversions(arr: Vec i32 { 0 }

C. fn count_inversions(arr: &[i32]) -> usize { 0 }

D. fn count_inversions(arr: &mut [i32]) -> usize { 0 }

Solution

1. Step 1: Identify correct function signature for counting inversions

   The function should take an immutable slice of integers and return the count as usize (non-negative integer).

2. Step 2: Compare options

   fn count_inversions(arr: &[i32]) -> usize { 0 } uses &[i32] for input and usize for output, which is correct. fn count_inversions(arr: Vec i32 { 0 } takes ownership (Vec) and returns i32 (can be negative). fn count_inversions(arr: &mut [i32]) -> usize { 0 } uses mutable slice unnecessarily. fn count_inversions(arr: &[i32]) -> i32 { 0 } returns i32 which can be negative, not ideal for count.

3. Final Answer:

   fn count_inversions(arr: &[i32]) -> usize { 0 } -> Option C

4. Quick Check:

   Immutable slice input + usize output = correct signature [OK]

Hint: Use &[i32] input and usize output for count functions [OK]

Common Mistakes:

• Using Vec instead of slice for input
• Returning signed integer for count
• Using mutable slice when not needed

3. What is the output of the following Rust code snippet counting inversions?

fn main() {
    let arr = [2, 4, 1, 3, 5];
    let mut count = 0;
    for i in 0..arr.len() {
        for j in i+1..arr.len() {
            if arr[i] > arr[j] {
                count += 1;
            }
        }
    }
    println!("{}", count);
}

medium

A. 4

B. 3

C. 2

D. 5

Solution

1. Step 1: Identify all inversion pairs in the array

   Array: [2, 4, 1, 3, 5]. Inversions are (2,1), (4,1), (4,3). Total 3 inversions.

2. Step 2: Confirm count from nested loops

   Loops check all pairs i < j. Each inversion increments count by 1. Final count is 3.

3. Final Answer:

   3 -> Option B

4. Quick Check:

   Count inversions by pairs = 3 [OK]

Hint: Count pairs where earlier number is bigger than later [OK]

Common Mistakes:

• Counting non-inversion pairs
• Missing some inversion pairs
• Confusing indices order

4. The following Rust code attempts to count inversions but has a bug. What is the bug?

fn count_inversions(arr: &[i32]) -> usize {
    let mut count = 0;
    for i in 0..arr.len() {
        for j in 0..arr.len() {
            if arr[i] > arr[j] {
                count += 1;
            }
        }
    }
    count
}

medium

A. Inner loop should start from i+1, not 0

B. Count variable should be i32, not usize

C. Function should take mutable slice

D. Comparison operator should be < instead of >

Solution

1. Step 1: Analyze loop ranges for counting inversions

   Inversion counts pairs where i < j and arr[i] > arr[j]. Inner loop starting at 0 compares all pairs including i >= j, causing double counting and invalid pairs.

2. Step 2: Correct inner loop start index

   Inner loop should start at i+1 to ensure only pairs with i < j are counted once.

3. Final Answer:

   Inner loop should start from i+1, not 0 -> Option A

4. Quick Check:

   Loop indices must ensure i < j for correct inversion count [OK]

Hint: Inner loop must start after outer index to avoid double count [OK]

Common Mistakes:

• Starting inner loop at 0 causing double counting
• Using wrong comparison operator
• Changing input slice to mutable unnecessarily

5. Given the array [8, 4, 2, 1], what is the number of inversions? Use the merge sort based approach to count inversions efficiently.

hard

A. 5

B. 3

C. 4

D. 6

Solution

1. Step 1: Understand merge sort inversion counting

   Merge sort counts inversions by counting how many elements from right subarray are placed before left subarray elements during merge.

2. Step 2: Count inversions in [8,4,2,1]

   Pairs: (8,4), (8,2), (8,1), (4,2), (4,1), (2,1) total 6 inversions.

3. Final Answer:

   6 -> Option D

4. Quick Check:

   All pairs where left > right count to 6 [OK]

Hint: Count pairs where left number bigger than right during merge [OK]

Common Mistakes:

• Counting only adjacent pairs
• Missing some inversion pairs
• Confusing merge sort steps