Radix Sort Algorithm in DSA Rust - Time & Space Complexity

Time Complexity: Radix Sort Algorithm

O(d * n)

Understanding Time Complexity

We want to understand how the time taken by Radix Sort changes as the input size grows.

Specifically, how the number of steps depends on the number of items and their digit length.

Scenario Under Consideration

Analyze the time complexity of the following Radix Sort code snippet.

fn radix_sort(arr: &mut [u32]) {
    let max = *arr.iter().max().unwrap_or(&0);
    let mut exp = 1;
    while max / exp > 0 {
        counting_sort_by_digit(arr, exp);
        exp *= 10;
    }
}

fn counting_sort_by_digit(arr: &mut [u32], exp: u32) {
    let mut output = vec![0; arr.len()];
    let mut count = vec![0; 10];
    for &num in arr.iter() {
        count[((num / exp) % 10) as usize] += 1;
    }
    for i in 1..10 {
        count[i] += count[i - 1];
    }
    for &num in arr.iter().rev() {
        let idx = ((num / exp) % 10) as usize;
        count[idx] -= 1;
        output[count[idx]] = num;
    }
    arr.copy_from_slice(&output);
}
    

This code sorts numbers by processing each digit from least to most significant using counting sort.

Identify Repeating Operations

Look for loops and repeated steps.

• Primary operation: Counting sort runs once per digit place.
• How many times: Number of digits in the largest number (d times).
• Inside counting sort, we loop over all n elements multiple times.

How Execution Grows With Input

For each digit, we do a counting sort over all n items.

Input Size (n)	Approx. Operations (d * n)
10	10 * d
100	100 * d
1000	1000 * d

Pattern observation: The time grows linearly with the number of items and also linearly with the number of digits.

Final Time Complexity

Time Complexity: O(d * n)

This means the time grows linearly with the number of items and the number of digits in the largest number.

Common Mistake

[X] Wrong: "Radix sort is always faster than comparison sorts like quicksort because it doesn't compare elements."

[OK] Correct: Radix sort depends on the number of digits (d). If d is large, it can be slower than efficient comparison sorts which are O(n log n). So it's not always faster.

Interview Connect

Understanding Radix Sort's time complexity helps you explain when it's a good choice and shows you can analyze algorithms beyond simple comparisons.

Self-Check

"What if the numbers were very large with many digits? How would that affect the time complexity?"

Practice

1. What is the main idea behind the Radix Sort Algorithm?

easy

A. Sort numbers by swapping adjacent elements repeatedly

B. Sort numbers by comparing each pair directly

C. Sort numbers by dividing them into two halves recursively

D. Sort numbers digit by digit starting from the least significant digit

Solution

1. Step 1: Understand Radix Sort approach

   Radix sort sorts numbers by processing each digit separately, starting from the least significant digit (rightmost).

2. Step 2: Compare with other sorting methods

   Unlike comparison-based sorts, radix sort uses digit positions to sort without direct element comparisons.

3. Final Answer:

   Sort numbers digit by digit starting from the least significant digit -> Option D

4. Quick Check:

   Radix sort = digit-by-digit sorting [OK]

Hint: Radix sort processes digits from right to left [OK]

Common Mistakes:

• Thinking radix sort compares elements directly
• Assuming it sorts by dividing arrays recursively
• Confusing it with bubble or quick sort methods

2. Which of the following Rust code snippets correctly initializes a vector to hold buckets for digits 0 to 9 in radix sort?

easy

A. let mut buckets: Vec = vec![Vec::new(); 10];

B. let buckets = Vec::with_capacity(10);

C. let buckets: Vec<i32> = vec![0; 10];

D. let mut buckets = vec![0; 10];

Solution

1. Step 1: Understand bucket structure needed

   Radix sort uses buckets as vectors of vectors to hold numbers for each digit (0-9).

2. Step 2: Check Rust syntax for initializing vector of vectors

   Using vec![Vec::new(); 10] creates 10 empty vectors, one for each digit bucket.

3. Final Answer:

   let mut buckets: Vec = vec![Vec::new(); 10]; -> Option A

4. Quick Check:

   Vector of vectors for buckets = let mut buckets: Vec = vec![Vec::new(); 10]; [OK]

Hint: Buckets need vectors inside a vector, not just integers [OK]

Common Mistakes:

• Using Vec<i32> instead of Vec for buckets
• Using with_capacity without initializing inner vectors
• Initializing buckets as integers instead of vectors

3. What will be the output of the following Rust code snippet implementing one pass of radix sort on the least significant digit?

let arr = vec![170, 45, 75, 90, 802, 24, 2, 66];
let mut buckets: Vec = vec![Vec::new(); 10];
for &num in &arr {
    let digit = num % 10;
    buckets[digit as usize].push(num);
}
let mut result = Vec::new();
for bucket in buckets {
    for num in bucket {
        result.push(num);
    }
}
println!("{:?}", result);

medium

A. [2, 802, 24, 45, 75, 66, 170, 90]

B. [170, 90, 802, 2, 24, 45, 75, 66]

C. [170, 802, 2, 24, 45, 75, 90, 66]

D. [802, 2, 24, 45, 75, 66, 170, 90]

Solution

1. Step 1: Calculate least significant digit for each number

   Digits: 170%10=0, 45%10=5, 75%10=5, 90%10=0, 802%10=2, 24%10=4, 2%10=2, 66%10=6.

2. Step 2: Place numbers in buckets and flatten

   Buckets: 0->[170,90], 2->[802,2], 4->[24], 5->[45,75], 6->[66]. Flattening in order: [170, 90, 802, 2, 24, 45, 75, 66].

3. Final Answer:

   [170, 90, 802, 2, 24, 45, 75, 66] -> Option B

4. Quick Check:

   Sorted by least digit = [170, 90, 802, 2, 24, 45, 75, 66] [OK]

Hint: Check digit % 10 and group accordingly [OK]

Common Mistakes:

• Mixing up digit extraction with division
• Not preserving order within buckets
• Incorrectly flattening buckets

4. Identify the bug in this Rust code snippet for one pass of radix sort and choose the fix:

let arr = vec![170, 45, 75];
let mut buckets: Vec = vec![Vec::new(); 10];
for num in arr {
    let digit = num / 10 % 10;
    buckets[digit].push(num);
}

medium

A. Change buckets[digit] to buckets[digit as usize]

B. Change num / 10 % 10 to num % 10

C. Initialize buckets with vec![0; 10] instead of vectors

D. Use for &num in &arr instead of for num in arr

Solution

1. Step 1: Identify type mismatch in indexing

   Variable digit is an integer but Rust requires usize for vector indexing.

2. Step 2: Fix by casting digit to usize

   Use buckets[digit as usize] to correctly index the vector.

3. Final Answer:

   Change buckets[digit] to buckets[digit as usize] -> Option A

4. Quick Check:

   Vector index must be usize = Change buckets[digit] to buckets[digit as usize] [OK]

Hint: Vector indices in Rust must be usize type [OK]

Common Mistakes:

• Using integer directly as vector index without casting
• Changing digit calculation unnecessarily
• Incorrect bucket initialization

5. Given the Rust function below that performs radix sort on a vector of positive integers, what will be the final sorted vector?

fn radix_sort(mut arr: Vec<i32>) -> Vec<i32> {
    let max = *arr.iter().max().unwrap();
    let mut exp = 1;
    while max / exp > 0 {
        let mut buckets: Vec = vec![Vec::new(); 10];
        for &num in &arr {
            let digit = (num / exp) % 10;
            buckets[digit as usize].push(num);
        }
        arr.clear();
        for bucket in buckets {
            for num in bucket {
                arr.push(num);
            }
        }
        exp *= 10;
    }
    arr
}

let input = vec![329, 457, 657, 839, 436, 720, 355];
let sorted = radix_sort(input);
println!("{:?}", sorted);

hard

A. [329, 436, 355, 457, 657, 720, 839]

B. [839, 720, 657, 457, 436, 355, 329]

C. [329, 355, 436, 457, 657, 720, 839]

D. [355, 329, 436, 457, 657, 720, 839]

Solution

1. Step 1: Understand the radix sort passes

   The function sorts by digits starting from least significant (units), then tens, then hundreds until max digit processed.

2. Step 2: Trace sorting steps on input

   After all passes, the vector is sorted ascending: [329, 355, 436, 457, 657, 720, 839].

3. Final Answer:

   [329, 355, 436, 457, 657, 720, 839] -> Option C

4. Quick Check:

   Radix sort final output = sorted ascending [OK]

Hint: Radix sort outputs fully sorted list ascending [OK]

Common Mistakes:

• Confusing order as descending
• Missing clearing array before collecting buckets
• Not multiplying exp by 10 each iteration