Why Two Non Repeating Elements in Array Using XOR in DSA Rust?

The Big Idea

Discover how a simple XOR trick can save you hours of tedious searching!

The Scenario

Imagine you have a box of socks where every sock has a matching pair except two unique socks. You want to find those two unique socks quickly without checking every single sock against all others.

The Problem

Manually comparing each sock with every other sock takes a lot of time and effort. It is easy to make mistakes and miss pairs, especially when the box is large. This slow and error-prone process wastes your time.

The Solution

Using XOR, a simple math trick, you can find the two unique socks in just one pass through the box. XOR cancels out pairs automatically, leaving only the unique socks. This method is fast, clean, and reliable.

Before vs After

✗ Before

for i in 0..arr.len() {
  for j in i+1..arr.len() {
    if arr[i] == arr[j] {
      mark_as_paired(i, j);
    }
  }
}
find_unpaired();

✓ After

let xor_all = arr.iter().fold(0, |acc, &x| acc ^ x);
let set_bit = xor_all & (!(xor_all - 1));
let (mut num1, mut num2) = (0, 0);
for &num in &arr {
  if num & set_bit == 0 {
    num1 ^= num;
  } else {
    num2 ^= num;
  }
}
println!("The two unique numbers are {} and {}", num1, num2);

What It Enables

This technique lets you find two unique items in a large collection instantly, without extra memory or complex checks.

Real Life Example

Finding two unique error codes in a huge log file where every other error code appears twice, helping quickly identify rare issues.

Key Takeaways

Manual pair checking is slow and error-prone.

XOR cancels pairs and isolates unique elements efficiently.

Using XOR reduces time and space needed to find two unique numbers.

Practice

1. What is the main idea behind using XOR to find two non-repeating elements in an array where every other element repeats?

easy

A. XOR removes duplicates by summing elements

B. XOR of all elements gives XOR of the two unique elements

C. XOR sorts the array to find unique elements

D. XOR counts the frequency of elements

Solution

1. Step 1: Understand XOR operation on array elements

   XORing all elements cancels out pairs of repeating elements because x ^ x = 0.

2. Step 2: Result after XORing all elements

   The result is XOR of the two unique elements since all duplicates cancel out.

3. Final Answer:

   XOR of all elements gives XOR of the two unique elements -> Option B

4. Quick Check:

   XOR cancels duplicates = XOR of unique elements [OK]

Hint: XOR all elements to isolate unique pair XOR [OK]

Common Mistakes:

• Thinking XOR counts frequency
• Assuming XOR sorts elements
• Using XOR as sum instead of bitwise operation

2. Which Rust syntax correctly initializes a variable to store XOR of all elements in a vector named arr?

easy

A. let mut xor = 0; for &num in &arr { xor ^= num; }

B. let xor = arr.reduce(|a, b| a + b);

C. let xor = arr.iter().sum();

D. let mut xor = 1; for num in arr { xor *= num; }

Solution

1. Step 1: Initialize mutable variable for XOR

   Use let mut xor = 0; to start XOR from zero.

2. Step 2: Iterate over references to elements and XOR

   Use for &num in &arr { xor ^= num; } to XOR each element.

3. Final Answer:

   let mut xor = 0; for &num in &arr { xor ^= num; } -> Option A

4. Quick Check:

   Mutable xor with ^= in loop = correct syntax [OK]

Hint: Use 'let mut xor = 0;' and XOR in loop [OK]

Common Mistakes:

• Using sum() instead of XOR
• Trying to multiply elements
• Not using mutable variable for XOR

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

let arr = vec![2, 3, 7, 9, 2, 3];
let mut xor = 0;
for &num in &arr {
    xor ^= num;
}
println!("{}", xor);

medium

A. 16

B. 0

C. 14

D. 9

Solution

1. Step 1: XOR all elements in the array

   Calculate 2 ^ 3 ^ 7 ^ 9 ^ 2 ^ 3 step-by-step: 2 ^ 3 = 1, 1 ^ 7 = 6, 6 ^ 9 = 15, 15 ^ 2 = 13, 13 ^ 3 = 14.

2. Step 2: Final XOR value

   The final XOR value is 14 after processing all elements.

3. Final Answer:

   14 -> Option C

4. Quick Check:

   XOR all elements = 14 [OK]

Hint: XOR duplicates cancel, result is XOR of unique elements [OK]

Common Mistakes:

• Incorrect XOR calculation order
• Assuming sum instead of XOR
• Forgetting XOR cancels duplicates

4. Identify the error in this Rust code snippet that tries to find two unique elements using XOR:

let arr = vec![4, 1, 2, 1, 2, 5];
let mut xor = 0;
for num in arr {
    xor ^= num;
}
let set_bit = xor & (-xor);
println!("{}", set_bit);

medium

A. Incorrect loop syntax for vector iteration

B. Missing mutable keyword for xor variable

C. Cannot use negative sign on unsigned integer

D. No error, code runs fine

Solution

1. Step 1: Understand variable types and operations

   In Rust, integer literals default to i32 (signed), so xor & (-xor) is valid.

2. Step 2: Verify code execution

   Loop correctly computes XOR (1), set_bit calculates correctly (1). No syntax or runtime errors.

3. Final Answer:

   No error, code runs fine -> Option D

4. Quick Check:

   i32 supports unary minus operator [OK]

Hint: Rust ints default to signed i32, -xor valid [OK]

Common Mistakes:

• Misassuming unsigned integers by default
• Thinking 'for num in arr' syntax is wrong
• Expecting mutable keyword issues

5. Given an array arr = [6, 1, 3, 6, 1, 5], which Rust code snippet correctly finds the two non-repeating elements using XOR?

hard

A. let mut xor = 0;
for &num in &arr { xor ^= num; }
let set_bit = xor & xor.wrapping_neg();
let (mut x, mut y) = (0, 0);
for &num in &arr {
if num & set_bit != 0 { x ^= num; } else { y ^= num; }
}
println!("{} {}", x, y);

B. let mut xor = 0;
for num in arr {
xor += num;
}
println!("{}", xor);

C. let mut xor = 0;
for &num in &arr {
xor ^= num;
}
println!("{}", xor);

D. let mut xor = 0;
for &num in &arr {
xor *= num;
}
println!("{}", xor);

Solution

1. Step 1: XOR all elements to get xor of two unique numbers

   Loop over array and XOR all elements to get xor = 6 ^ 1 ^ 3 ^ 6 ^ 1 ^ 5 = 3 ^ 5 = 6.

2. Step 2: Find rightmost set bit and separate elements

   Calculate set_bit = xor & xor.wrapping_neg() to isolate differing bit. Then separate elements into two groups based on this bit and XOR each group to find unique elements.

3. Step 3: Print the two unique elements

   After separation and XOR, x and y hold the two unique numbers 3 and 5.

4. Final Answer:

   Code snippet in Option A correctly finds two unique elements -> Option A

5. Quick Check:

   Use XOR, set bit, separate groups = correct approach [OK]

Hint: Use XOR, find set bit, separate and XOR groups [OK]

Common Mistakes:

• Using sum or multiplication instead of XOR
• Not isolating rightmost set bit correctly
• Not separating elements into two groups