Two Non Repeating Elements in Array Using XOR in DSA Python - Cheat Sheet & Quick Revision

Recall & Review

beginner

What does XOR operation do when applied between two same bits?

XOR of two same bits is 0. For example, 1 XOR 1 = 0 and 0 XOR 0 = 0.

intermediate

Why XOR of all elements in an array with exactly two non-repeating elements results in XOR of those two unique elements?

Because XOR of two same numbers is 0, all repeating elements cancel out, leaving XOR of only the two unique elements.

intermediate

How do you find a set bit in XOR of two unique numbers to separate them?

Find the rightmost set bit (bit with value 1) in the XOR result using expression: xor & (-xor). This bit differs between the two unique numbers.

intermediate

Explain the step to separate array elements into two groups using the set bit.

Divide elements into two groups: those with the set bit and those without. XOR each group separately to find the two unique numbers.

beginner

What is the time complexity of finding two non-repeating elements using XOR?

The time complexity is O(n) because we traverse the array a constant number of times.

What is the XOR of a number with itself?

A 0

B The number itself

C 1

D Undefined

XOR of a number with itself is always 0.

If XOR of all elements in an array is 6, what does this represent when exactly two elements are unique?

A Sum of two unique elements

B Product of two unique elements

C XOR of two unique elements

D Difference of two unique elements

The XOR of all elements equals XOR of the two unique elements after canceling duplicates.

How do you find the rightmost set bit in a number x?

A x & (-x)

B x | (-x)

C x & (x - 1)

D x ^ (-x)

x & (-x) isolates the rightmost set bit in x.

After finding the rightmost set bit, how are elements grouped?

A By even and odd values

B Randomly

C By greater or smaller than XOR value

D By presence or absence of the set bit

Elements are grouped based on whether the set bit is 1 or 0 in their binary form.

What is the main advantage of using XOR to find two unique elements?

A Uses extra memory

B Runs in O(n) time without extra space

C Runs in O(n^2) time

D Requires sorting

XOR method finds unique elements in linear time and constant space.

Describe the step-by-step process to find two non-repeating elements in an array using XOR.

Think about how XOR cancels duplicates and how to separate elements by a differing bit.

Explain why XOR operation helps in identifying unique elements in an array where all others repeat twice.

Focus on how XOR behaves with pairs and unique values.

Practice

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

easy

A. To sort the array in ascending order

B. To count the frequency of each element

C. To cancel out all repeating elements and isolate the XOR of the two unique elements

D. To reverse the array elements

Solution

1. Step 1: Understand XOR properties

   XOR of a number with itself is 0, and XOR with 0 is the number itself. This helps cancel out repeating elements.

2. Step 2: Apply XOR on all elements

   When XOR is applied on the entire array, all repeating elements cancel out, leaving XOR of the two unique elements.

3. Final Answer:

   To cancel out all repeating elements and isolate the XOR of the two unique elements -> Option C

4. Quick Check:

   XOR cancels duplicates = isolate unique elements [OK]

Hint: XOR duplicates become zero, leaving unique elements XOR [OK]

Common Mistakes:

• Thinking XOR sorts the array
• Using XOR to count frequencies
• Assuming XOR reverses elements

2. Which of the following Python code snippets correctly initializes the XOR of all elements in a list named arr to zero before processing?

easy

A. xor = 1

B. xor = 0

C. xor = arr[0]

D. xor = None

Solution

1. Step 1: Initialize XOR variable

   We start XOR with 0 because XOR with 0 returns the other number unchanged.

2. Step 2: Confirm initialization correctness

   Starting with 0 ensures the first XOR operation correctly sets the value to the first element.

3. Final Answer:

   xor = 0 -> Option B

4. Quick Check:

   Initialize XOR with 0 for correct accumulation [OK]

Hint: Start XOR with 0 to accumulate correctly [OK]

Common Mistakes:

• Initializing XOR with 1 causes wrong results
• Using first element without XOR 0 initialization
• Setting XOR to None causes errors

3. What will be the output of the following Python code?

arr = [2, 3, 7, 9, 2, 3]
xor = 0
for num in arr:
    xor ^= num
print(xor)

medium

A. 0

B. 9

C. 7

D. 14

Solution

1. Step 1: XOR all elements in the array

   Calculate XOR stepwise: 0^2=2, 2^3=1, 1^7=6, 6^9=15, 15^2=13, 13^3=14.

2. Step 2: Final XOR value

   The final XOR after processing all elements is 14.

3. Final Answer:

   14 -> Option D

4. Quick Check:

   Stepwise XOR = 14 [OK]

Hint: XOR all elements stepwise to find combined XOR [OK]

Common Mistakes:

• Forgetting XOR is cumulative and order matters
• Mistaking XOR with addition
• Stopping XOR early

4. Identify the error in the following code snippet that attempts to find two non-repeating elements using XOR:

arr = [4, 1, 2, 1, 2, 5]
xor = 0
for num in arr:
    xor ^= num
set_bit = xor & ~(xor - 1)
num1 = 0
num2 = 0
for num in arr:
    if (num & set_bit) > 0:
        num1 ^= num
    else:
        num2 ^= num
print(num1, num2)

medium

A. No error, code works correctly

B. XOR initialization should be arr[0] instead of 0

C. Incorrect calculation of set_bit using bitwise NOT

D. Using > 0 instead of != 0 in if condition

Solution

1. Step 1: Check set_bit calculation

   set_bit = xor & ~(xor - 1) correctly isolates rightmost set bit.

2. Step 2: Verify partition and XOR groups

   Elements are split by set_bit and XORed separately to find unique elements.

3. Step 3: Confirm output correctness

   Code correctly prints the two unique numbers without errors.

4. Final Answer:

   No error, code works correctly -> Option A

5. Quick Check:

   Correct set_bit and partitioning = code works [OK]

Hint: Use xor & ~(xor-1) to find rightmost set bit correctly [OK]

Common Mistakes:

• Misusing bitwise NOT causing wrong set_bit
• Initializing XOR incorrectly
• Using wrong condition in if statement

5. Given an array arr = [10, 20, 10, 30, 40, 20], which of the following Python code snippets correctly finds the two non-repeating elements using XOR and prints them in ascending order?

hard

A. xor = 0
for num in arr:
xor ^= num
set_bit = xor & (-xor)
num1 = 0
num2 = 0
for num in arr:
if num & set_bit:
num1 ^= num
else:
num2 ^= num
print(sorted([num1, num2]))

B. xor = 0
for num in arr:
xor ^= num
set_bit = xor | (xor - 1)
num1 = 0
num2 = 0
for num in arr:
if num & set_bit:
num1 ^= num
else:
num2 ^= num
print(sorted([num1, num2]))

C. xor = arr[0]
for num in arr[1:]:
xor ^= num
set_bit = xor & ~(xor - 1)
num1 = 0
num2 = 0
for num in arr:
if (num & set_bit) == 0:
num1 ^= num
else:
num2 ^= num
print(sorted([num1, num2]))

D. xor = 0
for num in arr:
xor ^= num
set_bit = xor & ~(xor + 1)
num1 = 0
num2 = 0
for num in arr:
if (num & set_bit) != 0:
num1 ^= num
else:
num2 ^= num
print(sorted([num1, num2]))

Solution

1. Step 1: Calculate XOR of all elements

   xor accumulates XOR of all elements, isolating XOR of two unique numbers.

2. Step 2: Find rightmost set bit correctly

   set_bit = xor & (-xor) correctly isolates the rightmost set bit for partitioning.

3. Step 3: Partition elements and XOR separately

   Elements are split by set_bit and XORed to find the two unique numbers.

4. Step 4: Sort and print unique elements

   Sorting ensures output is in ascending order as required.

5. Final Answer:

   Code in option A correctly finds and prints [30, 40] -> Option A

6. Quick Check:

   Rightmost set bit with xor & (-xor) + partition = correct [OK]

Hint: Use xor & (-xor) to find set bit and partition array [OK]

Common Mistakes:

• Using incorrect set_bit calculation like xor | (xor - 1)
• Wrong initialization of xor variable
• Incorrect condition in partition if statement