Majority Element Moore's Voting Algorithm in DSA Go - Interactive Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to initialize the candidate for majority element.

DSA Go

candidate := nums[[1]]

Drag options to blanks, or click blank then click option'

A0

B1

Clen(nums)-1

Dlen(nums)

Attempts:

3 left

💡 Hint

Common Mistakes

Using index 1 instead of 0 causes skipping the first element.

Using len(nums) causes index out of range error.

The candidate is initialized to the first element, which is at index 0.

2fill in blank

medium

Complete the code to reset the count when a new candidate is chosen.

DSA Go

if count == 0 {
    candidate = nums[[1]]
    count = 1
}

Drag options to blanks, or click blank then click option'

Ai

B0

Ccount

Dcandidate

Attempts:

3 left

💡 Hint

Common Mistakes

Using 0 instead of i resets candidate always to first element.

Using count or candidate as index causes errors.

When count is zero, the candidate is updated to the current element at index i.

3fill in blank

hard

Fix the error in the condition to update the count when the current element matches the candidate.

DSA Go

if nums[i] [1] candidate {
    count++
} else {
    count--
}

Drag options to blanks, or click blank then click option'

A!=

B==

C<

D>

Attempts:

3 left

💡 Hint

Common Mistakes

Using '!=' causes count to increase on different elements.

Using '<' or '>' is incorrect for equality check.

The count increases only when the current element equals the candidate.

4fill in blank

hard

Fill both blanks to complete the loop that finds the majority element candidate.

DSA Go

for [1] := 1; [1] < [2]; [1]++ {
    if count == 0 {
        candidate = nums[[1]]
        count = 1
    } else if nums[[1]] == candidate {
        count++
    } else {
        count--
    }
}

Drag options to blanks, or click blank then click option'

Ai

Blen(nums)

Ccount

Dcandidate

Attempts:

3 left

💡 Hint

Common Mistakes

Using count or candidate as loop limit causes errors.

Starting loop at 0 repeats first element already used.

The loop variable i starts at 1 and runs while i is less than the length of nums.

5fill in blank

hard

Fill all three blanks to verify the candidate is the majority element by counting its occurrences.

DSA Go

count = 0
for _, num := range nums {
    if num [1] candidate {
        count[2]
    }
}
if count [3] len(nums)/2 {
    return candidate
} else {
    return -1
}

Drag options to blanks, or click blank then click option'

A==

B++

C>

D<=

Attempts:

3 left

💡 Hint

Common Mistakes

Using '<=' instead of '>' causes wrong majority check.

Using '=' instead of '==' causes assignment error.

Forgetting to increment count causes zero count.

We count how many times candidate appears (==), increment count (++), and check if count is greater than half the length (>).

Practice

1. What is the main purpose of Moore's Voting Algorithm in an array of integers?

easy

A. To find the element that appears more than half the times

B. To sort the array in ascending order

C. To find the smallest element in the array

D. To count the total number of unique elements

Solution

1. Step 1: Understand the problem Moore's Voting Algorithm solves

   It is designed to find the majority element, which is the element that appears more than half the times in the array.

2. Step 2: Compare with other options

   Sorting, finding smallest element, or counting unique elements are not the algorithm's purpose.

3. Final Answer:

   To find the element that appears more than half the times -> Option A

4. Quick Check:

   Majority element = element appearing > n/2 times [OK]

Hint: Majority element appears more than half the array length [OK]

Common Mistakes:

• Confusing majority element with most frequent element
• Thinking it sorts the array
• Assuming it finds smallest or unique elements

2. Which of the following Go code snippets correctly initializes the variables needed for Moore's Voting Algorithm?

easy

A. count := 0; candidate := 0

B. var count int = 1; var candidate int = -1

C. count := 0; candidate := ''

D. var count string = '0'; var candidate int = 0

Solution

1. Step 1: Identify correct variable types and initialization

   Moore's Voting Algorithm uses an integer count starting at 0 and an integer candidate initialized to 0 or any valid integer.

2. Step 2: Check each option for type correctness

   count := 0; candidate := 0 uses count and candidate as integers with proper initialization. var count int = 1; var candidate int = -1 initializes count to 1 which is not standard start. count := 0; candidate := '' uses empty string for candidate which is wrong type. var count string = '0'; var candidate int = 0 uses string type for count which is incorrect.

3. Final Answer:

   count := 0; candidate := 0 -> Option A

4. Quick Check:

   Integer count and candidate initialized to 0 [OK]

Hint: Count starts at 0, candidate is integer zero [OK]

Common Mistakes:

• Using wrong data types for count or candidate
• Starting count at 1 instead of 0
• Initializing candidate with empty string

3. What will be the output of the following Go code snippet using Moore's Voting Algorithm?

arr := []int{2, 2, 1, 1, 1, 2, 2}
count := 0
candidate := 0
for _, num := range arr {
  if count == 0 {
    candidate = num
  }
  if num == candidate {
    count++
  } else {
    count--
  }
}
fmt.Println(candidate)

medium

A. 1

B. 0

C. 2

D. 3

Solution

1. Step 1: Trace the loop to find candidate

   Start with count=0, candidate=0.
   Iteration 1: count=0, candidate=2, count=1
   Iteration 2: num=2 == candidate=2, count=2
   Iteration 3: num=1 != candidate=2, count=1
   Iteration 4: num=1 != candidate=2, count=0
   Iteration 5: count=0, candidate=1, count=1
   Iteration 6: num=2 != candidate=1, count=0
   Iteration 7: count=0, candidate=2, count=1

2. Step 2: Final candidate after loop

   The candidate after the loop ends is 2.

3. Final Answer:

   2 -> Option C

4. Quick Check:

   Majority element found = 2 [OK]

Hint: Track count changes; candidate updates when count hits zero [OK]

Common Mistakes:

• Not updating candidate when count is zero
• Confusing candidate with last element
• Miscounting increments and decrements

4. Identify the bug in this Go code implementing Moore's Voting Algorithm:

arr := []int{3, 3, 4, 2, 4, 4, 2, 4, 4}
count := 0
candidate := 0
for i := 0; i < len(arr); i++ {
  if count == 0 {
    candidate = arr[i]
  }
  if arr[i] == candidate {
    count--
  } else {
    count++
  }
}
fmt.Println(candidate)

medium

A. Candidate is not updated when count is zero

B. Candidate initialized incorrectly

C. Loop index goes out of range

D. Count increments and decrements are reversed

Solution

1. Step 1: Analyze count update logic

   The algorithm should increase count when current element equals candidate, and decrease count otherwise.

2. Step 2: Identify the bug in code

   Here, count is decreased when arr[i] == candidate and increased otherwise, which is reversed.

3. Final Answer:

   Count increments and decrements are reversed -> Option D

4. Quick Check:

   Correct count update: increment if equal, decrement if not [OK]

Hint: Increment count if equal, decrement if different [OK]

Common Mistakes:

• Swapping increment and decrement operations
• Not updating candidate when count is zero
• Incorrect loop bounds causing runtime errors

5. Given an array where no element appears more than half the time, how can Moore's Voting Algorithm be adapted to confirm the absence of a majority element?

hard

A. Return the candidate directly without verification

B. Run the algorithm to find a candidate, then verify its count exceeds half the array length

C. Sort the array and pick the middle element

D. Count all elements and pick the one with maximum frequency without verification

Solution

1. Step 1: Understand Moore's Voting Algorithm limitation

   The algorithm finds a candidate but does not guarantee it is a majority if none exists.

2. Step 2: Adaptation to confirm majority

   After finding candidate, count its occurrences in the array. If count > n/2, candidate is majority; else no majority element exists.

3. Final Answer:

   Run the algorithm to find a candidate, then verify its count exceeds half the array length -> Option B

4. Quick Check:

   Verify candidate count > n/2 to confirm majority [OK]

Hint: Verify candidate count after algorithm to confirm majority [OK]

Common Mistakes:

• Assuming candidate is always majority without verification
• Using sorting instead of Moore's Voting Algorithm
• Picking max frequency without checking majority condition