KMP Pattern Matching Algorithm in DSA Go - Interactive Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to initialize the prefix array with zeros.

DSA Go

prefix := make([]int, len(pattern))
for i := range prefix {
    prefix[i] = [1]
}

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

Ai

B0

C-1

D1

Attempts:

3 left

💡 Hint

Common Mistakes

Initializing prefix array with ones or negative values causes incorrect matching.

Using loop index 'i' as initial value is wrong.

The prefix array stores lengths of longest proper prefix which is also suffix. It starts with zeros.

2fill in blank

medium

Complete the code to update the prefix length when characters match.

DSA Go

if pattern[i] == pattern[j] {
    j = j + [1]
    prefix[i] = j
}

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

A-1

Bi

C1

D0

Attempts:

3 left

💡 Hint

Common Mistakes

Incrementing by zero or negative values causes no progress.

Using loop index 'i' instead of 1 is incorrect.

When characters match, increase prefix length by 1 and assign it.

3fill in blank

hard

Fix the error in the loop condition to avoid index out of range.

DSA Go

for i := 1; i < [1]; i++ {
    // build prefix array
}

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

Alen(pattern)

Blen(text)

Clen(prefix) + 1

Dlen(pattern) - 1

Attempts:

3 left

💡 Hint

Common Mistakes

Using text length causes index errors.

Using len(pattern) - 1 misses last character.

The prefix array is built for the pattern length, so loop must run till len(pattern).

4fill in blank

hard

Fill both blanks to correctly update the index j when characters mismatch during prefix building.

DSA Go

for i := 1; i < len(pattern); i++ {
    for j > 0 && pattern[i] != pattern[j] {
        j = prefix[1]
    }
    if pattern[i] == pattern[j] {
        j = j + [2]
    }
    prefix[i] = j
}

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

A[j-1]

B[j]

C1

D0

Attempts:

3 left

💡 Hint

Common Mistakes

Using prefix[j] instead of prefix[j-1] causes infinite loops.

Incrementing j by 0 causes no progress.

When mismatch occurs, j moves to prefix[j-1]. When match occurs, j increments by 1.

5fill in blank

hard

Fill all three blanks to correctly implement the main KMP search loop.

DSA Go

for i := 0; i < len(text); i++ {
    for j > 0 && text[i] != pattern[1] {
        j = prefix[2]
    }
    if text[i] == pattern[3] {
        j++
    }
    if j == len(pattern) {
        fmt.Println("Pattern found at index", i - j + 1)
        j = prefix[j-1]
    }
}

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

A[j]

B[j-1]

Cj

Attempts:

3 left

💡 Hint

Common Mistakes

Using wrong indices causes incorrect matching.

Not updating j after finding a pattern causes missed matches.

Use pattern[j] to compare characters, fallback to prefix[j-1] on mismatch, and increment j on match.

Practice

1. What is the main purpose of the KMP (Knuth-Morris-Pratt) algorithm in pattern matching?

easy

A. To efficiently find occurrences of a pattern in a text without rechecking characters

B. To sort the characters of the pattern alphabetically

C. To reverse the text before searching

D. To count the number of vowels in the text

Solution

1. Step 1: Understand KMP's goal

   KMP is designed to find pattern matches in text efficiently by avoiding repeated comparisons.

2. Step 2: Compare options with KMP's function

   Only To efficiently find occurrences of a pattern in a text without rechecking characters describes this efficient search without rechecking characters.

3. Final Answer:

   To efficiently find occurrences of a pattern in a text without rechecking characters -> Option A

4. Quick Check:

   KMP purpose = efficient pattern search [OK]

Hint: KMP avoids rechecking characters during pattern search [OK]

Common Mistakes:

• Thinking KMP sorts or modifies the text
• Confusing KMP with simple substring search
• Assuming KMP counts characters instead of searching

2. Which of the following is the correct way to declare the prefix table (lps array) in Go for KMP algorithm?

easy

A. lps := []string{len(pattern)}

B. lps := make([]int, len(pattern))

C. lps := make([]bool, len(pattern))

D. lps := new(int)

Solution

1. Step 1: Identify correct Go syntax for integer slice

   In Go, make([]int, size) creates an integer slice of given size.

2. Step 2: Check options for correct slice creation

   lps := make([]int, len(pattern)) correctly creates an int slice for lps. Others use wrong types or syntax.

3. Final Answer:

   lps := make([]int, len(pattern)) -> Option B

4. Quick Check:

   Go slice for lps = make([]int, len(pattern)) [OK]

Hint: Use make([]int, size) to create integer slices in Go [OK]

Common Mistakes:

• Using wrong slice type like []string or []bool
• Using new(int) which creates a pointer, not slice
• Incorrect slice initialization syntax

3. What will be the output of the following Go code snippet that uses KMP to find pattern occurrences?

package main
import "fmt"

func computeLPS(pattern string) []int {
    lps := make([]int, len(pattern))
    length := 0
    i := 1
    for i < len(pattern) {
        if pattern[i] == pattern[length] {
            length++
            lps[i] = length
            i++
        } else {
            if length != 0 {
                length = lps[length-1]
            } else {
                lps[i] = 0
                i++
            }
        }
    }
    return lps
}

func main() {
    pattern := "ABABC"
    lps := computeLPS(pattern)
    fmt.Println(lps)
}

medium

A. [0 0 0 0 0]

B. [0 1 2 3 4]

C. [1 2 3 4 5]

D. [0 0 1 2 0]

Solution

1. Step 1: Compute LPS array for pattern "ABABC"

   Check characters stepwise: - i=1: 'B' != 'A' => lps[1]=0 - i=2: 'A' == 'A' => length=1, lps[2]=1 - i=3: 'B' == 'B' => length=2, lps[3]=2 - i=4: 'C' != 'A' => length=lps[1]=0, lps[4]=0

2. Step 2: Final LPS array is [0, 0, 1, 2, 0]

   This matches [0 0 1 2 0] exactly.

3. Final Answer:

   [0 0 1 2 0] -> Option D

4. Quick Check:

   LPS for "ABABC" = [0 0 1 2 0] [OK]

Hint: Trace pattern chars to build LPS stepwise [OK]

Common Mistakes:

• Confusing LPS values with pattern indices
• Not resetting length correctly on mismatch
• Assuming all zeros or increasing sequence

4. Identify the bug in this KMP prefix table computation code snippet in Go:

func computeLPS(pattern string) []int {
    lps := make([]int, len(pattern))
    length := 0
    i := 0
    for i < len(pattern) {
        if pattern[i] == pattern[length] {
            length++
            lps[i] = length
            i++
        } else {
            if length != 0 {
                length = lps[length-1]
            } else {
                lps[i] = 0
                i++
            }
        }
    }
    return lps
}

medium

A. The function should return a string, not []int

B. The length variable should be initialized to 1

C. The loop should start with i = 1, not 0

D. The lps array should be of type []bool

Solution

1. Step 1: Check loop initialization for LPS computation

   In KMP, i starts from 1 because lps[0] is always 0 and no comparison needed at index 0.

2. Step 2: Identify incorrect i initialization

   Here i starts at 0, causing incorrect comparisons and possible infinite loop.

3. Final Answer:

   The loop should start with i = 1, not 0 -> Option C

4. Quick Check:

   Start i=1 for LPS loop [OK]

Hint: LPS loop always starts at index 1 [OK]

Common Mistakes:

• Starting loop at 0 causing wrong LPS values
• Initializing length incorrectly
• Wrong return type or array type

5. Given the text "ABABDABACDABABCABAB" and pattern "ABABCABAB", how many times does the pattern occur in the text using KMP algorithm?

hard

A. 2

B. 1

C. 3

D. 0

Solution

1. Step 1: Understand the pattern and text

   The pattern "ABABCABAB" appears in the text at indices 10 and 12 (0-based indexing), overlapping occurrences.

2. Step 2: Count occurrences using KMP logic

   KMP finds two matches without rechecking characters, so total occurrences = 2.

3. Final Answer:

   2 -> Option A

4. Quick Check:

   Pattern occurs twice in text [OK]

Hint: Use KMP to find all pattern matches efficiently [OK]

Common Mistakes:

• Counting overlapping matches incorrectly
• Overcounting occurrences
• Assuming zero matches due to complexity