Why KMP Pattern Matching Algorithm in DSA C?

The Big Idea

Discover how computers find words lightning-fast without rechecking every letter!

The Scenario

Imagine you are searching for a word in a huge book by reading every letter one by one from the start each time you find a mismatch.

The Problem

This manual search is very slow and tiring because you keep going back and checking letters you already know don't match, wasting a lot of time.

The Solution

The KMP algorithm helps by remembering where to continue checking after a mismatch, so you never go back unnecessarily and find the word faster.

Before vs After

✗ Before

for (int i = 0; i <= text_length - pattern_length; i++) {
    int j = 0;
    while (j < pattern_length && text[i + j] == pattern[j]) {
        j++;
    }
    if (j == pattern_length) {
        // pattern found
    }
}

✓ After

int i = 0, j = 0;
while (i < text_length) {
    if (pattern[j] == text[i]) {
        i++; j++;
        if (j == pattern_length) {
            // pattern found
            j = lps[j - 1];
        }
    } else if (j != 0) {
        j = lps[j - 1];
    } else {
        i++;
    }
}

What It Enables

KMP makes searching for patterns in large texts fast and efficient, saving time and effort.

Real Life Example

When you use the 'Find' feature in a text editor to quickly locate a word, KMP-like methods help the computer find it instantly without checking every letter again.

Key Takeaways

Manual search repeats checks and wastes time.

KMP remembers where to continue after mismatches.

KMP speeds up pattern searching in texts.

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 total number of characters in the text

Solution

1. Step 1: Understand KMP's goal

   KMP algorithm is designed to find all occurrences of a pattern in a text efficiently.

2. Step 2: Identify how KMP works

   It avoids rechecking characters by using a prefix table to skip unnecessary comparisons.

3. Final Answer:

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

4. Quick Check:

   KMP = Efficient pattern search [OK]

Hint: KMP skips repeated checks using prefix info [OK]

Common Mistakes:

• Thinking KMP sorts or reverses strings
• Confusing KMP with simple substring search
• Assuming KMP counts characters only

2. Which of the following correctly declares the prefix (lps) array in C for KMP algorithm of size m?

easy

A. int *lps = malloc(m * sizeof(int));

B. int lps = new int[m];

C. int lps[m];

D. int lps[] = {m};

Solution

1. Step 1: Understand array declaration in C

   Static arrays like int lps[m]; require constant size or C99 support; dynamic allocation uses malloc.

2. Step 2: Identify correct dynamic allocation

   int *lps = malloc(m * sizeof(int)); correctly allocates memory for m integers dynamically.

3. Final Answer:

   int *lps = malloc(m * sizeof(int)); -> Option A

4. Quick Check:

   Dynamic array = malloc usage [OK]

Hint: Use malloc for dynamic arrays in C [OK]

Common Mistakes:

• Using Java-style array allocation in C
• Incorrect static array size syntax
• Misusing array initialization syntax

3. What will be the output of the following C code snippet using KMP prefix array computation for pattern "ABABC"?

int main() {
    char pattern[] = "ABABC";
    int m = 5, i = 1, len = 0;
    int lps[5] = {0};
    while (i < m) {
        if (pattern[i] == pattern[len]) {
            len++;
            lps[i] = len;
            i++;
        } else {
            if (len != 0) {
                len = lps[len - 1];
            } else {
                lps[i] = 0;
                i++;
            }
        }
    }
    for (int j = 0; j < m; j++) {
        printf("%d ", lps[j]);
    }
    return 0;
}

medium

A. 0 0 1 2 1

B. 0 1 0 1 2

C. 0 1 2 3 4

D. 0 0 1 2 0

Solution

1. Step 1: Compute lps array step-by-step for "ABABC"

   Index 0: 0; i=1: 'B' != 'A' (len=0) -> lps[1]=0, i=2; i=2: 'A' == 'A' -> len=1, lps[2]=1, i=3; i=3: 'B' == 'B' -> len=2, lps[3]=2, i=4; i=4: 'C' != 'A' (len=2) -> len=lps[1]=0, 'C' != 'A' -> lps[4]=0.

2. Step 2: Final lps array values

   The lps array is [0, 0, 1, 2, 0]. Output: 0 0 1 2 0

3. Final Answer:

   0 0 1 2 0 -> Option D

4. Quick Check:

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

Hint: Trace lps step-by-step for each pattern char [OK]

Common Mistakes:

• Miscomputing fallback index in lps
• Confusing pattern characters during comparison
• Assuming lps always increases

4. Identify the bug in this KMP prefix array computation snippet and select the fix:

int i = 1, len = 0;
while (i <= m) {
    if (pattern[i] == pattern[len]) {
        len++;
        lps[i] = len;
        i++;
    } else {
        if (len != 0) {
            len = lps[len - 1];
        } else {
            lps[i] = 0;
            i++;
        }
    }
}

medium

A. Remove i++ inside else block

B. Initialize len to 1 instead of 0

C. Change loop condition to i < m

D. Use pattern[len+1] instead of pattern[len]

Solution

1. Step 1: Analyze loop boundary

   The loop runs while i <= m, but array indices go from 0 to m-1, so i == m causes out-of-bounds access.

2. Step 2: Correct loop condition

   Changing condition to i < m prevents accessing beyond array size.

3. Final Answer:

   Change loop condition to i < m -> Option C

4. Quick Check:

   Loop index must be less than array size [OK]

Hint: Loop till less than array size, not equal [OK]

Common Mistakes:

• Using <= instead of < causing overflow
• Incorrect initialization of len
• Misplacing increment statements

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

hard

A. 1

B. 2

C. 3

D. 0

Solution

1. Step 1: Understand pattern occurrences

   Check the text for exact matches of pattern "ABABCABAB" (length 9).

2. Step 2: Locate matches in text

   Pattern matches fully at index 10 ("ABABCABAB" from positions 10-18) and also at index 0 ("ABABDABAC" partial mismatch at 4th char but KMP finds overlapping matches). Actually, KMP finds the pattern twice: once starting at index 0 (partial mismatch but KMP continues) and once at index 10 fully matching. The correct count is 2.

3. Final Answer:

   2 -> Option B

4. Quick Check:

   Pattern found twice in text [OK]

Hint: Count full pattern matches in text using KMP [OK]

Common Mistakes:

• Counting partial matches as full
• Misidentifying additional matches (e.g., at index 14)
• Overlooking text length boundaries