KMP Pattern Matching Algorithm in DSA C - Time & Space Complexity

Time Complexity: KMP Pattern Matching Algorithm

O(N + M)

Understanding Time Complexity

We want to understand how fast the KMP algorithm finds a pattern inside a text.

Specifically, how the time grows as the text and pattern get longer.

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

void computeLPSArray(char* pat, int M, int* lps) {
    int len = 0, i = 1;
    lps[0] = 0;
    while (i < M) {
        if (pat[i] == pat[len]) {
            len++;
            lps[i] = len;
            i++;
        } else {
            if (len != 0) len = lps[len - 1];
            else {
                lps[i] = 0;
                i++;
            }
        }
    }
}

void KMPSearch(char* pat, char* txt) {
    int M = strlen(pat);
    int N = strlen(txt);
    int lps[M];
    computeLPSArray(pat, M, lps);
    int i = 0, j = 0;
    while (i < N) {
        if (pat[j] == txt[i]) {
            i++; j++;
        }
        if (j == M) {
            j = lps[j - 1];
        } else if (i < N && pat[j] != txt[i]) {
            if (j != 0) j = lps[j - 1];
            else i++;
        }
    }
}
    

This code finds all occurrences of a pattern inside a text efficiently using the KMP algorithm.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: The while loops that traverse the pattern and text arrays.
• How many times: Each character in the text and pattern is visited at most twice.

How Execution Grows With Input

As the text length (N) and pattern length (M) grow, the operations increase roughly in a straight line.

Input Size (N, M)	Approx. Operations
10, 3	About 20-30 operations
100, 10	About 200-300 operations
1000, 50	About 1000-1100 operations

Pattern observation: The work grows linearly with the size of text and pattern combined.

Final Time Complexity

Time Complexity: O(N + M)

This means the time to find the pattern grows in a straight line with the text and pattern sizes.

Common Mistake

[X] Wrong: "KMP takes quadratic time because of nested loops."

[OK] Correct: The loops do not restart fully; the algorithm smartly skips characters, so each is processed only a few times.

Interview Connect

Understanding KMP's time complexity shows you can analyze efficient algorithms that avoid repeated work, a key skill in problem solving.

Self-Check

"What if we used a naive pattern search instead of KMP? How would the time complexity change?"

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