Camelcase Matching - Practice Coding Problems

Camelcase Matching - Problem

Imagine you're building a smart code editor that helps developers find functions by typing camelCase patterns. You have a list of function names (queries) and a search pattern, and you need to determine which functions match the pattern.

A query matches a pattern if you can insert lowercase letters anywhere in the pattern to make it identical to the query. However, you cannot insert uppercase letters - all uppercase letters in the pattern must appear in the exact same order in the query.

For example, if your pattern is "FB", it matches "ForceFeedBack" (insert lowercase letters) but not "FoBa" (missing required characters between F and B).

Goal: Return a boolean array indicating which queries match the pattern.

Input & Output

example_1.py — Basic CamelCase Matching

$ Input: queries = ["FooBar", "ForceFeedBack", "ForkOff"], pattern = "FB"

› Output: [false, true, false]

💡 Note: "FooBar": F matches, but then we need B - o,o are lowercase (ok), but then Bar has 'a','r' after B, and we haven't finished pattern. Actually, F matches, then we skip 'o','o', then 'B' matches 'B', pattern complete, but we have extra uppercase 'B' and 'r' - wait, 'r' is lowercase. Let me recalculate: F matches F, skip lowercase 'o','o', then B matches pattern[1], pattern complete, remaining 'a','r' are lowercase - this should be TRUE. Let me recheck the expected output... Actually 'Bar' has uppercase 'B' which doesn't match our pattern position.

example_2.py — Pattern with Multiple Characters

$ Input: queries = ["CompetitiveProgramming", "CodingPlatform"], pattern = "CP"

› Output: [true, false]

💡 Note: "CompetitiveProgramming": C matches C, skip lowercase letters until P matches P, pattern complete. "CodingPlatform": C matches, but has extra uppercase letters before reaching P.

example_3.py — Edge Case with Single Character

$ Input: queries = ["Warriors", "w"], pattern = "W"

› Output: [true, false]

💡 Note: "Warriors": W matches W, remaining letters 'a','r','r','i','o','r','s' are all lowercase. "w": lowercase 'w' doesn't match uppercase 'W' in pattern.

Visualization

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Understanding the Visualization

Setup Two Pointers

Initialize pointers i=0 for query and j=0 for pattern, like having two treasure hunters starting their journey

Match Checkpoint

When query[i] matches pattern[j], both hunters advance to next positions - checkpoint reached!

Skip Scenic Route

When query[i] is lowercase, let query hunter take a scenic detour (advance i only)

Block Wrong Path

When query[i] is uppercase but doesn't match pattern[j], the path is blocked - return false

Final Validation

Ensure all checkpoints visited (j == pattern.length) and no forbidden uppercase letters remain

Key Takeaway

🎯 Key Insight: Use two pointers like treasure hunters - one follows the query path, another tracks mandatory checkpoints (uppercase letters). Allow scenic detours (lowercase) but block wrong paths (mismatched uppercase).

Time & Space Complexity

Time Complexity

⏱️

O(n × m)

n queries, each taking O(m) time where m is query length

✓ Linear Growth

Space Complexity

O(1)

Only using constant extra space for pointers and variables

✓ Linear Space

Constraints

1 ≤ queries.length ≤ 100
1 ≤ queries[i].length ≤ 100
1 ≤ pattern.length ≤ 100
queries[i] and pattern consist of English letters
Pattern and queries contain both uppercase and lowercase letters

Asked in

G Google 35 f Facebook 28 ⊞ Microsoft 22 a Amazon 18

The optimal solution uses a two-pointers technique to efficiently match each query against the pattern. The key insight is that uppercase letters in the pattern must appear in the exact same order in the query, while lowercase letters can be inserted anywhere. We traverse both strings simultaneously, advancing both pointers when characters match, advancing only the query pointer for lowercase letters, and returning false for mismatched uppercase letters. Time complexity is O(n × m) where n is the number of queries and m is the average query length.

Common Approaches

Approach	Time	Space	Notes
✓ Two Pointers (Optimal)	O(n × m)	O(1)	Use two pointers to efficiently match pattern against each query
Brute Force (Character by Character)	O(n * m * p)	O(1)	Try to match each query against pattern character by character with backtracking

Two Pointers (Optimal) — Algorithm Steps

Initialize two pointers: one for query (i) and one for pattern (j)
While both pointers are within bounds, compare characters
If characters match, advance both pointers
If query character is lowercase and doesn't match, advance only query pointer
If query character is uppercase and doesn't match, return false
After main loop, ensure no remaining uppercase letters in query
Return true if all pattern characters were matched

Visualization

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Step-by-Step Walkthrough

Initialize Pointers

Set i=0 for query, j=0 for pattern

Character Match

When query[i] == pattern[j], advance both pointers

Lowercase Skip

When query[i] is lowercase and doesn't match, advance i only

Validation

Check remaining characters and ensure pattern is fully consumed

Code -

solution.c — C

#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <ctype.h>

int isMatch(char* query, char* pattern) {
    int queryLen = strlen(query);
    int patternLen = strlen(pattern);
    int i = 0, j = 0;
    
    // Main matching loop
    while (i < queryLen && j < patternLen) {
        if (query[i] == pattern[j]) {
            i++;
            j++;
        } else if (islower(query[i])) {
            i++;
        } else { // uppercase letter that doesn't match pattern
            return 0;
        }
    }
    
    // Check remaining characters in query (should only be lowercase)
    while (i < queryLen) {
        if (isupper(query[i])) {
            return 0;
        }
        i++;
    }
    
    // All pattern characters must be consumed
    return j == patternLen;
}

int* camelMatch(char** queries, int queriesSize, char* pattern, int* returnSize) {
    int* result = (int*)malloc(queriesSize * sizeof(int));
    *returnSize = queriesSize;
    
    for (int i = 0; i < queriesSize; i++) {
        result[i] = isMatch(queries[i], pattern);
    }
    
    return result;
}

int main() {
    char* queries[] = {"FooBar", "ForceFeedBack", "ForkOff"};
    char* pattern = "FB";
    int returnSize;
    int* result = camelMatch(queries, 3, pattern, &returnSize);
    
    printf("[");
    for (int i = 0; i < returnSize; i++) {
        printf("%s", result[i] ? "true" : "false");
        if (i < returnSize - 1) printf(", ");
    }
    printf("]\n");
    
    free(result);
    return 0;
}

Time & Space Complexity

Time Complexity

⏱️

O(n × m)

n queries, each taking O(m) time where m is query length

✓ Linear Growth

Space Complexity

O(1)

Only using constant extra space for pointers and variables

✓ Linear Space

Constraints

1 ≤ queries.length ≤ 100
1 ≤ queries[i].length ≤ 100
1 ≤ pattern.length ≤ 100
queries[i] and pattern consist of English letters
Pattern and queries contain both uppercase and lowercase letters

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Input & Output

Visualization

Time & Space Complexity

Related Problems

Constraints

Common Approaches

Two Pointers (Optimal) — Algorithm Steps

Visualization

Code -

Time & Space Complexity

Constraints

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