positions, and it requires up to m comparisons to verify the match.

With a reasonably good hash function, such false positives are unlikely to occur often. However, it is theoretically possible to construct a query where false positives cause worst-case performance.

Therefore, while Rabin-Karp has an expected time complexity of O(n), its worst-case time complexity remains O(n * m). Since m is typically less than or equal to n, O(n + m) is fundamentally the same as O(n).

Space Complexity

Space Complexity: O(m), where m is the length of the pattern.

Pros and Cons

Pros

The Rabin-Karp algorithm excels at multiple pattern matching, a feature that gives it an edge over other string searching algorithms. This is useful:

Effective for detecting plagiarism, as it supports multiple pattern matching.
Though theoretically not faster than brute force, its practical complexity is O(n+m).
With a robust hashing function, it is efficient and straightforward to implement.

Cons

There are several string matching algorithms with better performance than O(n*m); however, Rabin-Karp outperforms the naive brute force method in the worst-case scenario.
It can be as slow as brute force in practice and requires additional memory.

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