5.3 Substring Search
This section under major construction. Searching in long strings - online.
This website is a great resource for exact string searching algorithms.
High-performance pattern matching in Java for general string searching, searching with wildcards, and searching with character classes.
Rabin-Karp.Program RabinKarp.java implements the Rabin-Karp randomized fingerprint algorithm.
Knuth-Morris-Pratt.Program KMP.java is Knuth-Morris-Pratt algorithm. KMPplus.java is an improved version that takes time and space proportional to M + N (independent of the alphabet size R).
Boyer-Moore.Program BoyerMoore.java implements the bad-character rule part of the Boyer-Moore algorithm. It does not implement the strong good suffix rule.
Intrusion detection systems.Need very fast string searching since these are deployed at choke points of networks. Application
- Design a brute-force substring search algorithm that scans the pattern from right to left.
- Show the trace of the brute-force algorithm in the style of figure XYZ
for the following pattern and text strings.
- AAAAAAAB; AAAAAAAAAAAAAAAAAAAAAAAAB
- ABABABAB; ABABABABAABABABABAAAAAAAA
- Determine the KMP DFA for the following pattern strings.
- Suppose that the pattern and text are random strings over an alphabet of size R >= 2. Show that the expected number of character compares is (N - M + 1) (1 - R^-M) / (1 - R^-1) <= 2 (N - M + 1).
- Construct an example where the Boyer-Moore algorithm (with only the bad character rule) performls poorly.
- How would you modify Rabin-Karp to search for a given pattern with the additional proviso that the middle character is a "wildcard" (any text character at all can match it).
- How would you modify Rabin-Karp to determine whether any of a subset
of k patterns (say, all of the same length) is in the text?
Solution. Compute the hashes of the k patterns and store the hashes in a SET.
- How would you modify Rabin-Karp to search for an M-by-M pattern in an N-by-N text? Or some other irregularly-shaped pattern in an N-by-N text?
- Monte Carlo vs. Las Vegas Rabin Karp.
- Online palindrome detection. Read in characters one at a time. Report at each instant if the current string is a palindrome. Hint: use Karp-Rabin hashing idea.
- Tandem repeats.
A tandem repeat of a base string b within a string s is a substring
of s consisting of at least one consecutive copy of the base
string b. Given b and s, design an algorithm to
find a tandem repeat of b within s of maximum length.
The running time should be proportional to M + N, where
M is the length of b and N is the length of s.
Solution. This problem is a generalization of substring search (is thereat least one consecutive copy of b within s?) so we need an algorithm that generalize ssubstring search. Create the Knuth-Morris-Pratt DFA for k concatenated copies of b, where k = N/M. Now, simulate DFA on input s and record the largest state that it reaches. From this, we can identify the longest tandem repeat.
- Suffix-prefix match. Design a linear-time algorithm to find the longest suffix of one string a that exactly matches a prefix of another string b.
- Cyclic rotation. Design a linear-time algorithm to determine whether one string is a cyclic rotation of another. A string a is a cyclic rotation of a string b if a and b have the same length and a consists of a suffix of b followed by a prefix of b.
- Substring of a circular string. Design a linear-time algorithm to determine whether one string a is a substring of a cirular string b.
- Longest palindromic substring.
Given a string s, find the longest substring that is a palindrome
(or a Watson-crick palindrome).
Solution: can be solved in linear time using suffix trees
or Manacher's algorithm.
Here's a simpler solution that typically runs in linearthmic time.
First, we describe how to find all palindromic substrings
of length exactly L in linear time: use Karp-Rabin to iteratively
form the hashes of each substring of length L (and its reverse),
Since you don't know L, repeatedly double your guess of L until
you know the optimal length is between L and 2L. Then use
binary search to find the exactly length.
Solution. Manacher.java is an implementation of Manacher's algorithm.
- Repeated substring. [
Given an integer K and a string of length N, find the longest substring which
appears at least K times.
One solution. Assume you know the length L of the repeated string. Hash each substring of length L, and check if any hash occurs K or more times. If so, check to make sure you didn't get unlucky. Since you don't know L, repeatedly double your guess of L until you know the optimal length is between L and 2L. Then use binary search to find the right value.
- Longest common substring. Given two (or three strings), find the longest substring that appears in all three. Hint: assume you know the length L of the longest common substring. Hash each substring of length L and check if any hash bucket contains (at least) one entry from each string.
- All matches. Modify KMP to find all matches in linear time (instead of leftmost match).
- Fibonacci string. Interesting case for KMP. F(1) = B, F(2) = A, F(3) = AB, F(4) = ABA, F(5) = ABAAB, F(N) = F(N-1) F(N-2).
- Suppose that x and y are two strings.
Design a linear-time algorithm to determine whether x^m = y^n for some
integers m and n (where x^m means the concatenation of m copies of x).
Solution. Suffices to check where xy = yx (this fact is nontrivial).