Goal: Write a linear-time string matching algorithm in Swift that returns the indexes of all the occurrencies of a given pattern.
In other words, we want to implement an indexesOf(pattern: String) extension on String that returns an array [Int] of integers, representing all occurrences' indexes of the search pattern, or nil if the pattern could not be found inside the string.
For example:
let dna = "ACCCGGTTTTAAAGAACCACCATAAGATATAGACAGATATAGGACAGATATAGAGACAAAACCCCATACCCCAATATTTTTTTGGGGAGAAAAACACCACAGATAGATACACAGACTACACGAGATACGACATACAGCAGCATAACGACAACAGCAGATAGACGATCATAACAGCAATCAGACCGAGCGCAGCAGCTTTTAAGCACCAGCCCCACAAAAAACGACAATFATCATCATATACAGACGACGACACGACATATCACACGACAGCATA"
dna.indexesOf(ptnr: "CATA") // Output: [20, 64, 130, 140, 166, 234, 255, 270]
let concert = "🎼🎹🎹🎸🎸🎻🎻🎷🎺🎤👏👏👏"
concert.indexesOf(ptnr: "🎻🎷") // Output: [6]The Knuth-Morris-Pratt algorithm is considered one of the best algorithms for solving the pattern matching problem. Although in practice Boyer-Moore is usually preferred, the algorithm that we will introduce is simpler, and has the same (linear) running time.
The idea behind the algorithm is not too different from the naive string search procedure. As it, Knuth-Morris-Pratt aligns the text with the pattern and goes with character comparisons from left to right. But, instead of making a shift of one character when a mismatch occurs, it uses a more intelligent way to move the pattern along the text. In fact, the algorithm features a pattern pre-processing stage where it acquires all the informations that will make the algorithm skip redundant comparisons, resulting in larger shifts.
The pre-processing stage produces an array (called suffixPrefix in the code) of integers in which every element suffixPrefix[i] records the length of the longest proper suffix of P[0...i] (where P is the pattern) that matches a prefix of P. In other words, suffixPrefix[i] is the longest proper substring of P that ends at position i and that is a prefix of P. Just a quick example. Consider P = "abadfryaabsabadffg", then suffixPrefix[4] = 0, suffixPrefix[9] = 2, suffixPrefix[14] = 4.
There are different ways to obtain the values of SuffixPrefix array. We will use the method based on the Z-Algorithm. This function takes in input the pattern and produces an array of integers. Each element represents the length of the longest substring starting at position i of P and that matches a prefix of P. You can notice that the two arrays are similar, they record the same informations but on the different places. We only have to find a method to map Z[i] to suffixPrefix[j]. It is not that difficult and this is the code that will do for us:
for patternIndex in (1 ..< patternLength).reversed() {
textIndex = patternIndex + zeta![patternIndex] - 1
suffixPrefix[textIndex] = zeta![patternIndex]
}We are simply computing the index of the end of the substring starting at position i (as we know matches a prefix of P). The element of suffixPrefix at that index then it will be set with the length of the substring.
Once the shift-array suffixPrefix is ready we can begin with pattern search stage. The algorithm first attempts to compare the characters of the text with those of the pattern. If it succeeds, it goes on until a mismatch occurs. When it happens, it checks if an occurrence of the pattern is present (and reports it). Otherwise, if no comparisons are made then the text cursor is moved forward, else the pattern is shifted to the right. The shift's amount is based on the suffixPrefix array, and it guarantees that the prefix P[0...suffixPrefix[i]] will match its opposing substring in the text. In this way, shifts of more than one character are often made and lot of comparisons can be avoided, saving a lot of time.
Here is the code of the Knuth-Morris-Pratt algorithm:
extension String {
func indexesOf(ptnr: String) -> [Int]? {
let text = Array(self.characters)
let pattern = Array(ptnr.characters)
let textLength: Int = text.count
let patternLength: Int = pattern.count
guard patternLength > 0 else {
return nil
}
var suffixPrefix: [Int] = [Int](repeating: 0, count: patternLength)
var textIndex: Int = 0
var patternIndex: Int = 0
var indexes: [Int] = [Int]()
/* Pre-processing stage: computing the table for the shifts (through Z-Algorithm) */
let zeta = ZetaAlgorithm(ptnr: ptnr)
for patternIndex in (1 ..< patternLength).reversed() {
textIndex = patternIndex + zeta![patternIndex] - 1
suffixPrefix[textIndex] = zeta![patternIndex]
}
/* Search stage: scanning the text for pattern matching */
textIndex = 0
patternIndex = 0
while textIndex + (patternLength - patternIndex - 1) < textLength {
while patternIndex < patternLength && text[textIndex] == pattern[patternIndex] {
textIndex = textIndex + 1
patternIndex = patternIndex + 1
}
if patternIndex == patternLength {
indexes.append(textIndex - patternIndex)
}
if patternIndex == 0 {
textIndex = textIndex + 1
} else {
patternIndex = suffixPrefix[patternIndex - 1]
}
}
guard !indexes.isEmpty else {
return nil
}
return indexes
}
}Let's make an example reasoning with the code above. Let's consider the string P = ACTGACTA", the consequentially obtained suffixPrefix array equal to [0, 0, 0, 0, 0, 0, 3, 1], and the text T = "GCACTGACTGACTGACTAG". The algorithm begins with the text and the pattern aligned like below. We have to compare T[0] with P[0].
1
0123456789012345678
text: GCACTGACTGACTGACTAG
textIndex: ^
pattern: ACTGACTA
patternIndex: ^
x
suffixPrefix: 00000031
We have a mismatch and we move on comparing T[1] and P[0]. We have to check if a pattern occurrence is present but there is not. So, we have to shift the pattern right and by doing so we have to check suffixPrefix[1 - 1]. Its value is 0 and we restart by comparing T[1] with P[0]. Again a mismath occurs, so we go on with T[2] and P[0].
1
0123456789012345678
text: GCACTGACTGACTGACTAG
textIndex: ^
pattern: ACTGACTA
patternIndex: ^
suffixPrefix: 00000031
This time we have a match. And it continues until position 8. Unfortunately the length of the match is not equal to the pattern length, we cannot report an occurrence. But we are still lucky because we can use the values computed in the suffixPrefix array now. In fact, the length of the match is 7, and if we look at the element suffixPrefix[7 - 1] we discover that is 3. This information tell us that that the prefix of P matches the suffix of the susbtring T[0...8]. So the suffixPrefix array guarantees us that the two substring match and that we do not have to compare their characters, so we can shift right the pattern for more than one character!
The comparisons restart from T[9] and P[3].
1
0123456789012345678
text: GCACTGACTGACTGACTAG
textIndex: ^
pattern: ACTGACTA
patternIndex: ^
suffixPrefix: 00000031
They match so we continue the compares until position 13 where a misatch occurs beetwen charcter G and A. Just like before, we are lucky and we can use the suffixPrefix array to shift right the pattern.
1
0123456789012345678
text: GCACTGACTGACTGACTAG
textIndex: ^
pattern: ACTGACTA
patternIndex: ^
suffixPrefix: 00000031
Again, we have to compare. But this time the comparisons finally take us to an occurrence, at position 17 - 7 = 10.
1
0123456789012345678
text: GCACTGACTGACTGACTAG
textIndex: ^
pattern: ACTGACTA
patternIndex: ^
suffixPrefix: 00000031
The algorithm than tries to compare T[18] with P[1] (because we used the element suffixPrefix[8 - 1] = 1) but it fails and at the next iteration it ends its work.
The pre-processing stage involves only the pattern. The running time of the Z-Algorithm is linear and takes O(n), where n is the length of the pattern P. After that, the search stage does not "overshoot" the length of the text T (call it m). It can be be proved that number of comparisons of the search stage is bounded by 2 * m. The final running time of the Knuth-Morris-Pratt algorithm is O(n + m).
Note: To execute the code in the KnuthMorrisPratt.swift you have to copy the ZAlgorithm.swift file contained in the Z-Algorithm folder. The KnuthMorrisPratt.playground already includes the definition of the
Zetafunction.
Credits: This code is based on the handbook "Algorithm on String, Trees and Sequences: Computer Science and Computational Biology" by Dan Gusfield, Cambridge University Press, 1997.
Written for Swift Algorithm Club by Matteo Dunnhofer