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Penka Borukova Student at Telerik Academy. 1. Boyer Moore String Search Algorithm 2. The bad character rule 3. The good suffix rule 4. The algorithm itself.

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Presentation on theme: "Penka Borukova Student at Telerik Academy. 1. Boyer Moore String Search Algorithm 2. The bad character rule 3. The good suffix rule 4. The algorithm itself."— Presentation transcript:

1 Penka Borukova Student at Telerik Academy

2 1. Boyer Moore String Search Algorithm 2. The bad character rule 3. The good suffix rule 4. The algorithm itself 2

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4  Finds pattern in text  Useful for very large text  Space and time are expensive!  Some definitions  S[i…n] – suffix  S[1…i] – prefix  P – Pattern  T – Text 4

5  Boyer-Moore uses information gained by preprocessing P to skip as many alignments as possible  The strings are matched from the end and toward the beginning of P  The comparisons continue until either a mismatch occurs or the beginning of P is reached (which means of P is reached (which means there is a match) there is a match) 5

6  When mismatch is found Bad Character Rule Good Suffix Rule Bad Character Rule Good Suffix Rule 6

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8  The idea of bad character rule is to shift P by more than one characters when possible  R(x): The right-most occurrence of character x in P  R(x)=0 if x does not occur in the pattern  When mismatch is found shift is found shift it over underneath it over underneath 8

9 Pattern -> ABBABAA R(‘A’) = 1; R(‘B’)= 2; R(x) = 0; x >=0 && x =0 && x < 256 && x != ‘A’ && x != ‘B’ 9ABCABCBBCAABBABAA ABCABCBBCAABBABAA

10  Bad character rule focuses on characters  Work well in practice with large alphabets like the English alphabet  Work less well with small alphabets like DNA  Space required: O(|  ) for the number of characters in the alphabet 10

11  2D table indexed first by the index of the character c in the Alphabet and second by the index i in the Pattern  Return the occurrence of c in P with the next- highest index j < i or -1 if there is no such occurrence  The proposed shift will then be i - j  Space required: O(n|  |) 11

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13  Good suffix rule focuses on substrings  L’(i): For each i, L’(i) is the largest position less than n such that substring P[i,…,n] matches a suffix of P[1,…, ’(i) ]  with the additional requirement that the character preceding that suffix is not equal to character P[i-1]  If there is no such a position, L’(i) =0. 13

14  Example: 14ABCABCABCAAABCAACA ABCABCABCAAABCAACA

15  l’(i) : the length of the largest suffix of P[i,…,n], that is also a prefix of P  If none exists, then l’(i)=0. 15ABCABCABCAACACA ABCABCABCAACACA

16  Example: Indexes of P: Pattern: Pattern: l’(i) : l’(i) : L’(i) : L’(i) : 16012345678910CCACBCCBACC 22222222221 00000000063

17  Precompute L’(i), l’(i) for each position in P  Precompute R(x) or R(x,i) for each character x in   Align P to T  Compare right to left  On mismatch, shift by the max possible from (extended) bad character rule and good suffix rule and return to compare 17

18  O(m + n) - if the pattern does not appear in the text  O(nm) - when the pattern occurs in the text  This is the worst case 18

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21  http://en.wikipedia.org/wiki/Boyer%E2%80%9 3Moore_string_search_algorithm http://en.wikipedia.org/wiki/Boyer%E2%80%9 3Moore_string_search_algorithm http://en.wikipedia.org/wiki/Boyer%E2%80%9 3Moore_string_search_algorithm  http://www.iti.fh- flensburg.de/lang/algorithmen/pattern/bmen. htm http://www.iti.fh- flensburg.de/lang/algorithmen/pattern/bmen. htm http://www.iti.fh- flensburg.de/lang/algorithmen/pattern/bmen. htm  http://www.cs.ucdavis.edu/~gusfield/cs224f09/ bnotes.pdf http://www.cs.ucdavis.edu/~gusfield/cs224f09/ bnotes.pdf http://www.cs.ucdavis.edu/~gusfield/cs224f09/ bnotes.pdf  http://www-igm.univ- mlv.fr/~lecroq/string/node14.html http://www-igm.univ- mlv.fr/~lecroq/string/node14.html http://www-igm.univ- mlv.fr/~lecroq/string/node14.html 21

22  “C# Programming @ Telerik Academy  csharpfundamentals.telerik.com csharpfundamentals.telerik.com  Telerik Software Academy  academy.telerik.com academy.telerik.com  Telerik Academy @ Facebook  facebook.com/TelerikAcademy facebook.com/TelerikAcademy  Telerik Software Academy Forums  forums.academy.telerik.com forums.academy.telerik.com 22


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