Factor Oracle, Suffix Oracle

Matthieu Raffinot

Institut Gaspard-Monge, Université de Marne-la-Vallée

Algorithms Seminar

October 4, 1999

[summary by Alain Denise and Matthieu Raffinot]

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The aim of this work is to design efficient algorithms for string matching. For this purpose, we introduce a new kind of automaton: the factor oracle, associated with the string p to be recognized in a text. This leads to simple algorithms which are as efficient in time as already known ones, while using less memory. This is a joint work with Cyril Allauzen and Maxime Crochemore.

1   Introduction

The efficiency of string matching algorithms depends on the underlying automaton which represents the string p to be found in the text. Ideally, this automaton A should satisfy the following properties:
  1. A is acyclic;
  2. A recognizes at least the factors of p;
  3. A has the fewer states as possible;
  4. A has a linear number of transitions according to m, the length of p. (Such an automaton has at least m+1 states.)
The suffix or factor automaton [3, 5] satisfies 1., 2., and 4. but not 3. whereas the subsequence automaton [2] satisfies 1., 2., and 3. but not 4. We present in Section 2 an intermediate structure called factor oracle: an automaton with m+1 states that satisfies all the above requirements. Section 3 is devoted to the study of a string matching algorithm based on the factor oracle.

2   Construction of the Factor Oracle

Figure 1: High-level construction of the Oracle.

The factor oracle of a word p=p1p2... pm, denoted Oracle(p), is the automaton built by the algorithm Build_Oracle (Figure 1). All the states of the automaton are final. Figure 2 gives the factor oracle of the word p=abbbaab. On this example, the reader will notice that the word aba is recognized whereas it is not a factor of p.

Figure 2: Factor oracle of abbbaab.

Here are some notations which are used in the following. The set of all prefixes (resp. suffixes) of p is denoted by Pref(p) (resp. Suff(p)). The word prefp(i) is the prefix of length i of p for 0£ i£ m. For any uÎFact(p), we define
poccur(u,p)=min {  |z||z=wu and p=wuv  } ,
the ending position of the first occurrence of u in p. For any uÎFact(p), we define the set
endposp(u)={ i| p=wupi+1... pm }.
Given two factors u and v of p, we write u~p v if endposp(u)=endposp(v).

The authors prove in [1] the following lemmas.

Lemma 1   Given a state i of Oracle(p), let uÎS* be a minimal length word among the words recognized in i. Then uÎFact(p) and i=poccur(u,p).

Corollary 1   For any state i of Oracle(p), there exists an unique minimal length word among the words recognized in state i.

We denote min(i) the minimal length word of state i.

Corollary 2   Let i and j be two states of Oracle(p) such that j<i. Then min(i) cannot be a suffix of min(j).

Lemma 2   Let i be a state of Oracle(p). Then min(i) is a suffix of any word cÎS* which is the label of a path leading from state 0 to state i.

Lemma 3   Any word wÎFact(p) is recognized by Oracle(p) in a state j£poccur(w,p).

Corollary 3   Let wÎFact(p). Every word vÎSuff(w) is recognized by Oracle(p) in a state j£poccur(w).

Lemma 4   Let i be a state of Oracle(p). Any path ending by min(i) leads to a state j³ i.

Lemma 5   Let wÎ S* be a word recognized by Oracle(p) in i. Any suffix of w is recognized in a state j£ i.

Lemma 6   The number TOr(p) of transitions in Oracle(p=p1p2... pm) satisfies m £ TOr(p) £ 2m-1.

The high-level construction of the factor oracle is equivalent to the on-line algorithm given in Figure 3. An example of this construction is shown in Figure 4.

Figure 3: On-line construction of Oracle(p=p1p2... pm).

The on-line construction of Oracle(abbbaab) is given Figure 4.

Figure 4: On-line construction of Oracle(abbaba).

3   String Matching

The authors replace the suffix automaton with a factor oracle in the BDM (for backward dawg matching) [4, 6], obtaining the BOM (for backward oracle matching) algorithm.

The BOM algorithm consists in shifting a window of size m on the text. For each new position of this window, the factor oracle of the mirror image of p is used to search the suffix of the window from right to left. The basic idea is that if this backward search fails on a letter s after the reading of a word u then s u is not a factor of p and the beginning of the window can be shifted just after s. The worst-case complexity of BOM is O(nm).

The average complexity of the original BDM is in O(nlog|S|(m)/m) under a uniform Bernoulli model. In view of the experimental results (see [1]), the authors claim that their new BOM algorithm is also optimal on average:
Conjecture 1   Under a model of independence and equiprobability of letters, the BOM algorithm has an average complexity of O(nlog|S|(m)/m).
The authors show in [1] how to obtain a linear (in n) worst case algorithm from the BOM.


Allauzen (Cyril), Crochemore (Maxime), and Raffinot (Mathieu). -- Oracle des facteurs, oracle des suffixes. -- Technical Report n°99-08, Institut Gaspard-Monge, Université de Marne-la-Vallée, 1999. Available from http://www-igm.univ-mlv.fr/~raffinot/ftp/IGM99-08.ps.gz.

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