Method and device for measuring regular expression state complexity

Abstract

The invention relates to a method and device for measuring regular expression state complexity. The method for the measuring regular expression state complexity comprises the steps that firstly, the curly relationship between any two states p and q in a given non-deterministic type finite automation M is judged, and the curly relationship is one of the five kinds of relationships: the mutual-exclusion relationship, the equivalence relationship, the included relationship, the including relationship and the independent relationship, M = (Q, sigma, delta, q0, F), the Q is a finite set, each element of the Q is called as a state, the sigma is a finite alphabet, each element of the sigma is called as an input character, the delta is a state transition function, and the q0 belongs to the Q, the q0 is the unique starting state, and the F is a terminal state set; two, the regular expression state complexity is estimated according to the judging result of the step one, the state complexity is the state number / Q' / of the deterministic type finite automation M'obtained by determining the M, and the M'=( Q', sigma, delta', q0', F'). The method and device for measuring regular expression state complexity can obtain the reasonable estimating value rapidly, and improve measuring efficiency.

Description

technical field [0001] The invention relates to the field of information technology, in particular to a method and device for measuring the state complexity of a regular expression. Background technique [0002] The complexity and scale of regular expressions in the deep packet inspection system make the classic NFA (Non-deterministic Finite Automaton, non-deterministic finite automaton) and DFA (Deterministic Finite Automaton, deterministic finite automaton) matching methods unable To achieve line speed matching requirements. At present, relevant researchers have proposed a large number of algorithms, architectures and data structures to match the problems of low efficiency and huge memory overhead. However, these works generally have the following problems: 1) Regular expression matching can only be applied on a small scale (dozens or hundreds of lines). Problem; 2) It is only for some special types of regular expressions, and it cannot be solved correctly or even solved...

AI Technical Summary

Problems solved by technology

[0002] The complexity and scale of regular expressions in the deep packet inspection system make the classic NFA (Non-deterministic Finite Automaton, non-deterministic finite automaton) and DFA (Deterministic Finite Automaton, deterministic finite automaton) matching methods unable Achieving Line Speed ​​Matching Requirements

At present, relevant researchers have proposed a large number of algorithms, architectures and data structures to match the problems of low efficiency and huge memory overhead

However, these works generally have the following problems: 1) Regular expression matching can only be applied on a small scale (dozens or hundreds of lines). Problem; 2) It is only for some special types of regular expressions, and it cannot be solved correctly or even solved for more complex regular expression matching, and it is not universal; 3) Through a large number of tests and comparisons in multiple optional results To find a better result to solve the problem, the preprocessing time is too long to cope with frequent updates of regular expressions

[0004] But in regular expression matching, what needs to be studied is the state complexity of regular expressions

Although the description capabilities of regular expressions and regular languages ​​are equivalent and interchangeable, the results of the above research cannot be directly used to achieve the purpose of quantitative analysis and reliable comparison of regular expressions

This is because the above research mainly focuses on giving the upper bound of the state complexity in the worst case, but most of the regular expressions in the real deep packet inspection system do not meet the conditions required to get the worst case, and only rely on The upper bound of the special case is not reliable for regular expression comparisons

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