Adaptive Pattern Matching on Binary Data

Abstract

Pattern matching is an important operation in functional programs. So far, pattern matching has been investigated in the context of structured terms. This paper presents an approach to extend pattern matching to terms without (much of a) structure such as binaries which is the kind of data format that network applications typically manipulate. After introducing a notation for matching binary data against patterns, we present an algorithm that constructs a tree automaton from a set of binary patterns. We then show how the pattern matching can be made adaptive, how redundant tests can be avoided, and how we can further reduce the size of the resulting automaton by taking interferences between patterns into account. The effectiveness of our techniques is evaluated using implementations of network protocols taken from actual telecom applications. © Springer-Verlag 2004.