Genetically Programmed Pattern Matching for Overlapping Patterns

Created by W.Langdon from gp-bibliography.bib Revision:1.4221

  author =       "N. Nedjah and L. {de Macedo Mourelle}",
  title =        "Genetically Programmed Pattern Matching for
                 Overlapping Patterns",
  booktitle =    "The 2006 International Conference on Computer
                 Engineering and Systems",
  year =         "2006",
  pages =        "406--411",
  address =      "Cairo",
  month =        "5-7 " # nov,
  publisher =    "IEEE",
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "1-4244-0272-7",
  DOI =          "doi:10.1109/ICCES.2006.320482",
  abstract =     "Pattern matching is a fundamental feature in many
                 applications such as functional programming, logic
                 programming, theorem proving, term rewriting and
                 rule-based expert systems. Usually, patterns size is
                 not constrained and ambiguous patterns are allowed.
                 This generality leads to a clear and concise
                 programming style. However, it yields challenging
                 problems in compiling of such programming languages.
                 Generally, patterns are pre-processed into a
                 deterministic finite automaton. With ambiguous or
                 overlapping patterns a subject term may be an instance
                 of more than one pattern. In this case, pattern
                 matching order in lazy evaluation affects the size of
                 the matching automaton and the matching time.
                 Furthermore, it may even affect the termination
                 properties of term evaluations. In this paper, we
                 engineer good traversal orders that allow one to design
                 an efficient adaptive pattern-matchers that visit
                 necessary positions only. We do so using genetic
                 programming to evolve the most adequate traversal order
                 given the set of allowed patterns. Hence, we improve
                 time and space requirements of pattern-matching as well
                 as termination properties of term evaluation",

Genetic Programming entries for Nadia Nedjah Luiza de Macedo Mourelle