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N-Version Genetic Programming via Fault Masking

  • Kosuke Imamura
  • Heckendorn Robert B. 
  • Terence Soule
  • Foster James A. 
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2278)

Abstract

We introduce a new method, N-Version Genetic Programming (NVGP), for building fault tolerant software by building an ensemble of automatically generated modules in such a way as to maximize their collective fault masking ability. The ensemble itself is an example of n-version modular redundancy for fault tolerance, where the output of the ensemble is the most frequent output of n independent modules. By maximizing collective fault masking, NVGP approaches the fault tolerance expected from n version modular redundancy with independent faults in component modules. The ensemble comprises individual modules from a large pool generated with genetic programming, using operators that increase the diversity of the population. Our experimental test problem classified promoter regions in Escherichia coli DNA sequences. For this problem, NVGP reduced the number and variance of errors over single modules produced by GP, with statistical significance.

Keywords

Genetic Program Component Module Replacement Candidate Optimal Linear Combination Fault Tolerant Software 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Kosuke Imamura
    • 1
  • Heckendorn Robert B. 
    • 1
  • Terence Soule
    • 1
  • Foster James A. 
    • 1
  1. 1.Initiative for Bioinformatics and Evolutionary Studies (IBEST), Dept. of Computer ScienceUniversity of IdahoMoscow

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