Genetic programming in the wild

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Genetic programming in the wild: evolving unrestricted bytecode

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Genetic And Evolutionary Computation Conference archive
Proceedings of the 11th Annual conference on Genetic and evolutionary computation table of contents

Montreal, Québec, Canada

SESSION: Track 10: genetic programming table of contents

Pages 1043-1050

Year of Publication: 2009

ISBN:978-1-60558-325-9

Authors

Michael Orlov	Ben-Gurion University, Beer-Sheva, Israel
Moshe Sipper	Ben-Gurion University, Beer-Sheva, Israel

Sponsors

SIGEVO: ACM Special Interest Group on Genetic and Evolutionary Computation
ACM: Association for Computing Machinery

Publisher

ACM New York, NY, USA

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ABSTRACT

We describe a methodology for evolving Java bytecode, enabling the evolution of extant, unrestricted Java programs, or programs in other languages that compile to Java bytecode. Bytecode is evolved directly, without any intermediate genomic representation. Our approach is based upon the notion of compatible crossover, which produces correct programs by performing operand stack-, local variables-, and control flow-based compatibility checks on source and destination bytecode sections. This is in contrast to existing work that uses restricted subsets of the Java bytecode instruction set as a representation language for individuals in genetic programming. Given the huge universe of unrestricted Java bytecode, as is programs, our work enables the applications of evolution within this realm. We experimentally validate our methodology by both extensively testing the correctness of compatible crossover on arbitrary bytecode, and by running evolution on a program that exploits the richness of the Java virtual machine architecture and type system.

REFERENCES

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