The SPARC architecture manual: version 8
The SPARC architecture manual: version 8
Genetic programming (videotape): the movie
Genetic programming (videotape): the movie
A compiling genetic programming system that directly manipulates the machine code
Advances in genetic programming
Computer architecture (2nd ed.): a quantitative approach
Computer architecture (2nd ed.): a quantitative approach
Linear-Graph GP - A New GP Structure
EuroGP '02 Proceedings of the 5th European Conference on Genetic Programming
Evolutionary Test Program Induction for Microprocessor Design Verification
ATS '02 Proceedings of the 11th Asian Test Symposium
Automatic test program generation for pipelined processors
Proceedings of the 2003 ACM symposium on Applied computing
Fully Automatic Test Program Generation for Microprocessor Cores
DATE '03 Proceedings of the conference on Design, Automation and Test in Europe - Volume 1
High level validation of next-generation microprocessors
HLDVT '02 Proceedings of the Seventh IEEE International High-Level Design Validation and Test Workshop
Efficient machine-code test-program induction
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
IBM Journal of Research and Development
Automatic Test Program Generation: A Case Study
IEEE Design & Test
Code Generation for Functional Validation of Pipelined Microprocessors
Journal of Electronic Testing: Theory and Applications
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Test programs are fragment of code, but, unlike ordinary application programs, they are not intended to solve a problem, nor to calculate a function. Instead, they are supposed to give information about the machine that actually executes them. Today, the need for effective test programs is increasing, and, due to the inexorable increase in the number of transistor that can be integrated onto a single silicon die, devising effective test programs is getting more problematical. This paper presents µGP, an efficient and versatile approach to test-program generation based on an evolutionary algorithm. The proposed methodology is highly versatile and improves previous approaches, allowing the test-program generator generating complex assembly programs that include subroutines calls.