Martin Fajcik
PersonMartin Fajcik is documented in the provided evidence as a computer-science author of the 2018 arXiv paper “Automation of Processor Verification Using Recurrent Neural Networks,” which applies recurrent neural networks to coverage-guided processor verification.
First seen 5/24/2026
Last seen 5/26/2026
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Martin Fajcik
Martin Fajcik is documented in the available evidence as an author of the computer-science paper “Automation of Processor Verification Using Recurrent Neural Networks.” arXiv metadata lists the paper’s authors as Martin Fajcik, Marcela Zachariasova, and Pavel Smrz, with an online date of 2018-03-06 and arXiv identifier 1803.09810.[1]
Documented work
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1 connectionsMartin Fajcik is listed as an author of the paper.
LINKED ENTITIES
3 linksMarcela Zachariasova coauthor arXiv metadata lists Marcela Zachariasova as a coauthor on the same paper as Martin Fajcik.
Pavel Smrz coauthor arXiv metadata lists Pavel Smrz as a coauthor on the same paper as Martin Fajcik.
Codasip provided_demonstration_processors_for_publication The paper abstract states that processors provided by Codasip were used for demonstration purposes.
CITATIONS
5 sources5 citations — click to expand
[1] Martin Fajcik is listed as an author of “Automation of Processor Verification Using Recurrent Neural Networks,” alongside Marcela Zachariasova and Pavel Smrz; the arXiv metadata gives the date 2018-03-06 and arXiv ID 1803.09810. Automation of Processor Verification Using Recurrent Neural Networks
[2] The paper concerns simulation-based processor verification using pseudorandom generators, processor-input stimuli, and functional coverage monitoring. Automation of Processor Verification Using Recurrent Neural Networks
[3] The paper proposes dynamically altering constraints for a pseudorandom generator via a recurrent neural network receiving coverage feedback from simulation of the design under verification. Automation of Processor Verification Using Recurrent Neural Networks
[4] The authors used processors provided by Codasip for demonstration because their coverage state space was reasonably large and differed across processor types. Automation of Processor Verification Using Recurrent Neural Networks
[5] The paper abstract reports faster coverage closure and isolation of a small set of high-coverage stimuli usable for regression tests. Automation of Processor Verification Using Recurrent Neural Networks