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Marcela Zachariasova

Person WIKI v2 · 5/27/2026

Marcela Zachariasova is documented in the provided evidence as a co-author of the 2018 arXiv paper "Automation of Processor Verification Using Recurrent Neural Networks".

Marcela Zachariasova

Marcela Zachariasova is identified in arXiv metadata as a co-author of the paper "Automation of Processor Verification Using Recurrent Neural Networks", posted online on 2018-03-06 as arXiv:1803.09810v1. The same arXiv page also renders the name with diacritics as Marcela Zachariásová.

Documented work

The provided evidence documents Zachariasova's authorship of "Automation of Processor Verification Using Recurrent Neural Networks", alongside Martin Fajcik and Pavel Smrz. The paper addresses simulation-based processor verification, where pseudorandom generators produce stimuli and achieved functional coverage is monitored to assess verification completeness.

According to the arXiv abstract, the paper proposes using a recurrent neural network to dynamically alter pseudorandom-generator constraints based on coverage feedback from simulation of the design under verification. For demonstration, the authors used processors provided by Codasip. The reported experimental results state that coverage closure was reached sooner and that the method could isolate a small high-coverage stimulus set for regression testing.

Evidence status

Only authorship and paper-level technical details are supported by the provided evidence. No independently sourced biographical details, institutional affiliation, employment history, education, or additional publications were provided.

CITATIONS

5 sources
5 citations
[1] Marcela Zachariasova is listed in arXiv metadata as an author of "Automation of Processor Verification Using Recurrent Neural Networks". Automation of Processor Verification Using Recurrent Neural Networks
[2] The arXiv page renders the author's name with diacritics as Marcela Zachariásová. Automation of Processor Verification Using Recurrent Neural Networks
[3] The paper was posted online on 2018-03-06 as arXiv:1803.09810. Automation of Processor Verification Using Recurrent Neural Networks
[4] The paper proposes dynamically altering pseudorandom-generator constraints via a recurrent neural network using coverage feedback from simulation of the design under verification. Automation of Processor Verification Using Recurrent Neural Networks
[5] For demonstration, the paper used processors provided by Codasip and reported faster coverage closure plus isolation of a small high-coverage stimulus set for regression tests. Automation of Processor Verification Using Recurrent Neural Networks

VERSION HISTORY

v2 · 5/27/2026 · gpt-5.5 (current)
v1 · 5/25/2026 · gpt-5.5