Onur Guzey

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— Generating tests to achieve high coverage in simulation-based functional verification can be very challenging. Constrained-random and coverage-directed test generation methods have been proposed and shown with various degrees of success. In this paper, we propose a new tool built on top of an existing constrained random test generation framework. The goal(More)
Extensive software-based simulation continues to be the mainstream methodology for functional verification of designs. To optimize the use of limited simulation resources, coverage metrics are essential to guide the development of effective test suites. Traditional coverage metrics are defined based on either a functional model or a structural model of the(More)
<para> Success of simulation-based functional verification depends on the quality and diversity of the verification tests that are simulated. The objective of test generation methods is to generate tests that exercise as much different functionality of the hardware designs as possible. In this paper, we propose a novel methodology that generates a model of(More)
In simulation-based functional verification, composing and debugging testbenches can be tedious and time-consuming. A simulation data-mining approach, called TTPG (C. Wen, L-C Wang et al., 2005), was proposed as an alternative for functional test pattern generation. However, the core of simulation data-mining approach is Boolean learning, which tries to(More)
iv ACKNOWLEDGEMENTS It is a pleasure to thank everybody who made this thesis possible. It is difficult to overstate my gratitude to my advisor, Professor Ryan Kastner. With his inspiration, enthusiasm, and great efforts to explain things simply and clearly, he helped to make computer architecture fun for me. I also thank to Professor Ronald Iltis and(More)
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