Bayesian Network Test Generation
TechniqueBayesian Network Test Generation is identified in the provided evidence as a coverage-guided test-generation technique based on Bayesian networks and discussed alongside other machine-learning approaches for processor verification.
First seen 5/25/2026
Last seen 5/25/2026
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Overview
Bayesian Network Test Generation refers, in the provided evidence, to coverage-guided test generation based on Bayesian networks. The cited source places it among machine-learning-based techniques used in the broader landscape of test generation for processor verification.
Verification context
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3 sources3 citations — click to collapse
[1] Bayesian Network Test Generation is identified as coverage-guided test generation based on Bayesian networks and is discussed alongside other machine-learning techniques. Efficient Cross-Level Processor Verification using Coverage-guided Fuzzing
[2] The surrounding verification context includes symbolic-execution-based formal methods for ISS-level test-case generation and fuzzing-based techniques for testing processor emulators against physical CPUs. Efficient Cross-Level Processor Verification using Coverage-guided Fuzzing
[3] The evidence lists RISC-V verification approaches including directed test suites, randomized-pattern instruction generation, constraint-based specifications, LLVM-libFuzzer-based coverage-guided fuzzing, and RTL cross-level co-simulation. Efficient Cross-Level Processor Verification using Coverage-guided Fuzzing