This book offers a structured methodology for applying generative AI to the functional verification of complex semiconductor designs without sacrificing engineering accountability. It presents the VEGA framework—Verification Engineering through Guided AI—a complete verification lifecycle that treats AI as a governed accelerator, preserving traceability between design intent and verification evidence from specification through silicon sign-off.
Verification is the dominant schedule risk on most modern silicon programs. Modern SoCs contain billions of transistors and dozens of independently developed IP blocks, and large language models have rapidly entered hardware verification practice. Yet no comprehensive reference exists that explains how to integrate LLMs into industrial UVM-based verification flows with the rigor that pre-silicon engineering demands. This book closes that gap.
Across eight technical chapters, the book develops a complete methodology grounded in fifteen years of industrial verification practice. It introduces the Executable TestPlan as the central verification strategy artifact, a manifest-driven testbench architecture that governs AI-generated infrastructure, and scenario contracts for LLM-assisted test generation across functional, stress, and fault-injection categories. It reframes debug as classification anchored to design intent, extends the framework to subsystem verification through the Subsystem Intent Graph for cross-IP integration, and reconstructs verification sign-off as an evidence-based argument. The book closes with a ten-metric quality suite organized into three families—generation-side (Repair Efficiency Score, Verification Gap, Specification Coverage Ratio, Hallucination Rate), specification-side (Programming Model Coverage, Contract Violation Latency, Descriptor Fidelity Score, Observability Score), and process-side (Autonomy Index, Regeneration Stability)—for quantitatively evaluating AI-assisted verification pipelines.

The primary audience is hardware verification engineers, verification architects, and verification leads in industry, particularly those working on SoC, subsystem, and protocol-bridge verification. The secondary audience includes graduate students and faculty in electrical and computer engineering programs teaching functional verification, UVM, and SystemVerilog. The tertiary audience comprises EDA tool researchers, managers introducing AI into pre-silicon verification flows, and standards-body members working on emerging verification methodology specifications.

Vikash Kumar is Senior Verification Architect at Arm with over 15 years of experience in the semiconductor industry, specializing in the design and verification of complex semiconductor systems across IP, subsystem, and full System-on-Chip (SoC) levels. His work focuses on large-scale SoC integration, functional correctness, debug, and verification closure for high-performance designs using Verilog, SystemVerilog, and UVM. Prior to joining Arm, Vikash held engineering roles at Aricent Technologies and Intel, where he contributed to several large-scale silicon programs including the Intel Data Streaming Accelerator and Intel Analytics Accelerator. He has extensive hands-on experience with industry-standard interconnect and chiplet protocols including AMBA (AXI), CHI5, PCIe, and UCIe and has worked deeply on integration-level verification where subtle cross-boundary assumptions can lead to late-stage silicon escapes. He holds a Bachelor of Technology in Electronics and Communication Engineering from West Bengal University of Technology (W.B.U.T.), Kolkata, India.