According to Semiconductor Engineering, verification is often treated as a downstream collection of tests, regressions, dashboards, coverage reports, and signoff reviews. That model is out of step with modern products that span hardware, software, subsystems, and system domains while requirements and configurations keep shifting.
Adding more verification engines and automation is necessary, the article argues, but it does not solve the underlying problem: more activity does not automatically create more understanding. The real bottleneck is traceability at scale. When a requirement changes or a subsystem is reused, teams need to know what verification intent was affected, what assumptions were embedded, and whether earlier results still apply.
Verification outputs such as logs, waveforms, assertions, and coverage metrics are usually stored as local evidence rather than lifecycle knowledge. A passing regression result or coverage number lacks meaning without the requirement, configuration, design version, and assumptions that governed it. The proposed solution is a verification thread: a structured digital linkage among requirements, parameters, activities, configurations, and results.
Artifacts should become reusable evidence objects, preserving context so that results remain interpretable across audits, handoffs, and reuse. Since there is only one source, there are no differing viewpoints to compare; the piece presents this shift as essential to maintaining confidence in complex systems.