Test Program Bring-up: From Characterization Script to Screening Flow: Worked Example

Worked example

Worked Example for Test Program Bring-up: From Characterization Script to Screening Flow is anchored on First-pass test-program pass rate on known-good silicon, escaped-defect proxy rate, and debug turnaround time per failing test block.. Convert observed behavior into mechanism-backed and owner-bound actions.

A release blocker appears in First-pass test-program pass rate on known-good silicon, escaped-defect proxy rate, and debug turnaround time per failing test block.. Strong closure isolates first failing boundary, proves mechanism, applies one reversible fix, and validates blast radius before signoff.

Execution lens

SILICON BRING-UP FLOW - Test Program Bring-up: From Characterization Script to Screening Flow

symptom intake and setup state freeze
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dependency map: power/reset/clock/interface/firmware
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instrumented experiment with one-variable branch
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first failing boundary classification
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bounded mitigation and replay validation
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owner signoff with rollback criteria

Decision matrix

EVIDENCE MATRIX - Test Program Bring-up: From Characterization Script to Screening Flow

+-------------------------------+--------------------------------+--------------------------------+-----------------------------+
| Evidence                      | Tells you                      | Does not prove                 | Next action                 |
+-------------------------------+--------------------------------+--------------------------------+-----------------------------+
| rail/current timeline         | sequencing and power health    | firmware or protocol integrity | align with stage logs       |
| stage checkpoint logs         | failing transition boundary    | electrical root cause          | correlate with scope traces |
| interface trace/decode        | protocol behavior and timing   | global platform readiness      | replay under fixed setup    |
| shmoo/corner matrix           | margin-sensitive fail region   | exact failing mechanism        | isolate with targeted tests |
| before/after replay packet    | mitigation movement quality    | long-run stability             | run soak and corner matrix  |
+-------------------------------+--------------------------------+--------------------------------+-----------------------------+

Silicon bring-up deep dive

Correlation succeeds when tester and bench experiments share identical conditions and evidence expectations.

Concept diagram

CORRELATION LADDER

ATE fail bin -> extract pattern -> reproduce on bench -> reconcile deltas

Metric graph

CORRELATION CONFIDENCE

unmatched signatures     █████
partial matches          ████
full context matches     ███████

Metrics and artifacts to collect

• ATE-to-bench signature match ratio

• pattern replay fidelity score

• environment mismatch incident rate

• yield-impact closure tracker

Mini case study

Correlation speed improved dramatically after enforcing shared metadata headers and one replay protocol across tester and lab.

Debug branches

• Normalize V/F/T and pattern-window metadata first.

• Audit fixture and probing assumptions before silicon blame.

• Require repeatable signature in both environments before closure.

Senior review question

Ask: what is the first failing boundary, which artifact proves it, and who owns bounded closure?

Key takeaways

• Tie every bring-up claim to one reproducible setup state and one proving artifact.

• Prefer bounded fixes with clear owner and rollback trigger over broad multi-variable edits.

Common pitfalls

• Running parallel uncontrolled experiments and losing causality.

• Declaring closure without replaying across representative corners.

• Escalating severity before bench/setup hypotheses are disproven.

Worked-example reasoning

Start with synchronized evidence rather than speculative fixes.

Keep mitigation reversible until recurrence risk is measured.