Reports & Metrics for LBIST Overview focuses on LBIST signature quality, random-pattern-resistant fault count, runtime budget. The goal is to convert metric movement into mechanism, owner, and release decision.
A report should support a release decision for LBIST signature quality, random-pattern-resistant fault count, runtime budget. One headline number is rarely enough without setup tags and bucket-level evidence.
METRIC GRAPH - LBIST signature quality, random-pattern-resistant fault count, runtime budget
quality metric
^
| target
| - - - - - - -
| o after fix + regression
| o
| o baseline
| o regressed run
+--------------------------------------> closure iteration
input audit focused fix signoff review
Readout:
- explain what moved, why it moved, and who approved itPATTERN HISTOGRAM - LBIST Overview
pattern count
| ***
| *******
| ***********
|************* <- high-volume tail (optimize here)
+--------------------> pattern buckets
smoke stuck-at transition diagnosis
Balance quality and tester limits together.Track LBIST signature quality, random-pattern-resistant fault count, runtime budget by context and pattern class.
Review trend and bucket detail together.
Keep quality, timing, and power metrics in one dashboard.
Store each metric next to the artifact and run tag.
BIST value is realized only when insertion, diagnosis, and repair are tied to production flow.
BIST FLOW
insert MBIST/LBIST -> execute -> collect signatures -> diagnose/repair -> signoffREPAIR EFFECT
yield
^
| o pre-repair
| o post-repair
+---------------------> lotMBIST insertion coverage
repair signature report
LBIST resistant fault list
BIST release checklist
Fuse programming mismatch blocked repair activation; corrected bring-up script recovered expected yield uplift.
Validate BIST reachability
Correlate fail maps to repair signatures
Audit in-field boot test budget
Ask: what evidence proves this DFT decision is safe for production?
State metric, lot/corner context, and pattern tag with every claim.
Treat timing, power, and quality as one signoff problem.
Chasing coverage without legality checks.
Ignoring test-power side effects of pattern changes.
Debugging silicon without reproducible tags.
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