Static and Dynamic DAC Metrics: INL/DNL, Glitch, and SFDR: Expanded Case Study

Extended case study

A production issue linked to Static and Dynamic DAC Metrics: INL/DNL, Glitch, and SFDR appears after integration under realistic activity stress.

Background

Block-level checks looked healthy. Cross-domain interactions under corner conditions exposed hidden assumptions.

Symptoms observed

• DNL/INL limits, missing-code incidence, glitch impulse area at major carries, and SFDR/THD across output frequency sweep. degrades in one or more stressed modes

• bench and simulation disagree on trend shape

• ownership of root cause is unclear across analog, digital, and SI teams

Investigation timeline

1. Hour 0: lock workload, board, firmware, and environmental metadata.

2. Hour 1: capture synchronized analog/digital/power evidence.

3. Hour 2: classify first failing boundary and eliminate decoys.

4. Hour 3: run one high-confidence reproducer with controlled perturbation.

5. Hour 4: apply smallest reversible mitigation.

6. Hour 5: validate on representative stress matrix.

7. Hour 6: publish closure packet and residual-risk notes.

Root cause

Root cause traced to Static and Dynamic DAC Metrics: INL/DNL, Glitch, and SFDR: Static metrics quantify code-domain accuracy: DNL measures actual step size relative to 1 LSB and determines monotonicity risk, while INL measures cumulative deviation from an ideal transfer line and bounds low-frequency linearity.

Fix and validation

• Document the failing assumption explicitly.

• Implement bounded design or configuration mitigation.

• Attach measurable before-after evidence and ownership signoff.

Lessons learned

• Early assumption mapping shortens mixed-signal debug loops.

• Path-based analysis beats block-only analysis for integration failures.

• Guard-bands should be tied to measured transfer behavior, not habit.

CASE STUDY - Static and Dynamic DAC Metrics: INL/DNL, Glitch, and SFDR
margin / jitter / noise / stability trend before-after

Analog deep dive

DAC closure needs both static transfer quality and dynamic glitch/spectral discipline.

Concept diagram

DAC OUTPUT CHAIN

code mapping -> switching network -> output path -> reconstruction filter

Metric graph

DAC RISK MIX

major-carry glitches     █████
settling residuals       ████
image leakage            ███

Metrics and artifacts to collect

• INL/DNL sweep package

• glitch energy and settling trend

• SFDR/THD versus output frequency

• reconstruction filter compliance

Mini case study

Good static linearity masked dynamic spur failures driven by switching asymmetry and insufficient reconstruction margin.

Debug branches

• Tie static transfer plots to dynamic spectral outcomes.

• Inspect major-carry behavior separately from small-step transitions.

• Validate output path with realistic load and package parasitics.

Senior review question

Ask: which source-path-victim boundary failed first, and which artifact proves it reproducibly?

Key takeaways

• Tie every analog claim to one measurable metric and one proving artifact.

• Prefer minimal reversible mitigations with explicit owner and rollback criteria.

Common pitfalls

• Treating all noise as one scalar instead of path and frequency dependent behavior.

• Changing multiple analog knobs at once and losing causality.

• Declaring closure from nominal behavior without stress replay evidence.

Principal analog review addendum

Static and Dynamic DAC Metrics: INL/DNL, Glitch, and SFDR should be reviewed as an end-to-end execution problem spanning architecture, implementation, and integration.

Use DNL/INL limits, missing-code incidence, glitch impulse area at major carries, and SFDR/THD across output frequency sweep. as the trigger metric and Measurement plan connecting static sweep plots (INL/DNL) to dynamic FFT results (SFDR/THD/glitch-sensitive tones). as the proof contract.

DAC closure requires both static linearity discipline and dynamic switching-spectrum control. Durable closure comes from explicit assumptions and owner accountability.