Analog for Digital Engineers · All levels
Static and Dynamic DAC Metrics: INL/DNL, Glitch, and SFDR: Interview Drills
Interview Drills for Static and Dynamic DAC Metrics: INL/DNL, Glitch, and SFDR.
Interview drills
Interview Drills for Static and Dynamic DAC Metrics: INL/DNL, Glitch, and SFDR is anchored on DNL/INL limits, missing-code incidence, glitch impulse area at major carries, and SFDR/THD across output frequency sweep.. Convert observations into mechanism-backed and owner-bound actions.
PROMPT
You observe regression in DNL/INL limits, missing-code incidence, glitch impulse area at major carries, and SFDR/THD across output frequency sweep. for Static and Dynamic DAC Metrics: INL/DNL, Glitch, and SFDR. Explain root cause and release decision.
STRONG ANSWER
1. Defines failing boundary and operating context.
2. Explains mechanism: 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. Offset and gain errors are often calibratable, but code-dependent nonlinearity sets harder limits on precision. Dynamic metrics expose time-domain switching nonidealities: simultaneous bit toggles create glitch impulses, finite settling leaves residual error at the sample instant, and clock jitter or reference feedthrough introduces phase- and spur-related artifacts. In frequency-domain evaluation, SFDR captures the largest unwanted spur relative to the desired tone and is usually limited by mismatch, switching asymmetry, and output path distortion; THD and noise floor complete the picture for communication and instrumentation use cases. Strong evaluation practice links static bench data to dynamic spectral outcomes so teams can distinguish root causes such as mismatch, timing skew, or reference network weakness.
3. Requests proving artifact: Measurement plan connecting static sweep plots (INL/DNL) to dynamic FFT results (SFDR/THD/glitch-sensitive tones).
4. Proposes bounded fix + owner + rollback-safe validation.
WEAK ANSWER
Gives generic analog advice without mechanism proof, evidence, or ownership.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 filterMetric 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.