Verification IP & Protocol Compliance ยท All levels
Active vs Passive Agent Modes: Interview Drills
Interview Drills for Active vs Passive Agent Modes.
Interview drills
Interview Drills for Active vs Passive Agent Modes focuses on stimulus/check independence score and dual-mode regression pass rate. The purpose is to turn memory observations into mechanism-backed actions with explicit owners and release-safe validation.
PROMPT
You observe stimulus/check independence score and dual-mode regression pass rate on Active vs Passive Agent Modes. Explain root cause and release decision.
STRONG ANSWER
1. Defines failing traffic context and first transition loss.
2. Explains mechanism: Active agents generate protocol-correct traffic while passive agents observe and check without driving the bus. Mode selection affects who owns stimulus, how monitors attach, and whether compliance suites can run against third-party DUT environments without agent contention.
3. Requests proving artifact: agent mode matrix, contention log, and dual-mode regression report
4. Proposes bounded fix + owner + rollback-safe validation.
WEAK ANSWER
Gives generic VIP tuning ideas without checker evidence, owner accountability, or risk controls.Interview evidence matrix
VIP EVIDENCE MATRIX - Active vs Passive Agent Modes
+-------------------------------+--------------------------------+--------------------------------+---------------------------+
| Evidence | Tells you | Does not prove | Next action |
+-------------------------------+--------------------------------+--------------------------------+---------------------------+
| checker hit/miss + ACT/PRE mix | locality and row-state cost | lane-level capture integrity | inspect training margins |
| queue age + class breakdown | fairness and starvation risk | command legality details | parse command timeline |
| spec clause legality + bus timeline | timing-window pressure | root cause by itself | correlate with traffic map|
| eye / Vref / skew snapshots | PHY margin and drift behavior | controller policy quality | pair with schedule logs |
| CE/UE + scrub telemetry | reliability trajectory | immediate perf bottleneck only | map to hotspot addresses |
+-------------------------------+--------------------------------+--------------------------------+---------------------------+VIP deep dive
Reusable VIP layering, agent roles, monitor/scoreboard contracts, and packaging patterns that scale across protocols and projects.
Concept diagram
VIP SECTION - VIP Architecture & Packaging
testcase -> agents -> checkers -> coverage -> evidenceMetric graph
checker noise vs real violations trendReports and artifacts
checker hit report
coverage closure sheet
compliance trace matrix
regression health snapshot
Mini case study
A profile drift caused false checker storms until configuration hashes were locked in CI.
Debug branches
Reproduce with locked seed and profile
Isolate checker vs scoreboard vs DUT paths
Map failure to spec clause and owner
Senior review question
Ask: which latency, bandwidth, and reliability evidence proves this VIP topic is closed under real traffic?
Key takeaways
Always tie controller and PHY counter shifts to application latency and throughput outcomes.
Lock firmware timing profile, thermal condition, and DIMM state before comparing VIP captures.
Common pitfalls
Chasing peak bandwidth while ignoring p99 latency and fairness tails.
Changing timing guardbands without separating SI noise from scheduling issues.
Declaring closure without reliability gates, fault injection, and regression replay.
VIP atlas notes
Active vs Passive Agent Modes should be read as an end-to-end VIP behavior, not as a single block definition. Production compliance closure reflects interactions between agents, checkers, coverage, and customer evidence before tapeout or IP release claims.
Active agents generate protocol-correct traffic while passive agents observe and check without driving the bus. Mode selection affects who owns stimulus, how monitors attach, and whether compliance suites can run against third-party DUT environments without agent contention. VIP inefficiency is multiplicative: one weak checker enable, one hollow coverage bin, or one non-reproducible failure repeated across regressions can dominate signoff risk.