radar_trace 0.2.0

Pure-Dart tracer framework with monotonic spans, log-linear latency histograms, Zone-based async nesting, and a lossless outlier ring.

0.2.0

• New series module: MetricSample, SeriesGap, and MetricSeries (JSON with schemaVersion: 1), plus assessSeries producing a SeriesAssessment with a SeriesVerdict (monotonicGrowth / plateau / noisy / insufficientData). Implements the field-proven growth methodology: settle-window trim, gap-aware region selection (gaps are never bridged), init-free batch2-minus-batch1 delta, Theil-Sen robust slope, degrees-of-freedom-preserving noise (first-difference sigma combined with residual sigma), Mann-Kendall certification of growth verdicts (bounds the false-growth rate under pure noise at 0.5% one-sided; measured 0.07% over 12k seeded trials), and end-shift checks so late crashes cannot read as growth and late rises cannot read as a bounded plateau. Details claim only measured facts and quantify the detection floor. Honest degradation throughout: a signal that cannot be truthfully computed reads insufficientData / null — never a plausible number.

0.1.2

• Optional dedupKey on Tracer.trace / traceAsync / start — a caller-supplied signature (e.g. arguments) marking repeated invocations of the same operation. SpanKeyStatsSnapshot.duplicateCount reports how many spans repeated a previously-seen signature for a key (bounded to ~1024 signatures), distinct from any statistical "hot" heuristic. Span.dedupKey carries the joined signature.

0.1.1

• Docs only (no code change): document the per-key SpanKeyStatsSnapshot metrics — callsPerSecond, avgInterCallIntervalMicros, meanMicros, maxMicros, totalMicros, firstStartMicros, lastStartMicros — in the README.

0.1.0

• Initial release: Span model, LatencyHistogram, OutlierRing, TraceRecorder, TraceSnapshot, Tracer façade with Zone-based nesting.
• Added per-key call metrics to SpanKeyStatsSnapshot: firstStartMicros, lastStartMicros, avgInterCallIntervalMicros (null when count < 2), callsPerSecond (null when count < 2 or window is zero), meanMicros, maxMicros, totalMicros — all exact (no bucket approximation).