trace

Evidence-driven debugging traces ambiguous runtime failures by orchestrating parallel hypothesis generation and evidence collection. It assigns independent tracer lanes to gather supporting and contradicting evidence, ranks hypotheses by strength, and proposes a single discriminating probe.

Investigating a performance regression requires generating multiple competing explanations and running parallel tracer lanes to collect evidence from logs, metrics, and configs. The process ranks hypotheses by evidence strength, runs rebuttal rounds, and identifies the root cause through falsification checks.

Hypothesis-driven incident analysis supports architecture postmortems by restating observations, generating competing explanations, and directing team-mode tracer workers to gather evidence. It ranks evidence, detects convergence between explanations, and returns a synthesis with the single best discriminating probe.

Tracing experimental result discrepancies uses parallel evidence gathering across logs, metrics, configs, and code artifacts. Tracer lanes collect evidence for and against each hypothesis, identify critical unknowns, execute falsification checks, and output a ranked synthesis pinpointing the causal failure.

Parallel hypothesis tracing operates without external dependencies, using internal tracer workers to collect evidence and rank explanations. It orchestrates independent lanes that gather supporting and contradicting evidence, run rebuttals, and synthesize results without requiring additional components.

Falsification checks may be unnecessary for simple, deterministic bugs where the root cause is already obvious. This structured approach is designed for ambiguous, evidence-heavy causal failures where multiple competing hypotheses require parallel evidence collection and ranking to identify the discriminating probe.