{"schema_version":1,"experiment_id":"eoa_inverse_innovation_exp09_archetype_breadth150_20260804","cell_id":"search_space_pruning__computer_science","arm":"BREADTH_PROBE_ONE_SHOT","candidate_id":"search_space_pruning__computer_science__P1","proposal_index":1,"version":0,"title":"Auditable Configuration-Branch Pruning for Production-Failure Replay","problem":"After a software failure appears only under a production configuration, responders may face a combinatorial set of feature-flag values, service versions, dependency modes, and environment settings. The available replay capacity is insufficient to execute every configuration, while informal guesses can prematurely discard the configuration family containing the cause.","actors":["Incident commander","Site reliability engineer","Service owner","Replay-environment operator","Post-incident reviewer"],"observable_state":"A captured failure signature and production snapshot exist, but the incident workspace contains more candidate configuration branches than the replay environment can execute within its stated run budget; responders cannot reconstruct why some branches were skipped.","consequence":"Replay capacity is spent on configurations contradicted by known runtime evidence, investigation is delayed, and an unrecorded exclusion can conceal the configuration interaction needed to reproduce the failure.","affected_objective":"Identify at least one configuration that reproduces the captured failure signature within a fixed replay budget while retaining an explainable path to reconsider excluded configuration regions.","intervention":"Construct a configuration-search tree from the incident snapshot. Separate hard facts—such as observed flag values, loaded module versions, impossible dependency combinations, and required event ordering—from preferences about likely causes. Apply constraint filtering only to branches that contradict hard facts; defer rather than delete branches supported only by weak heuristics. Among surviving branches, remove configurations dominated by another configuration that exercises the same implicated components with no greater replay cost. Retain representatives from distinct component and flag families, record every exclusion with its rule and evidence, sample excluded branches for false negatives, and reopen a branch when its supporting fact is corrected or its audit sample reproduces the failure.","structural_mapping":[{"archetype_element":"Search Space Definition","domain_realization":"All replayable assignments of incident-relevant feature flags, service versions, dependency modes, and environment settings within the isolated incident snapshot."},{"archetype_element":"Candidate or Region Representation","domain_realization":"A tree whose levels assign configuration variables and whose branches represent partial or complete replay configurations."},{"archetype_element":"Objective or Success Criterion","domain_realization":"Reproduce the captured failure signature within the declared number of replay executions."},{"archetype_element":"Constraint Filter","domain_realization":"Reject a branch only when it contradicts an authenticated runtime observation or a validated compatibility rule."},{"archetype_element":"Dominance Check","domain_realization":"Remove a configuration when another surviving configuration covers the same implicated components and event preconditions at equal or lower replay cost."},{"archetype_element":"Diversity Preservation Rule","domain_realization":"Keep at least one uncertain representative from each distinct implicated component or feature-flag family until evidence resolves that family."},{"archetype_element":"False-Negative Review","domain_realization":"Replay a prespecified sample of excluded configurations and compare their signatures with the incident signature."},{"archetype_element":"Reentry or Exception Path","domain_realization":"Restore an excluded branch when source evidence changes, a compatibility rule is invalidated, or an audited exclusion reproduces the failure."},{"archetype_element":"Pruning Audit Trail","domain_realization":"For each excluded branch, store the rule, evidence reference, assumptions, timestamp, and approving responder."}],"mechanism_mapping":[{"mechanism_slug":"constraint_filtering","role":"Eliminates configuration branches that cannot match recorded runtime facts or validated dependency constraints before costly replay.","counterfactual_removal":"Without constraint filtering, contradicted branches continue consuming the bounded replay queue, so the search remains largely combinatorial."},{"mechanism_slug":"dominated_option_removal","role":"Eliminates redundant replay configurations covered by a no-costlier surviving configuration under the declared component and event criteria.","counterfactual_removal":"Without dominated-option removal, many fact-compatible but informationally redundant configurations remain, limiting the capacity available for distinct configuration families."},{"mechanism_slug":"sample_audit_of_exclusions","role":"Tests a fixed sample of pruned branches to detect invalid constraints or overly coarse exclusions.","counterfactual_removal":"Without exclusion sampling, a mistaken rule can silently remove the reproducing region and leave no operational signal that pruning failed."}],"causal_chain":["Production evidence and compatibility rules are converted into explicit branch predicates.","Predicates remove only branches inconsistent with hard evidence, while uncertain branches are deferred or retained.","Dominance checks remove replay-equivalent configurations that provide no additional implicated-component coverage at lower cost.","Diversity preservation keeps distinct uncertain configuration families reachable.","The smaller surviving set fits the bounded replay queue and receives deeper execution.","Audit samples test whether excluded regions contain matching failure signatures.","Logged reasons and reentry triggers allow mistaken exclusions to be reversed."],"baseline":"Responders manually choose replay configurations from the production snapshot using individual suspicions, with no common branch representation, exclusion log, diversity requirement, or systematic check of skipped configurations.","nearest_rivals":["Delta debugging, which repeatedly removes changes after obtaining a reproducible failing case; the proposed intervention instead governs which configuration regions receive scarce replay attempts when no compact reproducer yet exists.","Combinatorial interaction testing, which selects configurations to achieve interaction coverage; the proposed intervention excludes branches using incident-specific evidence and maintains reentry rather than optimizing general coverage.","Feature-flag inventory filtering, which lists or queries flags but does not supply dominance rules, false-negative audits, or an accountable exception path.","Failure-correlation ranking, which orders likely causes but does not justify hard elimination of configuration branches."],"remaining_contrastive_claim":"The candidate is specifically an incident-replay allocation procedure: it converts captured runtime facts into auditable branch exclusions while preserving diverse uncertain regions and sampled reentry. Its distinguishing claim is not that it ranks likely causes or guarantees a minimal reproducer, but that it makes pre-replay elimination reviewable under a fixed execution budget.","authority_safety":{"decision_authority":"The incident commander owns the replay budget and approves temporary pruning criteria; the service owner validates configuration semantics, and the tool itself has advisory authority only.","authorized_first_step":"Run the procedure in shadow mode on one archived incident snapshot, using an isolated replay environment and a fixed set of previously recorded candidate configurations.","excluded_actions":["Changing live production flags or service versions","Suppressing alerts or production telemetry","Deleting raw incident evidence or excluded configurations","Automatically declaring a root cause","Using heuristic scores as hard exclusion rules","Extending pruning rules to unrelated incidents without review"],"halt_rollback":"Stop the exercise and restore the unpruned replay list if a hard constraint excludes the archived reproducing configuration, an audit sample produces the target failure signature, evidence provenance cannot be reconstructed, or no configuration family remains represented. Preserve the log and invalidate the responsible rule before any restart."},"negative_tests":{"strongest_counterevidence":"The approach is undermined if the archived reproducing configuration is repeatedly pruned despite correct evidence capture, or if constructing and auditing predicates consumes at least as much constrained replay capacity as direct execution of the candidate set.","problem_falsifier":"The problem is absent when all fact-compatible configurations fit within the available replay budget and responders can execute them safely before the incident decision deadline.","intervention_falsifier":"The intervention fails its core logic if, under the declared rules, the known reproducing configuration becomes unreachable or exclusion audits cannot identify the rule that removed it.","risks":["Incomplete telemetry may turn an apparent hard fact into a false exclusion.","Coarse compatibility rules may prune an entire branch containing a viable subconfiguration.","Dominance dimensions may omit a component interaction that matters to the failure.","Diversity quotas may retain superficial variation while losing behaviorally distinct configurations.","Detailed configuration logs may expose secrets or sensitive infrastructure metadata.","Responders may treat advisory pruning as authoritative during time pressure.","Stale rules copied from an earlier incident may no longer match the deployed system."]},"next_evidence_step":"On one archived incident with a known reproducing configuration, freeze a maximum of 40 candidate configurations and a replay allowance of 12 executions. Before revealing the known reproducer to the pruning operator, build the branch representation, apply only evidence-cited rules, retain representatives across implicated component families, and reserve two of the 12 executions for randomly selected exclusions. Record whether the known reproducer remains reachable, whether every exclusion is reconstructable, how many candidates survive, and whether either exclusion sample matches the archived failure. This tests feasibility and false-negative controls without deployment or a claim of effect.","prior_art_status":"UNSEARCHED","diversity_from_prior_proposals":"Not assessed because runtime isolation forbids inspecting other proposals; this is a single one-shot candidate derived only from the supplied archetype and domain card.","revision_record":{"parent_version":null,"progress_targets_addressed":[],"conceptual_changes":[],"operational_changes":[],"evidence_changes":[],"claim_changes":[]}}