{"id":"resource-bounding-uses-dual-fidelity-strategies","text":"The codebase systematically bounds resource consumption through two orthogonal fidelity-reduction strategies: deterministic truncation (bounded deques, version pruning, click history caps) silently drops the oldest data in time-ordered domains, while probabilistic approximation (Bloom filters, SimHash, HyperLogLog, Morris counters) tolerates statistical error in set-membership domains — together covering both sequential and presence/absence resource bounding.","truth_value":"IN","source":"","source_url":"","source_hash":"","justifications":[{"type":"SL","antecedents":["memory-is-bounded-at-the-cost-of-silent-information-loss","probabilistic-dedup-trades-memory-for-coverage"],"outlist":[],"label":"deterministic truncation (time-ordered) and probabilistic approximation (set-membership) are complementary bounding strategies"}],"dependents":["monotonic-state-is-bounded-by-fidelity-not-reversal","state-is-temporally-and-spatially-bounded","two-tier-state-preserves-authority-under-monotonicity"],"metadata":{"last_reviewed":"2026-06-06T06:26:57","review_result":"pass"},"created_at":"","updated_at":"","reviewed_at":"","verified_at":"","retracted_at":"","explanation":{"steps":[{"node":"resource-bounding-uses-dual-fidelity-strategies","truth_value":"IN","reason":"SL justification valid","antecedents":["memory-is-bounded-at-the-cost-of-silent-information-loss","probabilistic-dedup-trades-memory-for-coverage"],"label":"deterministic truncation (time-ordered) and probabilistic approximation (set-membership) are complementary bounding strategies"},{"node":"memory-is-bounded-at-the-cost-of-silent-information-loss","truth_value":"IN","reason":"SL justification valid","antecedents":["bounded-collections-trade-completeness-for-memory","probabilistic-structures-trade-accuracy-for-space"],"label":"Deterministic truncation and probabilistic approximation are two faces of the same bounded-memory commitment"},{"node":"bounded-collections-trade-completeness-for-memory","truth_value":"IN","reason":"SL justification valid","antecedents":["news-feed-cache-is-bounded-deque","nearby-friends-history-bounded-100","url-shortener-click-history-bounded","gdrive-version-list-bounded"],"label":"Silent eviction via capped collections is the repo's standard memory-bounding pattern"},{"node":"news-feed-cache-is-bounded-deque","truth_value":"IN","reason":"premise"},{"node":"nearby-friends-history-bounded-100","truth_value":"IN","reason":"premise"},{"node":"url-shortener-click-history-bounded","truth_value":"IN","reason":"premise"},{"node":"gdrive-version-list-bounded","truth_value":"IN","reason":"premise"},{"node":"probabilistic-structures-trade-accuracy-for-space","truth_value":"IN","reason":"SL justification valid","antecedents":["hll-default-precision","morris-counter-32-estimators","simhash-threshold-default-3"],"label":"HLL, Morris, and SimHash all trade tunable accuracy for sub-linear space"},{"node":"hll-default-precision","truth_value":"IN","reason":"premise"},{"node":"morris-counter-32-estimators","truth_value":"IN","reason":"premise"},{"node":"simhash-threshold-default-3","truth_value":"IN","reason":"premise"},{"node":"probabilistic-dedup-trades-memory-for-coverage","truth_value":"IN","reason":"SL justification valid","antecedents":["crawler-three-layer-dedup","probabilistic-structures-trade-accuracy-for-space"],"label":"Each dedup layer uses a different probabilistic tradeoff; bounded memory is the unifying constraint across all three"},{"node":"crawler-three-layer-dedup","truth_value":"IN","reason":"SL justification valid","antecedents":["crawler-layered-dedup-bloom-then-simhash","bloom-filter-prevents-frontier-duplicates","crawler-normalize-once-convention"],"label":"Each layer catches what the others miss — normalization handles canonicalization, Bloom handles exact revisits, SimHash handles content clones"},{"node":"crawler-layered-dedup-bloom-then-simhash","truth_value":"IN","reason":"premise"},{"node":"bloom-filter-prevents-frontier-duplicates","truth_value":"IN","reason":"premise"},{"node":"crawler-normalize-once-convention","truth_value":"IN","reason":"premise"}]}}