justification-addition-is-robust-across-graph-states
IN derived (depth 4)
Adding a justification to an existing node achieves fully consistent multi-dimensional propagation — truth values, dependents index, and access tags — even when the dependency graph contains dangling references or lifecycle-marked nodes, because propagation safely handles both graph anomalies and node lifecycle states.
Summary
When you add a new justification to a node that already exists, the system reliably updates everything — truth values, dependency tracking, and access tags — even if the graph is in a messy state with broken references or nodes that have been marked for cleanup. This matters because it means the operation is safe to perform at any time without worrying about corrupting the network, since the system gracefully skips over problems rather than crashing or producing inconsistent results.
Justifications
SL — Consistent justification propagation combined with graph-inconsistency safety ensures robust state transitions regardless of graph quality
Antecedents (all must be IN):
- add-justification-achieves-consistent-propagation — Adding a justification to an existing node produces a fully consistent network state through guaranteed-terminating multi-dimensional propagation: truth values cascade via BFS through dependents, the reverse index is updated, and access tags recompute transitively — all within a single operation whose termination is guaranteed by BFS traversal and stop-on-unchanged semantics.
- propagation-is-safe-under-graph-inconsistency — Truth propagation achieves correctness even when the dependency graph contains dangling references: missing nodes are skipped with structured warnings rather than crashing, dangling IDs are excluded from both the changed and visited sets, and this graceful degradation composes with the underlying termination and lifecycle-awareness guarantees for all reachable nodes.
Dependents
These beliefs depend on this one:
- all-mutations-preserve-integrity-under-adverse-conditions — Every structural modification to the belief network preserves integrity even under adverse graph conditions: mutations are uniquely identifiable, auditable, and topology-preserving, while justification addition achieves consistent multi-dimensional propagation even when the dependency graph contains dangling references.
- all-truth-changes-are-topology-complete-and-robust — All forms of truth change — both cascading propagation and justification addition — achieve topology-complete multi-dimensional consistency under all graph states: truth values, dependents index, and access tags cascade to every transitively dependent node including through outlist connections, even when the graph contains dangling references.