freemo
8e6642e8c9
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Extended _compute_affected_subtree() to BFS over both the structural tree (parent-child plan relationships) and decision_dependencies edges (influence DAG). The algorithm performs a single O(V+E) BFS pass that unions neighbors from both edge sources, using a visited set for cycle detection to guard against data corruption. Decision creation now supports dependency_decision_ids parameter in record_decision() which populates the in-memory influence DAG store. get_influence_edges() returns the adjacency list format consumed by CorrectionService. All public CorrectionService methods (analyze_impact, execute_revert, execute_correction, generate_dry_run_report) accept an optional influence_edges parameter while remaining backward-compatible (defaults to None, preserving structural-only traversal when not provided). Key design decisions: - Single BFS pass over union of structural + influence edges rather than separate traversals, ensuring O(V+E) complexity and consistent visit order - Cycle detection via visited set with warning log (not an error) since cycles indicate data corruption, not a programming error - Influence edge logging: traversal emits count of influence edges processed for observability - Backward-compatible API: existing callers that only pass decision_tree continue to work identically ISSUES CLOSED: #542
125 lines
5.6 KiB
Gherkin
125 lines
5.6 KiB
Gherkin
Feature: Influence DAG traversal in correction affected subtree
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The affected subtree computation must traverse BOTH the structural
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tree (parent-child) AND the influence DAG (decision_dependencies)
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edges so that corrections cascade through influence relationships.
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# ================================================================
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# Structural-only (existing behaviour preserved)
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# ================================================================
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Scenario: Structural-only subtree with no influence edges
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Given an influence-aware correction service
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And a correction request targeting decision "D1" in plan "P1" for revert
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And a structural tree where "D1" has children "D2,D3" and "D2" has children "D4"
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And no influence edges
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When I analyze the impact with influence support
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Then the affected decision set should be "D1,D2,D3,D4"
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Scenario: Structural-only single node
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Given an influence-aware correction service
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And a correction request targeting decision "D1" in plan "P1" for revert
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And a structural tree with no children for "D1"
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And no influence edges
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When I analyze the impact with influence support
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Then the affected decision set should be "D1"
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# ================================================================
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# Influence-only (new behaviour)
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# ================================================================
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Scenario: Influence-only affected subtree finds linked decisions
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Given an influence-aware correction service
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And a correction request targeting decision "D1" in plan "P1" for revert
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And a structural tree with no children for "D1"
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And influence edges where "D1" influences "D5,D6" and "D5" influences "D7"
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When I analyze the impact with influence support
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Then the affected decision set should be "D1,D5,D6,D7"
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Scenario: Influence-only with no structural children
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Given an influence-aware correction service
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And a correction request targeting decision "DX" in plan "P1" for revert
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And a structural tree with no children for "DX"
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And influence edges where "DX" influences "DY"
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When I analyze the impact with influence support
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Then the affected decision set should be "DX,DY"
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# ================================================================
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# Combined structural + influence (union)
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# ================================================================
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Scenario: Combined structural and influence subtree is the union
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Given an influence-aware correction service
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And a correction request targeting decision "D1" in plan "P1" for revert
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And a structural tree where "D1" has children "D2,D3"
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And influence edges where "D1" influences "D4" and "D3" influences "D5"
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When I analyze the impact with influence support
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Then the affected decision set should be "D1,D2,D3,D4,D5"
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Scenario: Overlapping structural and influence edges deduplicate
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Given an influence-aware correction service
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And a correction request targeting decision "D1" in plan "P1" for revert
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And a structural tree where "D1" has children "D2"
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And influence edges where "D1" influences "D2"
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When I analyze the impact with influence support
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Then the affected decision set should be "D1,D2"
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# ================================================================
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# Cycle detection (corrupt data)
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# ================================================================
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Scenario: Cycle in influence DAG is handled gracefully
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Given an influence-aware correction service
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And a correction request targeting decision "D1" in plan "P1" for revert
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And a structural tree with no children for "D1"
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And influence edges with a cycle "D1" to "D2" to "D3" back to "D1"
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When I analyze the impact with influence support
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Then the affected decision set should be "D1,D2,D3"
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And no infinite loop occurred
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Scenario: Self-loop in influence DAG is handled gracefully
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Given an influence-aware correction service
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And a correction request targeting decision "D1" in plan "P1" for revert
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And a structural tree with no children for "D1"
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And influence edges where "D1" influences "D1"
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When I analyze the impact with influence support
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Then the affected decision set should be "D1"
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# ================================================================
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# Decision creation populates decision_dependencies
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# ================================================================
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Scenario: Decision creation records influence dependencies
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Given a decision service for influence tracking
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When I record a root decision "strategy_choice" for the tracked plan
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And I record a child decision "implementation_choice" depending on the root decision
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Then the influence edges for the tracked plan should link the root to the child
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Scenario: Decision creation without dependencies records no edges
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Given a decision service for influence tracking
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When I record a root decision "strategy_choice" for the tracked plan
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Then the influence edges for the tracked plan should be empty
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# ================================================================
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# Revert execution with influence edges
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# ================================================================
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Scenario: Revert with influence edges invalidates all affected
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Given an influence-aware correction service
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And a correction request targeting decision "D1" in plan "P1" for revert
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And a structural tree where "D1" has children "D2"
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And influence edges where "D1" influences "D3"
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When I execute the revert with influence support
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Then the reverted decisions should include "D1"
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And the reverted decisions should include "D2"
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And the reverted decisions should include "D3"
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