How n8n Handles Partial Workflow Execution and Dependency State

A developer describes a common debugging problem: rerunning a single failed node in a workflow whose inputs come from several upstream nodes, some of which may have succeeded, failed, or never run. The article explains that the engine must reason about graph topology, prior execution history, and whether a node is eligible to run, rather than simply rerunning everything. It notes that reusing stored results risks stale data, while recomputing everything wastes resources and may repeat external side effects like API calls. The author argues that a simple scheduler checking only whether parent nodes have run is insufficient, because nodes may have produced zero items or be waiting on other branches. The piece points to n8n's WorkflowExecute implementation and its runPartialWorkflow2 function as starting points for studying this behavior.