When changing Celery task dispatch semantics (especially Canvas: chains/groups/chords, unroll/freeze, and composed workflows), add regression tests that: - Cover edge/no-op compositions (e.g., empty/effectively-empty chains inside headers) to ensure they’re skipped and don’t hang. - Verify propagation of configured behavior across all primitives (e.g., a single `task_id_generator` used consistently throughout a canvas workflow). - Assert real execution/behavior, not only “no exception” (e.g., patch `apply_async` and confirm only intended tasks/bodies are applied). - Validate result metadata/stamping for nested compositions and replacements (e.g., group stamps are stored in the correct order and aren’t lost due to `replaced`). Example pattern for asserting the executed path (empty-chain chord header): ```python # chord whose header contains only empty chains should not apply header tasks from celery import chord, group, chain # header member is effectively empty empty_chain_sig = chain(tuple()) child_count = 24 child_chord = chord([empty_chain_sig], body=add.si(0, 0)) header = group([child_chord] * child_count) # patch Signature.apply_async and assert only chord bodies run header.apply_async() assert mock_apply_async.call_count == child_count ``` Apply this same approach when testing task-id generation and metadata stamping: freeze signatures, run the canvas workflow, and assert the expected `task_id` source and `_get_task_meta()` contents for each composed element.