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Existing tests verify aggregation math with synthetic data and basic sanity bounds, but don't confirm duct's measurements match actual resource usage. These tests run programs with known, predictable resource consumption and assert duct reports values within expected bounds: - Memory allocation: allocate N MB, verify peak_rss >= N MB - Wall clock time: sleep N seconds, verify reported time ~= N - Idle CPU: sleep reports near-zero CPU - CPU intensive: busy-loop reports significant CPU - Usage samples: verify JSONL structure and multiple reports - Consistent memory: held allocation visible across samples https://claude.ai/code/session_01FYRR4Y8PzNLBU344ovdDS5
Existing e2e tests verify duct counts child PIDs correctly, but never check that resource stats are actually aggregated across children. These new tests spawn multiple child processes with known memory allocations and verify: - Total RSS reflects sum across all children (N x M MB) - Individual child processes appear in usage.jsonl with correct RSS - total_rss in each sample equals the sum of per-process RSS values Adds test/data/memory_children.py helper that uses multiprocessing to fork N children each holding M MB for a specified duration. https://claude.ai/code/session_01FYRR4Y8PzNLBU344ovdDS5
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- Use assert to reference bytearray instead of _ prefix (F841) - Break long f-string debug line into separate variable (B950) https://claude.ai/code/session_01FYRR4Y8PzNLBU344ovdDS5
json.loads() returns Any, so return type annotations of dict/list[dict] trigger mypy's no-any-return check. Use Any instead. https://claude.ai/code/session_01FYRR4Y8PzNLBU344ovdDS5
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Summary
test/data/memory_children.pyhelper usingmultiprocessing.ProcessTest plan
test/duct_main/test_resource_validation.py)https://claude.ai/code/session_01FYRR4Y8PzNLBU344ovdDS5