mirror of
https://github.com/azaion/ai-training.git
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Oleksandr Bezdieniezhnykh
a47fa135de
- Modified `.gitignore` to include test fixture data while excluding test results. - Updated `config.yaml` to change the model from 'yolo11m.yaml' to 'yolo26m.pt'. - Enhanced `.cursor/rules/coderule.mdc` with additional guidelines for test environment consistency and infrastructure handling. - Revised autopilot state management in `_docs/_autopilot_state.md` to reflect current progress and tasks. - Removed outdated augmentation tests and adjusted dataset formation tests to align with the new structure. These changes streamline the configuration and testing processes, ensuring better organization and clarity in the project.
20 lines
789 B
Markdown
20 lines
789 B
Markdown
# Resilience Test Scenarios
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## RT-DSF-01: Dataset formation with empty data directory
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- **Input**: Empty data images dir
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- **Action**: Run `form_dataset()`
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- **Expected**: Creates empty train/valid/test directories; no crash
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- **Traces**: Restriction: Edge case handling
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## RT-ENC-01: Decrypt with corrupted ciphertext
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- **Input**: Randomly modified ciphertext bytes
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- **Action**: `Security.decrypt_to(corrupted_bytes, key)`
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- **Expected**: Either raises exception or returns garbage bytes (not original)
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- **Traces**: AC: Encryption integrity
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## RT-AQM-01: Malformed msgpack message
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- **Input**: Random bytes that aren't valid msgpack
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- **Action**: Pass to message handler
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- **Expected**: Exception caught; handler doesn't crash
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- **Traces**: AC: Error handling for malformed messages
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