2022 Wishlist for LLTFI: Feature Requests and Bug Fixes

[uditagarwal97]

We are continuously improving LLTFI to make it more versatile and robust. This issue tracks all the feature requests and bug fixes that we plan to add to LLTFI in 2022.
Feel free to request a new feature or bug fix by opening a new Github issue for it and then linking it back to this post.

Bug Fixes

• Improve the tool's documentation.
• Check if the GUI and the webapp still work. Update them to use the recent versions of Java and NodeJS. (Check the functionality of webapp and the GUI #9 )

Feature Requests

• Add docker image for LLTFI (Add docker image for LLTFI #5 )
• Use multiple threads to concurrently run multiple FI experiments (Use multiple threads to concurrently run multiple FI experiments #6 )
• Add support for RNNs (onnx-mlir failed with rnn-mnist benchmark #2 )
• Add fault model to support FI into DNN's weights and biases (memory-based FI) (Add fault model to support FI into DNN's weights and biases #7 )
• Check if LLTFI works correctly with the Caffee2 framework. Add Caffe2 benchmarks. (Add more benchmarks #8 )
• Add Apollo Baidu as a benchmark (Add more benchmarks #8 )
• Upgrade the ONNX-MLIR version (Update the onnx-mlir version #10)
• Add ML-level fault propagation tracing (Migrate, document, and test the code for ML-level error propogation tracing #29)
• Add documentation for using fault propagation tracing (Migrate, document, and test the code for ML-level error propogation tracing #29)