This repository implements BTD, a deep neural network (DNN) executable decompiler for x86 binaries. It recovers model specifications (operator types, topology, dimensions, parameters) from DNN executables compiled by TVM, Glow, and NNFusion frameworks. The system uses dynamic binary instrumentation via Intel Pin to collect execution traces, applies symbolic execution and taint analysis to recover tensor shapes, extracts parameters from memory dumps, and rebuilds models in PyTorch for correctness verification. The architecture consists of interconnected Python scripts and Pin tools organized around a three-phase decompilation pipeline: trace collection and filtering, shape recovery via symbolic execution, and parameter extraction. Key entry points include evaluation shell scripts (decompile_eval.sh, op_infer_eval.sh) and model-specific decompile/rebuild scripts in the evaluation/ directory. The system relies on external dependencies including Intel Pin 3.14, IDA Pro 7.5 (optional), and specific compiler versions (TVM v0.7-v0.9, Glow 2020-2022, NNFusion).