Code and Data for RENN published at ASE 2019
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Code and some pretrained models of the proposed DL technique are in folder
rnns. We also include the implementation of the baseline models used in this paper. In particular,stats.pyis used for some necessary statistics;ValueSet_RNN.pycontains the implementation of each model and training evaluation;conditional_main.pyandtest.pyare used for training and testing respectively. -
Code of crash analysis is in folder
crash_analysis. RENN takes the memory regions predicted by deep learning and leverage the alias relationship to assist reverse execution. -
Code of Intel Pin tools to record ground truth is in folder
pin_tools.