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config.py
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config.py
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# choose what binary you want to generate the dataset
version = ["openssl-101f"]
arch = ["x86"]
compiler = ["gcc", "clang"]
optimizer = ["O0", "O1", "O2", "O3"]
dir_name = "data/extracted-acfg/"
# VulSeeker
vulseeker_rawdata_dir = "data/openssl/"
vulseeker_dataset_dir = "data/vulseeker/"
vulseeker_feature_size = 8
vulseeker_model_save_path = "output/vulseeker/vulseeker_model_weight"
vulseeker_figure_save_path = "output/vulseeker/"
# Gemini
Gemini_rawdata_dir = "data/extracted-acfg"
Gemini_dataset_dir = "data/Gemini/"
Gemini_feature_size = 9 # (max_constant_1,max_constant_2,num of strings,....)
Gemini_model_save_path = "output/Gemini/Experiment_2/model_weight"
Gemini_figure_save_path = "output/Gemini/"
# some details about dataset generation
max_nodes = 500
min_nodes_threshold = 0
Buffer_Size = 1000
mini_batch = 10
# some params about training the network
learning_rate = 0.0001
epochs = 30
step_per_epoch = 5000
valid_step_pre_epoch = 3000
test_step_pre_epoch = 3000
T = 5
embedding_size = 64
embedding_depth = 2