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dnn-binary-code-similarity's Issues

Hello, I need the data set mentioned in your paper

The data set I need is"Dataset IV:This dataset contains vulnerable functions obtained from the vulnerability dataset in [18]. In total, it contains of 154vulnerable functions."
[18] Qian Feng, Rundong Zhou, Chengcheng Xu, Yao Cheng, Brian Testa, and Heng Yin. 2016. Scalable Graph-based Bug Search for Firmware Images. In ACM Conference on Computer and Communications Security (CCS’16).
But I didn't find the address of this data set in his paper. Could you help me

How dose the features come from?

Hi,

When I looked at the data, I saw that in each line, you have features of each node. I'm wondering how you generated those features. I didn't find that in your paper, either. I really appreciate your reply. Thanks a lot.

training auc is equal validation auc?

in line 140 of the train.py

        if (i % TEST_FREQ == 0):
            auc, fpr, tpr, thres = get_auc_epoch(gnn, Gs_train, classes_train,
                    BATCH_SIZE, load_data=valid_epoch)     #valid_epoch?
            gnn.say("Testing model: training auc = {0} @ {1}".format(
                auc, datetime.now()))
            auc, fpr, tpr, thres = get_auc_epoch(gnn, Gs_dev, classes_dev,
                    BATCH_SIZE, load_data=valid_epoch)
            gnn.say("Testing model: validation auc = {0} @ {1}".format(
                auc, datetime.now()))

partial results:

Initial training auc = 0.8385795480339078 @ 2021-01-14 10:49:18.571989
Initial validation auc = 0.8385795480339078 @ 2021-01-14 10:49:26.453895
EPOCH 1/100, loss = 0.6696747210700994 @ 2021-01-14 10:52:33.539342
Testing model: training auc = 0.9225966099742847 @ 2021-01-14 10:52:41.815191
Testing model: validation auc = 0.9225966099742847 @ 2021-01-14 10:52:49.352049
Model saved in ./saved_model/graphnn-model_best
EPOCH 2/100, loss = 0.6475605093730598 @ 2021-01-14 10:55:58.523499
Testing model: training auc = 0.9278334338892803 @ 2021-01-14 10:56:06.467269
Testing model: validation auc = 0.9278334338892803 @ 2021-01-14 10:56:14.051002

so should I change it as the following?

        if (i % TEST_FREQ == 0):
            auc, fpr, tpr, thres = get_auc_epoch(gnn, Gs_train, classes_train,
                    BATCH_SIZE, load_data=None) #change valid_epoch into None
            gnn.say("Testing model: training auc = {0} @ {1}".format(
                auc, datetime.now()))
            auc, fpr, tpr, thres = get_auc_epoch(gnn, Gs_dev, classes_dev,
                    BATCH_SIZE, load_data=valid_epoch)
            gnn.say("Testing model: validation auc = {0} @ {1}".format(
                auc, datetime.now()))

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