| SourcererCC |
Min lines: 6, Similarity threshold: 0.7 |
| Deckard |
Min tokens: 100, Stride: 2, Similarity threshold: 0.9 |
| RtvNN |
RtNN phase: hidden layer size: 400, epoch: 25, $\lambda_1$ for L2 regularization: 0.005, Initial learning rate: 0.003, Clipping gradient range: (-5.0, 5.0), RvNN phase: hidden layer size: (400, 400)-400, epoch: 5, Initial learning rate: 0.005, $\lambda_1$ for L2 regularization: 0.005, Distance threshold: 2.56 |
| ASTNN |
symbols embedding size: 128, hidden dimension: 100, mini-batch: 64, epoch: 5, threshold: 0.5, learning rate of AdaMax: 0.002 |
| SCDetector |
distance measure: Cosine distance, dimension of token vector: 100, threshold: 0.5, learning rate: 0.0001 |
| DeepSim |
Layers size: 88-6, (128x6-256-64)-128-32, epoch: 4, Initial learning rate: 0.001, $\lambda$ for L2 regularization: 0.00003, Dropout: 0.75 |
| CDLH |
Code length 32 for learned binary hash codes, size of word embeddings: 100 |
| TBCNN |
Convolutional layer dim size: 300，dropout rate: 0.5, batch size: 10 |
| FCCA |
Size of hidden states: 128(Text), 128(AST), embedding size: 300(Text), 300(AST), 64(CFG) clipping gradient range: (-1.2，1.2), epoch: 50, initial learning rate: 0.0005, dropout:0.6, batchsize: 32 |
| Amain |
distance measure: Euclidean distance, Cosine distance, Manhattan distance, Chebyshev distance, machine learning algorithm: random forest, depth: 64 |
