Software Defect Prediction via Attention-Based Recurrent Neural Network

Table 7

Tuned parameters for DP-ARNN.

Parameter	Description (value)
Embedding_dim	The dimensionality of embedding vectors (30)
Vector_length	The length of each AST vector (2000)
Bi-LSTM units	The number of the Bi-LSTM units per layer (40)
1st hidden layer nodes	The number of 1st hidden layer nodes (16)
2nd hidden layer nodes	The number of 2nd hidden layer nodes (24)
Batch_size	The number of training samples that propagated through DP-ARNN at a time (32)
Epoch	One forward/backward pass of all the training samples (20)
Monitor	The evaluation criteria on the validation set (val_acc)
Loss function	The loss function to minimize (binary_crossentropy)
Optimizer	The loss function solver (RMSprop)
Activation	Types of activation used in fully connected layers (tanh, linear, and sigmoid)