Impact of Parameter Tuning for Optimizing Deep Neural Network Models for Predicting Software Faults
Deep neural network models built by the appropriate design decisions are crucial to obtain the desired classifier performance. This is especially desired when predicting fault proneness of software modules. When correctly identified, this could help in reducing the testing cost by directing the effo...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Hindawi Limited
2021-01-01
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| Series: | Scientific Programming |
| Online Access: | http://dx.doi.org/10.1155/2021/6662932 |