@inproceedings{87c5c7275715426eb7ed3ffdbd2e670c,
title = "Embedded Software Fault Prediction Based on Back Propagation Neural Network",
abstract = "Predicting software faults before software testing activities can help rational distribution of time and resources. Software metrics are used for software fault prediction due to their close relationship with software faults. Thanks to the non-linear fitting ability, Neural networks are increasingly used in the prediction model. We first filter metric set of the embedded software by statistical methods to reduce the dimensions of model input. Then we build a back propagation neural network with simple structure but good performance and apply it to two practical embedded software projects. The verification results show that the model has good ability to predict software faults.",
keywords = "Back propagation neural network, Embedded software, Fault prediction, Software metrics",
author = "Pengyang Zong and Yichen Wang and Feng Xie",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 18th IEEE International Conference on Software Quality, Reliability, and Security Companion, QRS-C 2018 ; Conference date: 16-07-2018 Through 20-07-2018",
year = "2018",
month = aug,
day = "9",
doi = "10.1109/QRS-C.2018.00098",
language = "英语",
isbn = "9781538678398",
series = "Proceedings - 2018 IEEE 18th International Conference on Software Quality, Reliability, and Security Companion, QRS-C 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "553--558",
booktitle = "Proceedings - 2018 IEEE 18th International Conference on Software Quality, Reliability, and Security Companion, QRS-C 2018",
address = "美国",
}