Software Failure Prediction based on Thermal Images

Software failure prediction is one of the most critical issues in software reliability research. And there are several crucial challenges for software failure prediction, which includes complex data, intrusive monitoring that brings potential risk to the system and monitoring costs. We proposed the...

Full description

Saved in:
Bibliographic Details
Published in2022 9th International Conference on Dependable Systems and Their Applications (DSA) pp. 302 - 309
Main Authors Gong, Yiang, Lu, Minyan, Kong, Shiyi, Yan, Liang
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.08.2022
Subjects
Costs
Data models
Data processing
Delay effects
Hardware
Software
software failure prediction
Software reliability
thermal images
Online AccessGet full text

Cover

More Information
Summary:Software failure prediction is one of the most critical issues in software reliability research. And there are several crucial challenges for software failure prediction, which includes complex data, intrusive monitoring that brings potential risk to the system and monitoring costs. We proposed the FPbTI approach to predict software failure by using thermal images taken from outside of the hardware. In this approach, a data processing method is proposed and a convolutional neural network model is constructed. Additionally, corresponding experimental system was designed to verify the effectiveness of the approach. We experimentally demonstrate that our proposed approach achieves the goal of software failure prediction and shows remarkable performance.
ISSN:2767-6684
DOI:10.1109/DSA56465.2022.00048