Fault Identification and Reliability Assessment Tool Based on Deep Learning for Fault Big Data

Yoshinobu Tamura, Shigeru Yamada
2017 Software Networking  
Recently, many open source software (OSS) are developed under several OSS projects. Then, the software faults detected in OSS projects are managed by the bug tracking systems. Also, many data sets are recorded on the bug tracking systems by many users and project members. In this paper, we propose the useful method based on the deep learning for the improvement activities of OSS reliability. Moreover, we apply the existing software reliability model to the fault data recorded on the bug
more » ... system. In particular, we develop an application software for visualization and reliability assessment of fault data recorded on OSS. Furthermore, several numerical illustrations of the developed application software in the actual OSS project are shown in this paper. Then, we discuss the analysis results based on the developed application software by using the fault data sets of actual OSS projects.
doi:10.13052/jsn2445-9739.2017.008 fatcat:q4zmefg7lnfajg2e5bxfffynaa