Prediction of Software Fault Detection and Correction Processes With Time Series Analysis
Yingchun Li, Ye Ma, Rui Peng, Kaiye Gao · 2020 Asia-Pacific International Symposium on Advanced Reliability and Maintenance Modeling (APARM) · 2020
Most software reliability models have focused on merely fault detection process, and ignored the time delay for correcting the detected faults. Some recent works considering both fault detection process and correction process are proposed, mainly based on the Non-homogeneous Poisson Process. However, the analytical models are usually developed based on some specific assumptions on the fault occurrence time distribution, time delay distribution, etc. Differently, this paper proposes the time series analysis model for predicting both the detected number of faults and corrected number of faults during software testing process. Real dataset is used to illustrate the approach.