DocumentCode :
3722603
Title :
Small Sample Fault Data Prediction Study Based on Weibull Model
Author :
Hongpo Wang;Ge Yang;Linnan Bai; Juanyin;Qiang Li
Author_Institution :
Software Complexity Res. Center, Beijing, China
fYear :
2015
Firstpage :
9
Lastpage :
14
Abstract :
Using software testing data collected, this paper established a software safety defects S curve model based on Weibull model theory. χ2 testing and prediction error testing are employed to verify the matching ability of the Weibull model and applicability of the predicting result. How to select truncation error is also discussed here. Results show that better predictive effect can be achieved if computational formula of truncation error is properly adjusted. The application of predicting model was also developed in this paper. Small sample fault data prediction and predicting error problems are discussed here. If the amount of fault data accumulated is not big enough, prediction cannot carry out. Analyzing results point out that it can be solved through the combination of different types of data. Then variation tendency of small sample fault data can be predicted.
Keywords :
"Software","Data models","Testing","Mathematical model","Predictive models","Hazards"
Publisher :
ieee
Conference_Titel :
Computer Science and Mechanical Automation (CSMA), 2015 International Conference on
Type :
conf
DOI :
10.1109/CSMA.2015.9
Filename :
7371613
Link To Document :
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