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Please use this identifier to cite or link to this item:
http://hdl.handle.net/10016/161
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| Title: | Bayesian inference for a software reliability model using metrics information. |
| Author(s): | Wiper, Michael P.
Rodríguez Bernal, M. T. |
| Issued date: | Mar-2001 |
| URI: | http://hdl.handle.net/10016/161 |
| Abstract: | In this paper, we are concerned with predicting the number of faults N and the time to next failure of a piece of software. Information in the form of software metrics data is used to estimate the prior distribution of N via a Poisson regression model. Given failure time data, and a well known model for software failures, we show how to sample the posterior distribution using Gibbs sampling, as implemented in the package "WinBugs". The approach is illustrated with a practical example. |
| Serie / Nº.: | UC3M Working Papers. Statistics and Econometrics
2001-14 |
| Appears in Collections: | DES - Working Papers. Statistics and Econometrics. WS
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