An Imperfect Debugging Littlewood Non-homogeneous Poisson Process Model | ||||
| The Egyptian Statistical Journal | ||||
| Article 2, Volume 50, Issue 2, December 2006, Page 136-153 PDF (15.89 MB) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/esju.2006.313547 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
| Abdalla Abdel-Ghaly* ; May Barghout* | ||||
| Statistics Department, Faculty of Economics & Political Science, Cairo University | ||||
| Abstract | ||||
| The large literature on software reliability assessment and prediction essentially assumes that once a failure occurs the fault causing the failure is immediately removed with certainty. i.e., perfect debugging. This assumption may not be realistic. Due to the complexity of the software systems the testing team may not be able to remove the errors perfectly and the original error is He replaced by another error(s), i.e., imperfect debugging. The motivation for the present work is to relax this assumption. We present a new non-homogeneous Poisson Process (NHPP) model for reliability prediction, which is based upon the Littlewood Non-Homogeneous Poisson Process (LNHPP) model and incorporates imperfect debugging. Its predictive accuracy is compared on some real data sets with the predictions that come from the conventional LNHPP model. These initial results are encouraging. | ||||
| Keywords | ||||
| Software Reliability; Imperfect Debugging; Non; Homogeneous Poisson Process | ||||
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