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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Hribar, L. |
| Copyright Year | 2008 |
| Description | Author affiliation: Ericsson Nikola Tesla, Split (Hribar, L.) |
| Abstract | There are several families for software quality prediction techniques in development projects. All of them can be classified in several subfamilies. Each of these techniques has its own distinctive feature and it may not give correct prediction of quality for a scenario different from the one for which the technique was designed. All these techniques for software quality prediction are dispersed. One of them is statistical and probabilistic technique. The paper deals with software quality prediction techniques in development projects. Four different models based on statistical and probabilistic approach is presented and evaluated for prediction of software faults in very large development projects. |
| Starting Page | 157 |
| Ending Page | 162 |
| File Size | 371336 |
| Page Count | 6 |
| File Format | |
| ISBN | 9789536114979 |
| DOI | 10.1109/SOFTCOM.2008.4669471 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2008-09-25 |
| Publisher Place | Croatia |
| Access Restriction | Subscribed |
| Rights Holder | University of Split, FESB |
| Subject Keyword | Software maintenance Costs Software quality Software performance Predictive models Weibull distribution Artificial intelligence Information technology Aerospace industry Automotive engineering |
| Content Type | Text |
| Resource Type | Article |
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