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DC Field | Value | Language |
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dc.contributor.author | Amir Ngah | - |
dc.date.accessioned | 2012-10-08T04:02:22Z | - |
dc.date.available | 2012-10-08T04:02:22Z | - |
dc.date.issued | 2012-05 | - |
dc.identifier.uri | http://hdl.handle.net/123456789/1980 | - |
dc.description.abstract | This thesis addresses the research in the area of regression testing. Software systems change and evolve over time. Each time a system is changed regression tests have to be run to validate these changes. An important issue in regression testing is how to minimise reuse the existing test cases of original program for modified program. One of the techniques to tackle this issue is called regression test selection technique. The aim of this research is to significantly reduce the number of test cases that need to be run after changes have been made. Specifically, this thesis focuses on developing a model for regression test selection using the decomposition slicing technique. | en_US |
dc.language.iso | en | en_US |
dc.publisher | United Kingdom : Durham University | en_US |
dc.subject | QA 278.2 .A4 2012 | en_US |
dc.subject | Amir Ngah | en_US |
dc.subject | Tesis Durham University 2012 | en_US |
dc.subject | Regression analysis | en_US |
dc.title | Regression test selection by exclusion | en_US |
dc.type | Thesis | en_US |
Appears in Collections: | Staff Thesis |
Files in This Item:
File | Description | Size | Format | |
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QA 278.2 .A4 2012 Abstractt.pdf | 288.17 kB | Adobe PDF | View/Open | |
QA 278.2 .A4 2012 FullText.pdf Restricted Access | 10.22 MB | Adobe PDF | View/Open Request a copy |
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