Maintenance of software makes up a large fraction of the time and money spent in the software life cycle. By reducing the need for maintenance these costs can also be reduced. Predicting where maintenance is likely to occur can, help to reduce maintenance by prevention. This thesis details a study of the use of software quality;metrics to determine high complexity components in a software system. By the use of a history of maintenance done on a particular system, it is shown that a predictor equation can be developed to identify components which needed maintenance activities. This same equation can also be used to determine which components are likely to need maintenance in the future. Through the use of.these predictions and software metric complexities it should be possible to reduce the likelihood of a component needing maintenance. This might be accomplished by reducing the complexity of that component through further decomposition. / Master of Science
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/43067 |
| Date | 10 June 2012 |
| Creators | Wake, Steven A. |
| Contributors | Computer Science and Applications, Henry, Sallie M., Kafura, Dennis G., Hartson, H. Rex |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Language | English |
| Detected Language | English |
| Type | Thesis, Text |
| Format | vii, 49 leaves, BTD, application/pdf, application/pdf |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
| Relation | OCLC# 18567868, LD5655.V855_1988.W343.pdf |
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