Abstract
dc:description.abstractMaintenance 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.
Degree
thesis:*- Name thesis:degree_name
- Master of Science
- Level thesis:degree_level
- masters
- Discipline thesis:degree_discipline
- Computer Science and Applications
- Department dc:contributor.department
- Computer Science and Applications
- Grantor dc:publisher
- Virginia Tech
- Year dc:date.issued
- 1988
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Wake, Steven A.
- Chair dc:contributor.committeechair
-
- Henry, Sallie M.
- Committee members dc:contributor.committeemember
-
- Kafura, Dennis G.
- Hartson, H. Rex
Rights
dc:rights- Statement dc:rights
-
- In Copyright
- Licence dc:rights.uri
- Language dc:language.iso
- en
Identifiers
dc:identifier.*- Dc Identifier Other
- etd-06102012-040345
- OAI identifier oai:identifier
- oai:vtechworks.lib.vt.edu:10919/43067