Toolkit for Automatic Collection and Predictive Modelling of Software Metrics
| dc.contributor.advisor | Down, Douglas G. | |
| dc.contributor.author | Johnston, Tim | |
| dc.contributor.department | Computing and Software | en_US |
| dc.date.accessioned | 2016-06-30T16:05:58Z | |
| dc.date.available | 2016-06-30T16:05:58Z | |
| dc.date.issued | 2016 | |
| dc.description.abstract | For empirical software researchers, the management of experimental data and results is time-intensive and a significant source of error. As a result, research in this area is often difficult to reproduce, falsify and generalize. Software projects deemed feasible for study are typically of a limiting size and belong to particular domains for which measurement tools are available. We propose a toolkit for data gathering and exploratory modelling in empirical software research. Requirements are derived from issues commonly affecting studies of defect prediction and software evolution. We develop the toolkit by using a prototype-driven approach. The prototype toolkit is used to carry out a case study illustrating its effectiveness and potential for future extension. | en_US |
| dc.description.degree | Master of Applied Science (MASc) | en_US |
| dc.description.degreetype | Thesis | en_US |
| dc.identifier.uri | http://hdl.handle.net/11375/19705 | |
| dc.language.iso | en | en_US |
| dc.title | Toolkit for Automatic Collection and Predictive Modelling of Software Metrics | en_US |
| dc.type | Thesis | en_US |
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