Filling the gaps: Imputation of missing metrics’ values in a software quality model
Hierarchical software quality models usually rely on a number of metrics, which, once aggregated, provide an overview of selected perspectives of a system’s quality. Missing values of some metrics, that usually result from data unavailability, can seriously affect the final score. In the paper we em...
| Main Authors: | , , , |
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| Format: | Conference Paper |
| Published: |
2017
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| Online Access: | http://hdl.handle.net/20.500.11937/60161 |
| _version_ | 1848760582991249408 |
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| author | Kupinski, S. Walter, B. Wolski, Marcin Chojnacki, J. |
| author_facet | Kupinski, S. Walter, B. Wolski, Marcin Chojnacki, J. |
| author_sort | Kupinski, S. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Hierarchical software quality models usually rely on a number of metrics, which, once aggregated, provide an overview of selected perspectives of a system’s quality. Missing values of some metrics, that usually result from data unavailability, can seriously affect the final score. In the paper we empirically validate a few imputation methods in context of a custom Géant-QM framework, used for evaluation of several open source systems. Early results indicate imputing a missing value based on its close neighbors as data donors introduces less noise that using a wider set of donors. |
| first_indexed | 2025-11-14T10:18:05Z |
| format | Conference Paper |
| id | curtin-20.500.11937-60161 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T10:18:05Z |
| publishDate | 2017 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-601612018-08-16T00:28:27Z Filling the gaps: Imputation of missing metrics’ values in a software quality model Kupinski, S. Walter, B. Wolski, Marcin Chojnacki, J. Hierarchical software quality models usually rely on a number of metrics, which, once aggregated, provide an overview of selected perspectives of a system’s quality. Missing values of some metrics, that usually result from data unavailability, can seriously affect the final score. In the paper we empirically validate a few imputation methods in context of a custom Géant-QM framework, used for evaluation of several open source systems. Early results indicate imputing a missing value based on its close neighbors as data donors introduces less noise that using a wider set of donors. 2017 Conference Paper http://hdl.handle.net/20.500.11937/60161 10.1145/3143434.3143451 restricted |
| spellingShingle | Kupinski, S. Walter, B. Wolski, Marcin Chojnacki, J. Filling the gaps: Imputation of missing metrics’ values in a software quality model |
| title | Filling the gaps: Imputation of missing metrics’ values in a software quality model |
| title_full | Filling the gaps: Imputation of missing metrics’ values in a software quality model |
| title_fullStr | Filling the gaps: Imputation of missing metrics’ values in a software quality model |
| title_full_unstemmed | Filling the gaps: Imputation of missing metrics’ values in a software quality model |
| title_short | Filling the gaps: Imputation of missing metrics’ values in a software quality model |
| title_sort | filling the gaps: imputation of missing metrics’ values in a software quality model |
| url | http://hdl.handle.net/20.500.11937/60161 |