Towards an Improvement of Bug Severity Classification
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F14%3A00076796" target="_blank" >RIV/00216224:14330/14:00076796 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1109/SEAA.2014.51" target="_blank" >http://dx.doi.org/10.1109/SEAA.2014.51</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/SEAA.2014.51" target="_blank" >10.1109/SEAA.2014.51</a>
Alternative languages
Result language
angličtina
Original language name
Towards an Improvement of Bug Severity Classification
Original language description
Predicting the severity of bugs has been found in past research to improve triaging and the bug resolution process. For this reason, many classification/prediction approaches emerged over the years to provide an automated reasoning over severity classes.In this paper, we use text mining together with bi-grams and feature selection to improve the classification of bugs in severe/non-severe classes. We adopt the Naive Bayes (NB) classifier considering Mozilla and Eclipse datasets commonly used in relatedworks. Overall, the results show that the application of bi-grams can improve slightly the performance of the classifier, but feature selection can be more effective to determine the most informative terms and bi-grams. The results are in any case project-dependent, as in some cases the addition of bi-grams may worsen the performance.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
<a href="/en/project/LG13010" target="_blank" >LG13010: Czech Republic representation in the European Research Consortium for Informatics and Mathematics (ERCIM)</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2014
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
40th Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2014
ISBN
9781479957941
ISSN
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e-ISSN
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Number of pages
8
Pages from-to
269-276
Publisher name
IEEE
Place of publication
Verona
Event location
Verona
Event date
Jan 1, 2014
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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