dc.contributor.author |
Ghaith, Shadi |
|
dc.date.accessioned |
2013-11-28T16:18:31Z |
|
dc.date.available |
2013-11-28T16:18:31Z |
|
dc.date.issued |
2013 |
|
dc.identifier.uri |
http://hdl.handle.net/10344/3484 |
|
dc.description |
peer-reviewed |
en_US |
dc.description.abstract |
Performance regression testing is an important step in the
software development lifecycle, especially for enterprise applications. Commonly the analysis of performance regression testing to find anomalies is carried out manually and
therefore can be error-prone, time consuming and sensitive to the input load. In our research, we propose a new
technique that overcomes the above problems which helps
the performance testing teams to improve their process and
speeds up the entire software production process. |
en_US |
dc.language.iso |
eng |
en_US |
dc.publisher |
Association for Computing Machinery |
en_US |
dc.relation.ispartofseries |
ISSTA 2013 Proceedings of the 2013 International Symposium on Software Testing and Analysis;pp.370-373 |
|
dc.relation.uri |
http://dx.doi.org/10.1145/2483760.2492399 |
|
dc.rights |
"© ACM,2013. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in ISSTA 2013 Proceedings of the 2013 International Symposium on Software Testing and Analysis pp. 370-373 http://dx.doi.org/10.1145/2483760.2492399 |
en_US |
dc.subject |
application change |
en_US |
dc.subject |
performance models |
en_US |
dc.subject |
regression testing |
en_US |
dc.title |
Analysis of performance regression testing data by transaction profiles |
en_US |
dc.type |
info:eu-repo/semantics/conferenceObject |
en_US |
dc.type.supercollection |
all_ul_research |
en_US |
dc.type.supercollection |
ul_published_reviewed |
en_US |
dc.contributor.sponsor |
SFI |
en_US |
dc.relation.projectid |
10/CE/I1855 |
en_US |
dc.rights.accessrights |
info:eu-repo/semantics/openAccess |
en_US |