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dc.contributor.authorCito, Jurgen
dc.contributor.authorLeitner, Philipp
dc.contributor.authorRinard, Martin C
dc.contributor.authorGall, Harald C.
dc.date.accessioned2021-11-01T18:36:54Z
dc.date.available2021-11-01T18:36:54Z
dc.date.issued2019-08
dc.identifier.urihttps://hdl.handle.net/1721.1/137037
dc.description.abstract© 2019 IEEE. Because of differences between development and production environments, many software performance problems are detected only after software enters production. We present PerformanceHat, a new system that uses profiling information from production executions to develop a global performance model suitable for integration into interactive development environments. PerformanceHat's ability to incrementally update this global model as the software is changed in the development environment enables it to deliver near real-time predictions of performance consequences reflecting the impact on the production environment. We implement PerformanceHat as an Eclipse plugin and evaluate it in a controlled experiment with 20 professional software developers implementing several software maintenance tasks using our approach and a representative baseline (Kibana). Our results indicate that developers using PerformanceHat were significantly faster in (1) detecting the performance problem, and (2) finding the root-cause of the problem. These results provide encouraging evidence that our approach helps developers detect, prevent, and debug production performance problems during development before the problem manifests in production.en_US
dc.language.isoen
dc.publisherIEEEen_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/ICSE.2019.00102en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourceMIT web domainen_US
dc.titleInteractive Production Performance Feedback in the IDEen_US
dc.typeArticleen_US
dc.identifier.citationCito, Jurgen, Leitner, Philipp, Rinard, Martin C and Gall, Harald C. 2019. "Interactive Production Performance Feedback in the IDE." Proceedings - International Conference on Software Engineering, 2019-May.
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratoryen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.relation.journalProceedings - International Conference on Software Engineeringen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dc.date.updated2021-04-15T15:18:31Z
dspace.orderedauthorsCito, J; Leitner, P; Rinard, M; Gall, HCen_US
dspace.date.submission2021-04-15T15:18:32Z
mit.journal.volume2019-Mayen_US
mit.licenseOPEN_ACCESS_POLICY
mit.metadata.statusPublication Information Neededen_US


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