Mastering Uncertainty in Performance Estimations of Configurable Software Systems

Understanding the influence of configuration options on performance is key for finding optimal system configurations, system understanding, and performance debugging. In prior research, a number of performance-influence modeling approaches have been proposed, which model a configuration option'...

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Bibliographic Details

Published in:	2020 35th IEEE/ACM International Conference on Automated Software Engineering (ASE) pp. 684 - 696
Main Authors:	Dorn, Johannes, Apel, Sven, Siegmund, Norbert
Format:	Conference Proceeding
Language:	English
Published:	ACM 01.09.2020
Subjects:	Computing methodologies → Uncertainty quantification Configurable Software Systems Performance-Influence Modeling Predictive models Probabilistic logic Probabilistic Programming Programming Software and its engineering → Software performance Software engineering Software reliability Software systems Uncertainty
ISSN:	2643-1572
Online Access:	Get full text
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