Automated Experiments for Deriving Performance-relevant Properties of Software Execution Environments

The software execution environment can play a crucial role when analyzing the performance of a software system. In this book, a novel approach for the automated detection of performance-relevant properties of the execution environment is presented. The properties are detected using predefined experi...

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Hovedforfatter: Hauck, Michael
Format: Online
Sprog:engelsk
Udgivet: KIT Scientific Publishing 2021
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Online adgang:34608
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author Hauck, Michael
author_browse Hauck, Michael
author_facet Hauck, Michael
author_sort Hauck, Michael
collection Directory of Open Access Books
description The software execution environment can play a crucial role when analyzing the performance of a software system. In this book, a novel approach for the automated detection of performance-relevant properties of the execution environment is presented. The properties are detected using predefined experiments and integrated into performance prediction tools. The approach is applied to experiments for detecting different CPU, OS, and virtualization properties, and validated in different case studies.
format Online
id doab-20.500.12854ir-41638
institution Directory of Open Access Books
language eng
publishDate 2021
publishDateRange 2021
publishDateSort 2021
publisher KIT Scientific Publishing
publisherStr KIT Scientific Publishing
record_format ojs
spelling doab-20.500.12854ir-416382023-12-20T18:40:46Z Automated Experiments for Deriving Performance-relevant Properties of Software Execution Environments Hauck, Michael QA75.5-76.95 Execution Environment Measurements Experiments Metamodel Software Performance Prediction bic Book Industry Communication::U Computing & information technology::UY Computer science The software execution environment can play a crucial role when analyzing the performance of a software system. In this book, a novel approach for the automated detection of performance-relevant properties of the execution environment is presented. The properties are detected using predefined experiments and integrated into performance prediction tools. The approach is applied to experiments for detecting different CPU, OS, and virtualization properties, and validated in different case studies. 2021-02-11T08:43:48Z 2021-02-11T08:43:48Z 2019-07-30 20:01:58 2014 book 34608 18670067 9783731501381 https://directory.doabooks.org/handle/20.500.12854/41638 eng The Karlsruhe Series on Software Design and Quality / Ed. by Prof. Dr. Ralf Reussner image/jpeg Attribution-ShareAlike 4.0 International https://www.ksp.kit.edu/9783731501381 KIT Scientific Publishing 10.5445/KSP/1000037233 10.5445/KSP/1000037233 68fffc18-8f7b-44fa-ac7e-0b7d7d979bd2 9783731501381 XVI, 315 p. open access
spellingShingle QA75.5-76.95
Execution Environment
Measurements
Experiments
Metamodel
Software Performance Prediction
bic Book Industry Communication::U Computing & information technology::UY Computer science
Hauck, Michael
Automated Experiments for Deriving Performance-relevant Properties of Software Execution Environments
title Automated Experiments for Deriving Performance-relevant Properties of Software Execution Environments
title_full Automated Experiments for Deriving Performance-relevant Properties of Software Execution Environments
title_fullStr Automated Experiments for Deriving Performance-relevant Properties of Software Execution Environments
title_full_unstemmed Automated Experiments for Deriving Performance-relevant Properties of Software Execution Environments
title_short Automated Experiments for Deriving Performance-relevant Properties of Software Execution Environments
title_sort automated experiments for deriving performance relevant properties of software execution environments
topic QA75.5-76.95
Execution Environment
Measurements
Experiments
Metamodel
Software Performance Prediction
bic Book Industry Communication::U Computing & information technology::UY Computer science
topic_facet QA75.5-76.95
Execution Environment
Measurements
Experiments
Metamodel
Software Performance Prediction
bic Book Industry Communication::U Computing & information technology::UY Computer science
url 34608
work_keys_str_mv AT hauckmichael automatedexperimentsforderivingperformancerelevantpropertiesofsoftwareexecutionenvironments