An Online Fault Detection Approachfor Web Applications
When the user interface of a web application reacts sluggish, or simple tasks suchas signing forms or saving data take unnecessary long time, the user experienceis diminished. Hence, one needs to monitor the working of this application,and undertake suitable action if such behavior is detected. This...
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ndltd-UPSALLA1-oai-DiVA.org-uu-3304592017-09-30T05:26:34ZAn Online Fault Detection Approachfor Web ApplicationsengÅholm, NiklasUppsala universitet, Institutionen för informationsteknologi2017Engineering and TechnologyTeknik och teknologierWhen the user interface of a web application reacts sluggish, or simple tasks suchas signing forms or saving data take unnecessary long time, the user experienceis diminished. Hence, one needs to monitor the working of this application,and undertake suitable action if such behavior is detected. This report exploreshow a method of Online Fault Detection (FADO) can be used to monitor thecondition of a web application. After reviewing the algorithm, results of thecase study are presented. The key insight is that the system is not so much interested in identifyingindividual request with an abnormally large response time, but in detectingsituations where such long response times are consistently present. That is,individual requests are aggregated into blocks which are evaluated together.We explore how to do this, and how this scheme interacts with the FADOalgorithm. The resulting system is compared to the existing system consistingof static thresholds, and it is indicated how the solution adapts to changingsituations. Finally this report presents some of the challenges and the di erentchoices one could make when deploying the FADO algorithm. Student thesisinfo:eu-repo/semantics/bachelorThesistexthttp://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-330459UPTEC IT, 1401-5749 ; 17017application/pdfinfo:eu-repo/semantics/openAccess |
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English |
format |
Others
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Engineering and Technology Teknik och teknologier |
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Engineering and Technology Teknik och teknologier Åholm, Niklas An Online Fault Detection Approachfor Web Applications |
description |
When the user interface of a web application reacts sluggish, or simple tasks suchas signing forms or saving data take unnecessary long time, the user experienceis diminished. Hence, one needs to monitor the working of this application,and undertake suitable action if such behavior is detected. This report exploreshow a method of Online Fault Detection (FADO) can be used to monitor thecondition of a web application. After reviewing the algorithm, results of thecase study are presented. The key insight is that the system is not so much interested in identifyingindividual request with an abnormally large response time, but in detectingsituations where such long response times are consistently present. That is,individual requests are aggregated into blocks which are evaluated together.We explore how to do this, and how this scheme interacts with the FADOalgorithm. The resulting system is compared to the existing system consistingof static thresholds, and it is indicated how the solution adapts to changingsituations. Finally this report presents some of the challenges and the di erentchoices one could make when deploying the FADO algorithm. |
author |
Åholm, Niklas |
author_facet |
Åholm, Niklas |
author_sort |
Åholm, Niklas |
title |
An Online Fault Detection Approachfor Web Applications |
title_short |
An Online Fault Detection Approachfor Web Applications |
title_full |
An Online Fault Detection Approachfor Web Applications |
title_fullStr |
An Online Fault Detection Approachfor Web Applications |
title_full_unstemmed |
An Online Fault Detection Approachfor Web Applications |
title_sort |
online fault detection approachfor web applications |
publisher |
Uppsala universitet, Institutionen för informationsteknologi |
publishDate |
2017 |
url |
http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-330459 |
work_keys_str_mv |
AT aholmniklas anonlinefaultdetectionapproachforwebapplications AT aholmniklas onlinefaultdetectionapproachforwebapplications |
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1718541411659284480 |