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Monitoring probabilistic properties

Published: 24 August 2009 Publication History

Abstract

Monitoring allows for checking if a system fulfils its requirements at runtime. This is required for quality assurance purposes. Currently several approaches exist to monitor standard and timing properties. However, a current challenge is to provide a comprehensive approach for monitoring probabilistic properties, as they are used to formulate performance, reliability, safety, and availability requirements. The main problem of these probabilistic properties is that there is no binary acceptance condition. To overcome this problem, this paper describes a monitoring approach called ProMo that is based on acceptance sampling and sequential hypothesis testing. This approach is validated based on several experiments that have been performed on an example system which provides medical assistance in remote areas.

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cover image ACM Conferences
ESEC/FSE '09: Proceedings of the 7th joint meeting of the European software engineering conference and the ACM SIGSOFT symposium on The foundations of software engineering
August 2009
408 pages
ISBN:9781605580012
DOI:10.1145/1595696
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 24 August 2009

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Author Tags

  1. performance
  2. probabilistic properties
  3. reliability
  4. runtime monitoring
  5. safety
  6. security
  7. web services

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ESEC/FSE09
Sponsor:
ESEC/FSE09: Joint 12th European Software Engineering Conference
August 24 - 28, 2009
Amsterdam, The Netherlands

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ESEC/FSE '09 Paper Acceptance Rate 32 of 217 submissions, 15%;
Overall Acceptance Rate 112 of 543 submissions, 21%

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  • (2022)M-BSRM: Multivariate BayeSian Runtime QoS Monitoring Using Point Mutual InformationIEEE Transactions on Services Computing10.1109/TSC.2019.295260415:1(484-497)Online publication date: 1-Jan-2022
  • (2022)Deep Learning for Autonomous Vehicle Control: Algorithms, State-of-the-Art, and Future ProspectsundefinedOnline publication date: 9-Feb-2022
  • (2021)Mobility and Dependence-Aware QoS Monitoring in Mobile Edge ComputingIEEE Transactions on Cloud Computing10.1109/TCC.2021.30630509:3(1143-1157)Online publication date: 1-Jul-2021
  • (2020)Compositional Probabilistic Analysis of Temporal Properties Over Stochastic DetectorsIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2020.301264339:11(3288-3299)Online publication date: Nov-2020
  • (2020)A Social Sensing Approach for Quality Changes of Real-World Services2020 IEEE International Conference on Service Oriented Systems Engineering (SOSE)10.1109/SOSE49046.2020.00017(82-91)Online publication date: Aug-2020
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