research-article

QN-based Modeling and Analysis of Software Performance Antipatterns for Cyber-Physical Systems

Authors:

Riccardo Pinciroli,

Connie U. Smith,

Catia TrubianiAuthors Info & Claims

ICPE '21: Proceedings of the ACM/SPEC International Conference on Performance Engineering

Pages 93 - 104

https://doi.org/10.1145/3427921.3450251

Published: 09 April 2021 Publication History

Abstract

Identifying performance problems in modern software systems is nontrivial, even more so when looking at specific application domains, such as cyber-physical systems. The heterogeneity of software and hardware components makes the process of performance evaluation more challenging, and traditional software performance engineering techniques may fail while dealing with interacting and heterogeneous components. The goal of this paper is to introduce a model-based approach to understand software performance problems in cyber-physical systems. In our previous work, we listed some common bad practices, namely software performance antipatterns, that may occur. Here we are interested in shedding light on these antipatterns by means of performance models, i.e., queuing network models, that provide evidence of how antipatterns may affect the overall system performance. Starting from the specification of three software performance antipatterns tailored for cyber-physical systems, we provide the queuing network models capturing the corresponding bad practices. The analysis of these models demonstrates their usefulness in recognizing performance problems early in the software development process. This way, performance engineers are supported in the task of detecting and fixing the performance criticalities.

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Cited By

Pinciroli RSmith CTrubiani C(2023)Modeling more software performance antipatterns in cyber-physical systemsSoftware and Systems Modeling10.1007/s10270-023-01137-x23:4(1003-1023)Online publication date: 20-Dec-2023
https://doi.org/10.1007/s10270-023-01137-x
Avritzer ABritto RTrubiani CCamilli MJanes ARusso Bvan Hoorn AHeinrich RRapp MHenß JChalawadi R(2022)Scalability testing automation using multivariate characterization and detection of software performance antipatternsJournal of Systems and Software10.1016/j.jss.2022.111446193:COnline publication date: 1-Nov-2022
https://dl.acm.org/doi/10.1016/j.jss.2022.111446
Murgia MPinciroli RTrubiani CTuosto E(2022)On Model-Based Performance Analysis of Collective Adaptive SystemsLeveraging Applications of Formal Methods, Verification and Validation. Adaptation and Learning10.1007/978-3-031-19759-8_17(266-282)Online publication date: 22-Oct-2022
https://dl.acm.org/doi/10.1007/978-3-031-19759-8_17
Show More Cited By

Index Terms

QN-based Modeling and Analysis of Software Performance Antipatterns for Cyber-Physical Systems
1. Computer systems organization
  1. Embedded and cyber-physical systems
2. General and reference
  1. Cross-computing tools and techniques
    1. Metrics
    2. Performance

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cover image ACM Conferences

ICPE '21: Proceedings of the ACM/SPEC International Conference on Performance Engineering

April 2021

301 pages

ISBN:9781450381949

DOI:10.1145/3427921

General Chairs:
Johann Bourcier
University of Rennes 1, France
,
Zhen Ming (Jack) Jiang
York University, Canada
,
Program Chairs:
Cor-Paul Bezemer
University of Alberta, Canada
,
Vittorio Cortellessa
University of L'Aquila, Italy

Copyright © 2021 ACM.

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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Published: 09 April 2021

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ICPE '21: ACM/SPEC International Conference on Performance Engineering

April 19 - 23, 2021

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ICPE '21 Paper Acceptance Rate 16 of 61 submissions, 26%;

Overall Acceptance Rate 252 of 851 submissions, 30%

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Cited By

Pinciroli RSmith CTrubiani C(2023)Modeling more software performance antipatterns in cyber-physical systemsSoftware and Systems Modeling10.1007/s10270-023-01137-x23:4(1003-1023)Online publication date: 20-Dec-2023
https://doi.org/10.1007/s10270-023-01137-x
Avritzer ABritto RTrubiani CCamilli MJanes ARusso Bvan Hoorn AHeinrich RRapp MHenß JChalawadi R(2022)Scalability testing automation using multivariate characterization and detection of software performance antipatternsJournal of Systems and Software10.1016/j.jss.2022.111446193:COnline publication date: 1-Nov-2022
https://dl.acm.org/doi/10.1016/j.jss.2022.111446
Murgia MPinciroli RTrubiani CTuosto E(2022)On Model-Based Performance Analysis of Collective Adaptive SystemsLeveraging Applications of Formal Methods, Verification and Validation. Adaptation and Learning10.1007/978-3-031-19759-8_17(266-282)Online publication date: 22-Oct-2022
https://dl.acm.org/doi/10.1007/978-3-031-19759-8_17
van Dinten IDerakhshanfar PPanichella AZaidman A(undefined)The Slow and the Furious? Performance Antipattern Detection in Cyber-Physical SystemsSSRN Electronic Journal10.2139/ssrn.4185426
https://doi.org/10.2139/ssrn.4185426

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