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Exploring synergies between bottleneck analysis and performance antipatterns

Authors:

Catia Trubiani,

Antinisca Di Marco,

Vittorio Cortellessa,

Dorina PetriuAuthors Info & Claims

ICPE '14: Proceedings of the 5th ACM/SPEC international conference on Performance engineering

Pages 75 - 86

https://doi.org/10.1145/2568088.2568092

Published: 22 March 2014 Publication History

Abstract

The problem of interpreting the results of performance analysis is quite critical, mostly because the analysis results (i.e. mean values, variances, and probability distributions) are hard to transform into feedback for software engineers that allows to remove performance problems. Approaches aimed at identifying and removing the causes of poor performance in software systems commonly fall in two categories: (i) bottleneck analysis, aimed at identifying overloaded software components and/or hardware resources that affect the whole system performance, and (ii) performance antipatterns, aimed at detecting and removing common design mistakes that notably induce performance degradation.

In this paper, we look for possible synergies between these two categories of approaches in order to empower the performance investigation capabilities. In particular, we aim at showing that the approach combination allows to provide software engineers with broader sets of alternative solutions leading to better performance results. We have explored this research direction in the context of Layered Queueing Network models, and we have considered a case study in the e-commerce domain. After comparing the results achievable with each approach separately, we quantitatively show the benefits of merging bottleneck analysis and performance antipatterns.

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Cited By

Avritzer ACusick JJanes ACamilli MRusso BTrubiani Cvan Hoorn A(2024)Dependability Modeling in an Industrial Environment2024 IEEE 35th International Symposium on Software Reliability Engineering Workshops (ISSREW)10.1109/ISSREW63542.2024.00045(43-48)Online publication date: 28-Oct-2024
https://doi.org/10.1109/ISSREW63542.2024.00045
Incerto ETrubiani C(2024)Flocks of Birds: A Quantitative EvaluationLeveraging Applications of Formal Methods, Verification and Validation. REoCAS Colloquium in Honor of Rocco De Nicola10.1007/978-3-031-73709-1_17(271-286)Online publication date: 9-Oct-2024
https://doi.org/10.1007/978-3-031-73709-1_17
Dave SNowatzki TShrivastava AAamodt TSwift MJerger N(2023)Explainable-DSE: An Agile and Explainable Exploration of Efficient HW/SW Codesigns of Deep Learning Accelerators Using Bottleneck AnalysisProceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 410.1145/3623278.3624772(87-107)Online publication date: 25-Mar-2023
https://dl.acm.org/doi/10.1145/3623278.3624772
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Index Terms

Exploring synergies between bottleneck analysis and performance antipatterns

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Information

Published In

cover image ACM Conferences

ICPE '14: Proceedings of the 5th ACM/SPEC international conference on Performance engineering

March 2014

310 pages

ISBN:9781450327336

DOI:10.1145/2568088

General Chairs:
Klaus-Dieter Lange
Hewlett-Packard Company, USA
,
John Murphy
University College Dublin, Ireland
,
Program Chairs:
Walter Binder
University of Lugano, Switzerland
,
José Merseguer
Universidad de Zaragoza, Spain

Copyright © 2014 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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SIGMETRICS: ACM Special Interest Group on Measurement and Evaluation
SIGSOFT: ACM Special Interest Group on Software Engineering
SPEC: SPEC Research Group

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 22 March 2014

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ICPE'14

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ICPE'14: ACM/SPEC International Conference on Performance Engineering

March 22 - 26, 2014

Dublin, Ireland

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ICPE '14 Paper Acceptance Rate 21 of 78 submissions, 27%;

Overall Acceptance Rate 252 of 851 submissions, 30%

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Cited By

Avritzer ACusick JJanes ACamilli MRusso BTrubiani Cvan Hoorn A(2024)Dependability Modeling in an Industrial Environment2024 IEEE 35th International Symposium on Software Reliability Engineering Workshops (ISSREW)10.1109/ISSREW63542.2024.00045(43-48)Online publication date: 28-Oct-2024
https://doi.org/10.1109/ISSREW63542.2024.00045
Incerto ETrubiani C(2024)Flocks of Birds: A Quantitative EvaluationLeveraging Applications of Formal Methods, Verification and Validation. REoCAS Colloquium in Honor of Rocco De Nicola10.1007/978-3-031-73709-1_17(271-286)Online publication date: 9-Oct-2024
https://doi.org/10.1007/978-3-031-73709-1_17
Dave SNowatzki TShrivastava AAamodt TSwift MJerger N(2023)Explainable-DSE: An Agile and Explainable Exploration of Efficient HW/SW Codesigns of Deep Learning Accelerators Using Bottleneck AnalysisProceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 410.1145/3623278.3624772(87-107)Online publication date: 25-Mar-2023
https://dl.acm.org/doi/10.1145/3623278.3624772
Avritzer ACamilli MJanes ARusso BTrubiani Cvan Hoorn A(2023)Continuous Dependability Assessment of Microservice SystemsSoftware Architecture. ECSA 2022 Tracks and Workshops10.1007/978-3-031-36889-9_11(138-147)Online publication date: 16-Jul-2023
https://doi.org/10.1007/978-3-031-36889-9_11
Arcelli D(2021)Envisioning Model-Based Performance Engineering FrameworksProcedia Computer Science10.1016/j.procs.2021.04.008184(541-548)Online publication date: 2021
https://doi.org/10.1016/j.procs.2021.04.008
Petriu D(2021)Integrating the analysis of multiple non-functional properties in model-driven engineeringSoftware and Systems Modeling10.1007/s10270-021-00953-320:6(1777-1791)Online publication date: 28-Nov-2021
https://doi.org/10.1007/s10270-021-00953-3
Trubiani CAleti AGoodwin SJamshidi Pvan Hoorn AGratzl S(2020)VisArch: Visualisation of Performance-based Architectural RefactoringsSoftware Architecture10.1007/978-3-030-58923-3_12(182-190)Online publication date: 8-Sep-2020
https://doi.org/10.1007/978-3-030-58923-3_12
He SManns GSaunders JWang WPollock LSoffa MDumas MPfahl DApel SRusso A(2019)A statistics-based performance testing methodology for cloud applicationsProceedings of the 2019 27th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering10.1145/3338906.3338912(188-199)Online publication date: 12-Aug-2019
https://dl.acm.org/doi/10.1145/3338906.3338912
Iqbal JUl Haq S(2017)Automatic Feedback Generation in Software Performance Engineering: A ReviewOriental journal of computer science and technology10.13005/ojcst/10.02.0810:2(305-310)Online publication date: 6-Apr-2017
https://doi.org/10.13005/ojcst/10.02.08
Dubois DTrubiani CCasale G(2016)Model-Driven Application Refactoring to Minimize Deployment Costs in Preemptible Cloud Resources2016 IEEE 9th International Conference on Cloud Computing (CLOUD)10.1109/CLOUD.2016.0052(335-342)Online publication date: Jun-2016
https://doi.org/10.1109/CLOUD.2016.0052
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