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Automatically Detecting "Excessive Dynamic Memory Allocations" Software Performance Anti-Pattern

Authors:

Manjula Peiris,

James H. HillAuthors Info & Claims

ICPE '16: Proceedings of the 7th ACM/SPEC on International Conference on Performance Engineering

Pages 237 - 248

https://doi.org/10.1145/2851553.2851563

Published: 12 March 2016 Publication History

Abstract

This paper presents a methodology for automatically detecting the excessive dynamic memory allocation software performance anti-pattern, which is implemented in a tool named Excessive Memory Allocation Detector (EMAD). To the best of author's knowledge, EMAD is the first attempt to detect excessive dynamic memory allocation anti-pattern without human intervention. EMAD uses dynamic binary instrumentation and exploratory data analysis to determine if an application (or middleware) exhibits excessive dynamic memory allocations. Unlike traditional approaches, EMAD's technique does not rely on source code analysis. Results of applying EMAD to several open-source projects show that EMAD can detect the excessive dynamic memory allocations anti-pattern correctly. The results also show that application performance improves when the detected excessive dynamic memory allocations are resolved.

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Cited By

Mohammed MAlshayeb MHassine J(2024)A rule-based approach for the identification of quality improvement opportunities in GRL modelsSoftware Quality Journal10.1007/s11219-024-09679-z32:3(1007-1037)Online publication date: 6-Jun-2024
https://doi.org/10.1007/s11219-024-09679-z
Weninger MGander EMössenböck H(2021)Guided ExplorationProceedings of the ACM on Human-Computer Interaction10.1145/34617315:EICS(1-34)Online publication date: 29-May-2021
https://dl.acm.org/doi/10.1145/3461731
Lui Nal Hasan MHill J(2021)Real-time Detection of the More is Less Performance Anti-Pattern in MySQL Databases2021 IEEE 24th International Symposium on Real-Time Distributed Computing (ISORC)10.1109/ISORC52013.2021.00020(71-78)Online publication date: Jun-2021
https://doi.org/10.1109/ISORC52013.2021.00020
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Index Terms

Automatically Detecting "Excessive Dynamic Memory Allocations" Software Performance Anti-Pattern
1. Software and its engineering
  1. Software organization and properties
    1. Contextual software domains
      1. Operating systems
        Memory management
        Allocation / deallocation strategies
    2. Extra-functional properties
      1. Software performance

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Published In

cover image ACM Conferences

ICPE '16: Proceedings of the 7th ACM/SPEC on International Conference on Performance Engineering

March 2016

346 pages

ISBN:9781450340809

DOI:10.1145/2851553

General Chairs:
Alberto Avritzer
Sonatype, Inc., USA
,
Alexandru Iosup
Delft University of Technology, the Netherlands
,
Program Chairs:
Xiaoyun Zhu
Futurewei Technologies, USA
,
Steffen Becker
Chemnitz University of Technology, Germany

Copyright © 2016 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: 12 March 2016

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ICPE'16: ACM/SPEC International Conference on Performance Engineering

March 12 - 16, 2016

Delft, The Netherlands

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ICPE '16 Paper Acceptance Rate 23 of 74 submissions, 31%;

Overall Acceptance Rate 252 of 851 submissions, 30%

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Cited By

Mohammed MAlshayeb MHassine J(2024)A rule-based approach for the identification of quality improvement opportunities in GRL modelsSoftware Quality Journal10.1007/s11219-024-09679-z32:3(1007-1037)Online publication date: 6-Jun-2024
https://doi.org/10.1007/s11219-024-09679-z
Weninger MGander EMössenböck H(2021)Guided ExplorationProceedings of the ACM on Human-Computer Interaction10.1145/34617315:EICS(1-34)Online publication date: 29-May-2021
https://dl.acm.org/doi/10.1145/3461731
Lui Nal Hasan MHill J(2021)Real-time Detection of the More is Less Performance Anti-Pattern in MySQL Databases2021 IEEE 24th International Symposium on Real-Time Distributed Computing (ISORC)10.1109/ISORC52013.2021.00020(71-78)Online publication date: Jun-2021
https://doi.org/10.1109/ISORC52013.2021.00020
Weninger MMakor LMossenbock H(2020)Memory Cities: Visualizing Heap Memory Evolution Using the Software City Metaphor2020 Working Conference on Software Visualization (VISSOFT)10.1109/VISSOFT51673.2020.00017(110-121)Online publication date: Sep-2020
https://doi.org/10.1109/VISSOFT51673.2020.00017
Weninger MGander EMössenböck HHosking AFinocchi I(2019)Detection of suspicious time windows in memory monitoringProceedings of the 16th ACM SIGPLAN International Conference on Managed Programming Languages and Runtimes10.1145/3357390.3361025(95-104)Online publication date: 21-Oct-2019
https://dl.acm.org/doi/10.1145/3357390.3361025
Weninger MLengauer PMössenböck HBinder WCortellessa VKoziolek ASmirni EPoess M(2017)User-centered Offline Analysis of Memory Monitoring DataProceedings of the 8th ACM/SPEC on International Conference on Performance Engineering10.1145/3030207.3030236(357-360)Online publication date: 17-Apr-2017
https://dl.acm.org/doi/10.1145/3030207.3030236

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