research-article

Digging into UML models to remove performance antipatterns

Authors:

Vittorio Cortellessa,

Antinisca Di Marco,

Romina Eramo,

Alfonso Pierantonio,

Catia TrubianiAuthors Info & Claims

QUOVADIS '10: Proceedings of the 2010 ICSE Workshop on Quantitative Stochastic Models in the Verification and Design of Software Systems

Pages 9 - 16

https://doi.org/10.1145/1808877.1808880

Published: 03 May 2010 Publication History

Get Access

Abstract

Performance antipatterns have been informally defined and characterized as bad practices in software design that can originate performance problems. Such special type of patterns can involve static and dynamic aspects of software as well as deployment features. It has been shown that quite often the inability to meet performance requirements is due to the presence of antipatterns in the software design. However the problem of formally defining antipatterns and automatically detect them within a design model has not been investigated yet. In this paper we examine this problem within the UML context and show how performance antipatterns can be defined and detected in UML models by mean of OCL. A case study in UML annotated with the MARTE profile is presented where, after a performance analysis that shows unsatisfactory results, performance antipatterns are detected through an OCL engine. The identification of an antipattern suggests the architectural alternatives that can remove that specific problem. We show in our example that the removal of a certain antipattern actually allows to overcome a specific performance problem.

References

[1]

JESS, the Rule Engine for the Java Platform, http://www.jessrules.com/jess/index.shtml.

Google Scholar

[2]

OCL 2.0 Specification, OMG, http://www.omg.org/cgi-bin/doc?formal/06-05-01.

Google Scholar

[3]

UML 2.0 Superstructure Specification, OMG, http://www.omg.org/cgi-bin/doc?formal/05-07-04.

Google Scholar

[4]

UML Profile for MARTE, OMG, http://www.omgmarte.org/Documents/Specifications/08-06-09.pdf.

Google Scholar

[5]

WinPEPSY-QNS, a tool for calculating performance measures of queueing networks, http://www7.informatik.unierlangen.de/prbazan/pepsy.

Google Scholar

[6]

S. Balsamo, A. Di Marco, P. Inverardi, and M. Simeoni. Model-based performance prediction in software development: A survey. IEEE Transactions on Software Engineering, 30(5):295--310, 2004.

Digital Library

Google Scholar

[7]

V. Cortellessa, A. Di Marco, and C. Trubiani. Performance antipatterns as logical predicates. In IEEE International Conference on Engineering of Complex Computer Systems, 2010. to appear.

Digital Library

Google Scholar

[8]

V. Cortellessa and R. Mirandola. Prima-uml: a performance validation incremental methodology on early uml diagrams. Sci. Comput. Program., 44(1):101--129, 2002.

Digital Library

Google Scholar

[9]

C. Hirel, R. Sahner, X. Zang, and K. Trivedi. Reliability and Performability Modeling using SHARPE 2000. In Computer Performance Evaluation: modelling techniques and tools, volume 1786 of LNCS, pages 345--349, 2000.

Digital Library

Google Scholar

[10]

R. Jain. Art of Computer Systems Performance Analysis. 1991.

Google Scholar

[11]

T. Parsons and J. Murphy. Detecting performance antipatterns in component based enterprise systems. Journal of Object Technology, 7(3):55--90, 2008.

Crossref

Google Scholar

[12]

C. U. Smith and L. G. Williams. Software performance antipatterns. In 2nd International Workshop on Software and Performance, 2000.

Digital Library

Google Scholar

[13]

C. U. Smith and L. G. Williams. More new software performance antipatterns: Even more ways to shoot yourself in the foot. In Computer Measurement Group Conference, 2003.

Google Scholar

[14]

J. Xu. Rule-based automatic software performance diagnosis and improvement. In WOSP'08, Workshop on Software Performance, pages 1--12, 2008.

Digital Library

Google Scholar

Cited By

View all

Dorgham DBelal NAbdelmoez W(2021)Early Performance Prediction in Bioinformatics Systems Using Palladio Component ModelingApplied Sciences10.3390/app1112542611:12(5426)Online publication date: 11-Jun-2021
https://doi.org/10.3390/app11125426
Farooq AZaytsev VVisser EKolovos DSöderberg E(2021)There is more than one way to zen your PythonProceedings of the 14th ACM SIGPLAN International Conference on Software Language Engineering10.1145/3486608.3486909(68-82)Online publication date: 17-Oct-2021
https://dl.acm.org/doi/10.1145/3486608.3486909
Smith CAmaral JKoziolek ATrubiani CIosup A(2020)Software Performance Antipatterns in Cyber-Physical SystemsProceedings of the ACM/SPEC International Conference on Performance Engineering10.1145/3358960.3379138(173-180)Online publication date: 20-Apr-2020
https://dl.acm.org/doi/10.1145/3358960.3379138
Show More Cited By

Index Terms

Digging into UML models to remove performance antipatterns

Recommendations

Performance evaluation of UML design with Stochastic Well-formed Nets

The paper presents a method to compute performance metrics (response time, sojourn time, throughput) on Unified Modeling Language design. The method starts with UML design annotated according to the UML Profile for Schedulability, Performance and Time. ...
UML Everywhere

A standardized and widely used diagramming notation is a sign of a profession's maturity. Yet in software engineering, we still use diverse and ad hoc notations. Here, the author proposes that engineers should put their differences aside and make a ...
PRIMA-UML: a performance validation incremental methodology on early UML diagrams
Special issue on unified modeling language (UML 2000)

The development of complex software systems satisfying performance requirements is achievable only spending careful attention to performance goals throughout the lifecycle, and especially from its very beginning. Unified modeling language (UML) is ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

QUOVADIS '10: Proceedings of the 2010 ICSE Workshop on Quantitative Stochastic Models in the Verification and Design of Software Systems

May 2010

50 pages

ISBN:9781605589725

DOI:10.1145/1808877

General Chair:
Carlo Ghezzi
Politecnico di Milano, Italy
,
Program Chairs:
Lars Grunske Swinburne
University of Technology, Australia
,
Raffaela Mirandola
Politecnico di Milano, Italy

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]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 03 May 2010

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Conference

ICSE '10

Sponsor:

SIGSOFT

ICSE '10: 32nd International Conference on Software Engineering

May 3, 2010

Cape Town, South Africa

Upcoming Conference

ICSE 2025

2025 IEEE/ACM 46th International Conference on Software Engineering

April 26 - May 3, 2025

Ottawa , ON , Canada

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

25
Total Citations
View Citations
320
Total Downloads

Downloads (Last 12 months)2
Downloads (Last 6 weeks)0

Reflects downloads up to 16 Nov 2024

Other Metrics

View Author Metrics

Citations

Cited By

View all

Dorgham DBelal NAbdelmoez W(2021)Early Performance Prediction in Bioinformatics Systems Using Palladio Component ModelingApplied Sciences10.3390/app1112542611:12(5426)Online publication date: 11-Jun-2021
https://doi.org/10.3390/app11125426
Farooq AZaytsev VVisser EKolovos DSöderberg E(2021)There is more than one way to zen your PythonProceedings of the 14th ACM SIGPLAN International Conference on Software Language Engineering10.1145/3486608.3486909(68-82)Online publication date: 17-Oct-2021
https://dl.acm.org/doi/10.1145/3486608.3486909
Smith CAmaral JKoziolek ATrubiani CIosup A(2020)Software Performance Antipatterns in Cyber-Physical SystemsProceedings of the ACM/SPEC International Conference on Performance Engineering10.1145/3358960.3379138(173-180)Online publication date: 20-Apr-2020
https://dl.acm.org/doi/10.1145/3358960.3379138
Das TDingel J(2018)Model development guidelines for UML-RTSoftware and Systems Modeling (SoSyM)10.1007/s10270-016-0549-617:3(717-752)Online publication date: 1-Jul-2018
https://dl.acm.org/doi/10.1007/s10270-016-0549-6
Arcelli DCortellessa VDi Pompeo DOuni AKessentini MCinnéide M(2016)Automated translation among EPSILON languages for performance-driven UML software model refactoringProceedings of the 1st International Workshop on Software Refactoring10.1145/2975945.2975951(25-32)Online publication date: 4-Sep-2016
https://dl.acm.org/doi/10.1145/2975945.2975951
Khan YEl-Attar M(2016)Using model transformation to refactor use case models based on antipatternsInformation Systems Frontiers10.1007/s10796-014-9528-z18:1(171-204)Online publication date: 1-Feb-2016
https://dl.acm.org/doi/10.1007/s10796-014-9528-z
Das TDingel JLethbridge T(2015)State machine antipatterns for UML-RTProceedings of the 18th International Conference on Model Driven Engineering Languages and Systems10.5555/3351736.3351747(54-63)Online publication date: 30-Sep-2015
https://dl.acm.org/doi/10.5555/3351736.3351747
Das TDingel J(2015)State machine antipatterns for UML-RT2015 ACM/IEEE 18th International Conference on Model Driven Engineering Languages and Systems (MODELS)10.1109/MODELS.2015.7338235(54-63)Online publication date: Sep-2015
https://doi.org/10.1109/MODELS.2015.7338235
Arcelli DCortellessa VTrubiani C(2015)Performance-Based Software Model Refactoring in Fuzzy ContextsCompiler Construction10.1007/978-3-662-46675-9_10(149-164)Online publication date: 2015
https://doi.org/10.1007/978-3-662-46675-9_10
Trubiani CGhabi AEgyed A(2015)Exploiting Traceability Uncertainty Between Software Architectural Models and Performance Analysis ResultsSoftware Architecture10.1007/978-3-319-23727-5_26(305-321)Online publication date: 22-Oct-2015
https://doi.org/10.1007/978-3-319-23727-5_26
Show More Cited By

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Cited By

Index Terms

Recommendations

Performance evaluation of UML design with Stochastic Well-formed Nets

UML Everywhere

PRIMA-UML: a performance validation incremental methodology on early UML diagrams