Empirical Analysis of Performance Problems on Code Level
Pages 117 - 120
Abstract
Performance problems are well known on architecture level. On code level their occurrences have not been systematically researched so far. Since a lot of everyday work of software developers is done on code level, methods and tools with focus on frequent performance problems are relevant. In the presented thesis, a method for systematically evaluating the occurrence and the frequency of performance problems on code level is presented and applied to repositories. The results of this empirical research will be a classification of performance problems and a quantification of their frequency. This will raise the awareness on certain problem classes for developers and will provide a basis for the development of new performance tools for preventing performance problems.
References
[1]
J. P. S. Alcocer and A. Bergel. Tracking down performance variation against source code evolution. In Proceedings of the 11th Symposium on Dynamic Languages, DLS 2015, pages 129--139, New York, NY, USA, 2015. ACM.
[2]
V. Cortellessa, A. Di Marco, and C. Trubiani. Performance antipatterns as logical predicates. In Engineering of Complex Computer Systems (ICECCS), 2010 15th IEEE International Conference on, pages 146--156. IEEE, 2010.
[3]
A. Georges, D. Buytaert, and L. Eeckhout. Statistically rigorous java performance evaluation. ACM SIGPLAN Notices, 42(10):57--76, 2007.
[4]
C. Heger, J. Happe, and R. Farahbod. Automated root cause isolation of performance regressions during software development. In ICPE 13, pages 27--38, New York, USA, 2013. ACM.
[5]
A. Hindle, A. Wilson, K. Rasmussen, E. J. Barlow, J. C. Campbell, and S. Romansky. Greenminer: A hardware based mining software repositories software energy consumption framework. In MSR 2014, pages 12--21, New York, USA, 2014. ACM.
[6]
V. Horkỳ, F. Haas, J. Kotr\vc, M. Lacina, and P. Truma. Performance regression unit testing: a case study. In Computer Performance Engineering, pages 149--163. Springer, 2013.
[7]
G. Jin, L. Song, X. Shi, J. Scherpelz, and S. Lu. Understanding and detecting real-world performance bugs. In Proceedings of the 33rd ACM SIGPLAN PLDI, PLDI '12, pages 77--88, New York, USA, 2012. ACM.
[8]
Y. Liu, C. Xu, and S.-C. Cheung. Characterizing and detecting performance bugs for smartphone applications. In Proceedings of the 36th ICPE, pages 1013--1024. ACM, 2014.
[9]
A. Nistor, T. Jiang, and L. Tan. Discovering, reporting, and fixing performance bugs. In MSR 2013, pages 237--246. IEEE Press, 2013.
[10]
M. Pradel, M. Huggler, and T. R. Gross. Performance regression testing of concurrent classes. In Proceedings of the 2014 International Symposium on Software Testing and Analysis, pages 13--25. ACM, 2014.
[11]
D. G. Reichelt and F. Scheller. Improving performance analysis of software system versions using change-based test selection. In Symposium on Software Performance, 2015.
[12]
D. G. Reichelt and J. Schmidt. Performanzanalyse von softwaresystemversionen: Methode und erste ergebnisse. In Software Engineering & Management 2015, Multikonferenz der GI-Fachbereiche Softwaretechnik (SWT) und Wirtschaftsinformatik (WI), FA WI-MAW, 17. Marz - 20. Marz 2015, Dresden, Germany, pages 153--158, 2015.
[13]
C. U. Smith and L. G. Williams. More new software performance antipatterns: Even more ways to shoot yourself in the foot. In CMG Conference, pages 717--725. Citeseer, 2003.
[14]
C. Trubiani and A. Koziolek. Detection and solution of software performance antipatterns in palladio architectural models. In ACM SIGSOFT Software Engineering Notes, volume 36, pages 19--30. ACM, 2011.
[15]
A. van Hoorn, J. Waller, and W. Hasselbring. Kieker: A framework for application performance monitoring and dynamic software analysis. In Proceedings of the 3rd joint ACM/SPEC International Conference on Performance Engineering (ICPE 2012), pages 247--248. ACM, April 2012.
[16]
A. Wert, J. Happe, and L. Happe. Supporting swift reaction: Automatically uncovering performance problems by systematic experiments. In Proceedings of the 2013 ICPE, pages 552--561. IEEE Press, 2013.
[17]
S. Zaman, B. Adams, and A. E. Hassan. Security versus performance bugs: a case study on firefox. In MSR 2011, pages 93--102. ACM, 2011.
Index Terms
- Empirical Analysis of Performance Problems on Code Level
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Published In
March 2016
346 pages
ISBN:9781450340809
DOI:10.1145/2851553
- General Chairs:
- Alberto Avritzer,
- Alexandru Iosup,
- Program Chairs:
- Xiaoyun Zhu,
- Steffen Becker
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Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.
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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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Overall Acceptance Rate 252 of 851 submissions, 30%
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