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Inferring Performance Bug Patterns from Developer Commits

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Inferring Performance Bug Patterns from Developer Commits. / Chen, Yiqun; Winter, Stefan; Suri, Neeraj.

Proceedings - 2019 IEEE 30th International Symposium on Software Reliability Engineering, ISSRE 2019. ed. / Katinka Wolter; Ina Schieferdecker; Barbara Gallina; Michel Cukier; Roberto Natella; Naghmeh Ivaki; Nuno Laranjeiro. IEEE Computer Society Press, 2019. p. 70-81 8987574 (Proceedings - International Symposium on Software Reliability Engineering, ISSRE; Vol. 2019-October).

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

Harvard

Chen, Y, Winter, S & Suri, N 2019, Inferring Performance Bug Patterns from Developer Commits. in K Wolter, I Schieferdecker, B Gallina, M Cukier, R Natella, N Ivaki & N Laranjeiro (eds), Proceedings - 2019 IEEE 30th International Symposium on Software Reliability Engineering, ISSRE 2019., 8987574, Proceedings - International Symposium on Software Reliability Engineering, ISSRE, vol. 2019-October, IEEE Computer Society Press, pp. 70-81, 30th IEEE International Symposium on Software Reliability Engineering, ISSRE 2019, Berlin, Germany, 28/10/19. https://doi.org/10.1109/ISSRE.2019.00017

APA

Chen, Y., Winter, S., & Suri, N. (2019). Inferring Performance Bug Patterns from Developer Commits. In K. Wolter, I. Schieferdecker, B. Gallina, M. Cukier, R. Natella, N. Ivaki, & N. Laranjeiro (Eds.), Proceedings - 2019 IEEE 30th International Symposium on Software Reliability Engineering, ISSRE 2019 (pp. 70-81). [8987574] (Proceedings - International Symposium on Software Reliability Engineering, ISSRE; Vol. 2019-October). IEEE Computer Society Press. https://doi.org/10.1109/ISSRE.2019.00017

Vancouver

Chen Y, Winter S, Suri N. Inferring Performance Bug Patterns from Developer Commits. In Wolter K, Schieferdecker I, Gallina B, Cukier M, Natella R, Ivaki N, Laranjeiro N, editors, Proceedings - 2019 IEEE 30th International Symposium on Software Reliability Engineering, ISSRE 2019. IEEE Computer Society Press. 2019. p. 70-81. 8987574. (Proceedings - International Symposium on Software Reliability Engineering, ISSRE). https://doi.org/10.1109/ISSRE.2019.00017

Author

Chen, Yiqun ; Winter, Stefan ; Suri, Neeraj. / Inferring Performance Bug Patterns from Developer Commits. Proceedings - 2019 IEEE 30th International Symposium on Software Reliability Engineering, ISSRE 2019. editor / Katinka Wolter ; Ina Schieferdecker ; Barbara Gallina ; Michel Cukier ; Roberto Natella ; Naghmeh Ivaki ; Nuno Laranjeiro. IEEE Computer Society Press, 2019. pp. 70-81 (Proceedings - International Symposium on Software Reliability Engineering, ISSRE).

Bibtex

@inproceedings{246f4309d1e4432fb504c559d8c22950,
title = "Inferring Performance Bug Patterns from Developer Commits",
abstract = "Performance bugs, i.e., program source code that is unnecessarily inefficient, have received significant attention by the research community in recent years. A number of empirical studies have investigated how these bugs differ from 'ordinary' bugs that cause functional deviations and several approaches to aid their detection, localization, and removal have been proposed. Many of these approaches focus on certain subclasses of performance bugs, e.g., those resulting from redundant computations or unnecessary synchronization, and the evaluation of their effectiveness is usually limited to a small number of known instances of these bugs. To provide researchers working on performance bug detection and localization techniques with a larger corpus of performance bugs to evaluate against, we conduct a study of more than 700 performance bug fixing commits across 13 popular open source projects written in C and C++ and investigate the relative frequency of bug types as well as their complexity. Our results show that many of these fixes follow a small set of bug patterns, that they are contributed by experienced developers, and that the number of lines needed to fix performance bugs is highly project dependent.",
keywords = "Performance, Software Engineering, Testing",
author = "Yiqun Chen and Stefan Winter and Neeraj Suri",
year = "2019",
month = jul,
day = "17",
doi = "10.1109/ISSRE.2019.00017",
language = "English",
series = "Proceedings - International Symposium on Software Reliability Engineering, ISSRE",
publisher = "IEEE Computer Society Press",
pages = "70--81",
editor = "Katinka Wolter and Ina Schieferdecker and Barbara Gallina and Michel Cukier and Roberto Natella and Naghmeh Ivaki and Nuno Laranjeiro",
booktitle = "Proceedings - 2019 IEEE 30th International Symposium on Software Reliability Engineering, ISSRE 2019",
note = "30th IEEE International Symposium on Software Reliability Engineering, ISSRE 2019 ; Conference date: 28-10-2019 Through 31-10-2019",

}

RIS

TY - GEN

T1 - Inferring Performance Bug Patterns from Developer Commits

AU - Chen, Yiqun

AU - Winter, Stefan

AU - Suri, Neeraj

PY - 2019/7/17

Y1 - 2019/7/17

N2 - Performance bugs, i.e., program source code that is unnecessarily inefficient, have received significant attention by the research community in recent years. A number of empirical studies have investigated how these bugs differ from 'ordinary' bugs that cause functional deviations and several approaches to aid their detection, localization, and removal have been proposed. Many of these approaches focus on certain subclasses of performance bugs, e.g., those resulting from redundant computations or unnecessary synchronization, and the evaluation of their effectiveness is usually limited to a small number of known instances of these bugs. To provide researchers working on performance bug detection and localization techniques with a larger corpus of performance bugs to evaluate against, we conduct a study of more than 700 performance bug fixing commits across 13 popular open source projects written in C and C++ and investigate the relative frequency of bug types as well as their complexity. Our results show that many of these fixes follow a small set of bug patterns, that they are contributed by experienced developers, and that the number of lines needed to fix performance bugs is highly project dependent.

AB - Performance bugs, i.e., program source code that is unnecessarily inefficient, have received significant attention by the research community in recent years. A number of empirical studies have investigated how these bugs differ from 'ordinary' bugs that cause functional deviations and several approaches to aid their detection, localization, and removal have been proposed. Many of these approaches focus on certain subclasses of performance bugs, e.g., those resulting from redundant computations or unnecessary synchronization, and the evaluation of their effectiveness is usually limited to a small number of known instances of these bugs. To provide researchers working on performance bug detection and localization techniques with a larger corpus of performance bugs to evaluate against, we conduct a study of more than 700 performance bug fixing commits across 13 popular open source projects written in C and C++ and investigate the relative frequency of bug types as well as their complexity. Our results show that many of these fixes follow a small set of bug patterns, that they are contributed by experienced developers, and that the number of lines needed to fix performance bugs is highly project dependent.

KW - Performance

KW - Software Engineering

KW - Testing

U2 - 10.1109/ISSRE.2019.00017

DO - 10.1109/ISSRE.2019.00017

M3 - Conference contribution/Paper

AN - SCOPUS:85081101902

T3 - Proceedings - International Symposium on Software Reliability Engineering, ISSRE

SP - 70

EP - 81

BT - Proceedings - 2019 IEEE 30th International Symposium on Software Reliability Engineering, ISSRE 2019

A2 - Wolter, Katinka

A2 - Schieferdecker, Ina

A2 - Gallina, Barbara

A2 - Cukier, Michel

A2 - Natella, Roberto

A2 - Ivaki, Naghmeh

A2 - Laranjeiro, Nuno

PB - IEEE Computer Society Press

T2 - 30th IEEE International Symposium on Software Reliability Engineering, ISSRE 2019

Y2 - 28 October 2019 through 31 October 2019

ER -