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MUBench: a benchmark for API-misuse detectors

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

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MUBench: a benchmark for API-misuse detectors. / Amani, Sven; Nadi, Sarah; Nguyen, Hoan A. et al.
MSR '16 Proceedings of the 13th International Conference on Mining Software Repositories. New York: ACM, 2016. p. 464-467.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

Harvard

Amani, S, Nadi, S, Nguyen, HA, Nguyen, TN & Mezini, E 2016, MUBench: a benchmark for API-misuse detectors. in MSR '16 Proceedings of the 13th International Conference on Mining Software Repositories. ACM, New York, pp. 464-467. https://doi.org/10.1145/2901739.2903506

APA

Amani, S., Nadi, S., Nguyen, H. A., Nguyen, T. N., & Mezini, E. (2016). MUBench: a benchmark for API-misuse detectors. In MSR '16 Proceedings of the 13th International Conference on Mining Software Repositories (pp. 464-467). ACM. https://doi.org/10.1145/2901739.2903506

Vancouver

Amani S, Nadi S, Nguyen HA, Nguyen TN, Mezini E. MUBench: a benchmark for API-misuse detectors. In MSR '16 Proceedings of the 13th International Conference on Mining Software Repositories. New York: ACM. 2016. p. 464-467 doi: 10.1145/2901739.2903506

Author

Amani, Sven ; Nadi, Sarah ; Nguyen, Hoan A. et al. / MUBench : a benchmark for API-misuse detectors. MSR '16 Proceedings of the 13th International Conference on Mining Software Repositories. New York : ACM, 2016. pp. 464-467

Bibtex

@inproceedings{81e900b5524544469b6fd2ca0c18f9e4,
title = "MUBench: a benchmark for API-misuse detectors",
abstract = "Over the last few years, researchers proposed a multitude of automated bug-detection approaches that mine a class of bugs that we call API misuses. Evaluations on a variety of software products show both the omnipresence of such misuses and the ability of the approaches to detect them.This work presents MuBench, a dataset of 89 API misuses that we collected from 33 real-world projects and a survey. With the dataset we empirically analyze the prevalence of API misuses compared to other types of bugs, finding that they are rare, but almost always cause crashes. Furthermore, we discuss how to use it to benchmark and compare API-misuse detectors.",
author = "Sven Amani and Sarah Nadi and Nguyen, {Hoan A.} and Nguyen, {Tien N.} and Ermira Mezini",
year = "2016",
doi = "10.1145/2901739.2903506",
language = "English",
isbn = "9781450341868",
pages = "464--467",
booktitle = "MSR '16 Proceedings of the 13th International Conference on Mining Software Repositories",
publisher = "ACM",

}

RIS

TY - GEN

T1 - MUBench

T2 - a benchmark for API-misuse detectors

AU - Amani, Sven

AU - Nadi, Sarah

AU - Nguyen, Hoan A.

AU - Nguyen, Tien N.

AU - Mezini, Ermira

PY - 2016

Y1 - 2016

N2 - Over the last few years, researchers proposed a multitude of automated bug-detection approaches that mine a class of bugs that we call API misuses. Evaluations on a variety of software products show both the omnipresence of such misuses and the ability of the approaches to detect them.This work presents MuBench, a dataset of 89 API misuses that we collected from 33 real-world projects and a survey. With the dataset we empirically analyze the prevalence of API misuses compared to other types of bugs, finding that they are rare, but almost always cause crashes. Furthermore, we discuss how to use it to benchmark and compare API-misuse detectors.

AB - Over the last few years, researchers proposed a multitude of automated bug-detection approaches that mine a class of bugs that we call API misuses. Evaluations on a variety of software products show both the omnipresence of such misuses and the ability of the approaches to detect them.This work presents MuBench, a dataset of 89 API misuses that we collected from 33 real-world projects and a survey. With the dataset we empirically analyze the prevalence of API misuses compared to other types of bugs, finding that they are rare, but almost always cause crashes. Furthermore, we discuss how to use it to benchmark and compare API-misuse detectors.

U2 - 10.1145/2901739.2903506

DO - 10.1145/2901739.2903506

M3 - Conference contribution/Paper

SN - 9781450341868

SP - 464

EP - 467

BT - MSR '16 Proceedings of the 13th International Conference on Mining Software Repositories

PB - ACM

CY - New York

ER -