Andror2: A dataset of manually-reproduced bug reports for android apps

Tyler Wendland; Jingyang Sun; Junayed Mahmud; S. M. Hasan Mansur; Steven Huang; Kevin Moran; Julia Rubin; Mattia Fazzini

doi:10.1109/MSR52588.2021.00082

Andror2: A dataset of manually-reproduced bug reports for android apps

Tyler Wendland, Jingyang Sun, Junayed Mahmud, S. M. Hasan Mansur, Steven Huang, Kevin Moran, Julia Rubin, Mattia Fazzini

Computer Science and Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

12 Scopus citations

Abstract

Software maintenance constitutes a large portion of the software development lifecycle. To carry out maintenance tasks, developers often need to understand and reproduce bug reports. As such, there has been increasing research activity coalescing around the notion of automating various activities related to bug reporting. A sizable portion of this research interest has focused on the domain of mobile apps. However, as research around mobile app bug reporting progresses, there is a clear need for a manually vetted and reproducible set of real-world bug reports that can serve as a benchmark for future work. This paper presents AndroR2: a dataset of 90 manually reproduced bug reports for Android apps listed on Google Play and hosted on GitHub, systematically collected via an in-depth analysis of 459 reports extracted from the GitHub issue tracker. For each reproduced report, AndroR2 includes the original bug report, an apk file for the buggy version of the app, an executable reproduction script, and metadata regarding the quality of the reproduction steps associated with the original report. We believe that the AndroR2 dataset can be used to facilitate research in automatically analyzing, understanding, reproducing, localizing, and fixing bugs for mobile applications as well as other software maintenance activities more broadly.

Original language	English (US)
Title of host publication	Proceedings - 2021 IEEE/ACM 18th International Conference on Mining Software Repositories, MSR 2021
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	600-604
Number of pages	5
ISBN (Electronic)	9781728187105
DOIs	https://doi.org/10.1109/MSR52588.2021.00082
State	Published - May 2021
Event	18th IEEE/ACM International Conference on Mining Software Repositories, MSR 2021 - Virtual, Online Duration: May 17 2021 → May 19 2021

Publication series

Name	Proceedings - 2021 IEEE/ACM 18th International Conference on Mining Software Repositories, MSR 2021

Conference

Conference	18th IEEE/ACM International Conference on Mining Software Repositories, MSR 2021
City	Virtual, Online
Period	5/17/21 → 5/19/21

Bibliographical note

Funding Information:
ACKNOWLEDGMENT This work was partially supported by a gift from Facebook and the NSF CCF-1955853 grant.

Publisher Copyright:
© 2021 IEEE.

Keywords

Bug reports
Mobile apps.
Software maintenance

Access

10.1109/MSR52588.2021.00082

OpenUrl availability

Full text

Cite this

Wendland, T., Sun, J., Mahmud, J., Hasan Mansur, S. M., Huang, S., Moran, K., Rubin, J., & Fazzini, M. (2021). Andror2: A dataset of manually-reproduced bug reports for android apps. In Proceedings - 2021 IEEE/ACM 18th International Conference on Mining Software Repositories, MSR 2021 (pp. 600-604). Article 9463119 (Proceedings - 2021 IEEE/ACM 18th International Conference on Mining Software Repositories, MSR 2021). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/MSR52588.2021.00082

Andror2: A dataset of manually-reproduced bug reports for android apps. / Wendland, Tyler; Sun, Jingyang; Mahmud, Junayed et al.
Proceedings - 2021 IEEE/ACM 18th International Conference on Mining Software Repositories, MSR 2021. Institute of Electrical and Electronics Engineers Inc., 2021. p. 600-604 9463119 (Proceedings - 2021 IEEE/ACM 18th International Conference on Mining Software Repositories, MSR 2021).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Wendland, T, Sun, J, Mahmud, J, Hasan Mansur, SM, Huang, S, Moran, K, Rubin, J & Fazzini, M 2021, Andror2: A dataset of manually-reproduced bug reports for android apps. in Proceedings - 2021 IEEE/ACM 18th International Conference on Mining Software Repositories, MSR 2021., 9463119, Proceedings - 2021 IEEE/ACM 18th International Conference on Mining Software Repositories, MSR 2021, Institute of Electrical and Electronics Engineers Inc., pp. 600-604, 18th IEEE/ACM International Conference on Mining Software Repositories, MSR 2021, Virtual, Online, 5/17/21. https://doi.org/10.1109/MSR52588.2021.00082

Wendland T, Sun J, Mahmud J, Hasan Mansur SM, Huang S, Moran K et al. Andror2: A dataset of manually-reproduced bug reports for android apps. In Proceedings - 2021 IEEE/ACM 18th International Conference on Mining Software Repositories, MSR 2021. Institute of Electrical and Electronics Engineers Inc. 2021. p. 600-604. 9463119. (Proceedings - 2021 IEEE/ACM 18th International Conference on Mining Software Repositories, MSR 2021). doi: 10.1109/MSR52588.2021.00082

Wendland, Tyler ; Sun, Jingyang ; Mahmud, Junayed et al. / Andror2 : A dataset of manually-reproduced bug reports for android apps. Proceedings - 2021 IEEE/ACM 18th International Conference on Mining Software Repositories, MSR 2021. Institute of Electrical and Electronics Engineers Inc., 2021. pp. 600-604 (Proceedings - 2021 IEEE/ACM 18th International Conference on Mining Software Repositories, MSR 2021).

@inproceedings{a668ab3e7dd84765b16b06f32d3c1a17,

title = "Andror2: A dataset of manually-reproduced bug reports for android apps",

abstract = "Software maintenance constitutes a large portion of the software development lifecycle. To carry out maintenance tasks, developers often need to understand and reproduce bug reports. As such, there has been increasing research activity coalescing around the notion of automating various activities related to bug reporting. A sizable portion of this research interest has focused on the domain of mobile apps. However, as research around mobile app bug reporting progresses, there is a clear need for a manually vetted and reproducible set of real-world bug reports that can serve as a benchmark for future work. This paper presents AndroR2: a dataset of 90 manually reproduced bug reports for Android apps listed on Google Play and hosted on GitHub, systematically collected via an in-depth analysis of 459 reports extracted from the GitHub issue tracker. For each reproduced report, AndroR2 includes the original bug report, an apk file for the buggy version of the app, an executable reproduction script, and metadata regarding the quality of the reproduction steps associated with the original report. We believe that the AndroR2 dataset can be used to facilitate research in automatically analyzing, understanding, reproducing, localizing, and fixing bugs for mobile applications as well as other software maintenance activities more broadly.",

keywords = "Bug reports, Mobile apps., Software maintenance",

author = "Tyler Wendland and Jingyang Sun and Junayed Mahmud and {Hasan Mansur}, {S. M.} and Steven Huang and Kevin Moran and Julia Rubin and Mattia Fazzini",

note = "Funding Information: ACKNOWLEDGMENT This work was partially supported by a gift from Facebook and the NSF CCF-1955853 grant. Publisher Copyright: {\textcopyright} 2021 IEEE.; 18th IEEE/ACM International Conference on Mining Software Repositories, MSR 2021 ; Conference date: 17-05-2021 Through 19-05-2021",

year = "2021",

month = may,

doi = "10.1109/MSR52588.2021.00082",

language = "English (US)",

series = "Proceedings - 2021 IEEE/ACM 18th International Conference on Mining Software Repositories, MSR 2021",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "600--604",

booktitle = "Proceedings - 2021 IEEE/ACM 18th International Conference on Mining Software Repositories, MSR 2021",

}

TY - GEN

T1 - Andror2

T2 - 18th IEEE/ACM International Conference on Mining Software Repositories, MSR 2021

AU - Wendland, Tyler

AU - Sun, Jingyang

AU - Mahmud, Junayed

AU - Hasan Mansur, S. M.

AU - Huang, Steven

AU - Moran, Kevin

AU - Rubin, Julia

AU - Fazzini, Mattia

PY - 2021/5

Y1 - 2021/5

N2 - Software maintenance constitutes a large portion of the software development lifecycle. To carry out maintenance tasks, developers often need to understand and reproduce bug reports. As such, there has been increasing research activity coalescing around the notion of automating various activities related to bug reporting. A sizable portion of this research interest has focused on the domain of mobile apps. However, as research around mobile app bug reporting progresses, there is a clear need for a manually vetted and reproducible set of real-world bug reports that can serve as a benchmark for future work. This paper presents AndroR2: a dataset of 90 manually reproduced bug reports for Android apps listed on Google Play and hosted on GitHub, systematically collected via an in-depth analysis of 459 reports extracted from the GitHub issue tracker. For each reproduced report, AndroR2 includes the original bug report, an apk file for the buggy version of the app, an executable reproduction script, and metadata regarding the quality of the reproduction steps associated with the original report. We believe that the AndroR2 dataset can be used to facilitate research in automatically analyzing, understanding, reproducing, localizing, and fixing bugs for mobile applications as well as other software maintenance activities more broadly.

AB - Software maintenance constitutes a large portion of the software development lifecycle. To carry out maintenance tasks, developers often need to understand and reproduce bug reports. As such, there has been increasing research activity coalescing around the notion of automating various activities related to bug reporting. A sizable portion of this research interest has focused on the domain of mobile apps. However, as research around mobile app bug reporting progresses, there is a clear need for a manually vetted and reproducible set of real-world bug reports that can serve as a benchmark for future work. This paper presents AndroR2: a dataset of 90 manually reproduced bug reports for Android apps listed on Google Play and hosted on GitHub, systematically collected via an in-depth analysis of 459 reports extracted from the GitHub issue tracker. For each reproduced report, AndroR2 includes the original bug report, an apk file for the buggy version of the app, an executable reproduction script, and metadata regarding the quality of the reproduction steps associated with the original report. We believe that the AndroR2 dataset can be used to facilitate research in automatically analyzing, understanding, reproducing, localizing, and fixing bugs for mobile applications as well as other software maintenance activities more broadly.

KW - Bug reports

KW - Mobile apps.

KW - Software maintenance

UR - http://www.scopus.com/inward/record.url?scp=85113670305&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85113670305&partnerID=8YFLogxK

U2 - 10.1109/MSR52588.2021.00082

DO - 10.1109/MSR52588.2021.00082

M3 - Conference contribution

AN - SCOPUS:85113670305

T3 - Proceedings - 2021 IEEE/ACM 18th International Conference on Mining Software Repositories, MSR 2021

SP - 600

EP - 604

BT - Proceedings - 2021 IEEE/ACM 18th International Conference on Mining Software Repositories, MSR 2021

PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 17 May 2021 through 19 May 2021

ER -

Andror2: A dataset of manually-reproduced bug reports for android apps

Abstract

Publication series

Conference

Bibliographical note

Keywords

Access

OpenUrl availability

Other files and links

Fingerprint

Cite this