research-article

GrumPy: an automated approach to simplify issue data analysis for newcomers

Authors:

Joselito Mota Jr.,

Railana Santana,

Ivan MachadoAuthors Info & Claims

SBES '21: Proceedings of the XXXV Brazilian Symposium on Software Engineering

Pages 33 - 38

https://doi.org/10.1145/3474624.3476012

Published: 05 October 2021 Publication History

Abstract

The development model of open-source projects involves intensive developers’ collaborations to develop new features and maintain existing ones. Repositories hosting the projects may offer communication facilities to make partnerships happen in practice systematically. Issue reporting is one of the most employed strategies, as it carries valuable information about the software behavior or the repository itself. Indeed, issues have become the focus of several recent investigations, leading to an increased demand for automated approaches to support issue mining and analysis. The literature has brought a set of solutions for automating issue mining and analysis. However, they do not often provide developers with a user-friendly interface or an easy way to mine, manage or visualize issues’ data. Therefore, this paper introduces GrumPy, an open-source environment aimed to provide an automated approach to mine, manage, and visualize statistics about reported issues from open-source repositories. It provides a manageable multi-miner, a module to handle or visualize issues’ components, and a dashboard module responsible for showing repository data graphically. Our tool goal is to facilitate issues research work and its components.

References

[1]

John Anvik, Lyndon Hiew, and Gail C. Murphy. 2006. Who Should Fix This Bug?Association for Computing Machinery, New York, NY, USA, 361–370. https://doi.org/10.1145/1134285.1134336

[2]

Alessandra Bagnato, Konstantinos Barmpis, Nik Bessis, Luis Adrián Cabrera-Diego, Juri Di Rocco, Davide Di Ruscio, Tamás Gergely, Scott Hansen, Dimitris Kolovos, Philippe Krief, Ioannis Korkontzelos, Stéphane Laurière, Jose Manrique Lopez de la Fuente, Pedro Maló, Richard F. Paige, Diomidis Spinellis, Cedric Thomas, and Jurgen Vinju. 2018. Developer-Centric Knowledge Mining from Large Open-Source Software Repositories (CROSSMINER). In Software Technologies: Applications and Foundations, Martina Seidl and Steffen Zschaler (Eds.). Springer International Publishing, Cham, 375–384.

[3]

Chaoss.2021. CHAOSS web site. https://chaoss.github.io/grimoirelab/

[4]

Santiago Dueñas, Valerio Cosentino, Gregorio Robles, and Jesus M. Gonzalez-Barahona. 2018. Perceval: Software Project Data at Your Will. In Proceedings of the 40th International Conference on Software Engineering: Companion Proceeedings (Gothenburg, Sweden) (ICSE ’18). Association for Computing Machinery, New York, NY, USA, 1–4. https://doi.org/10.1145/3183440.3183475

Digital Library

[5]

Github. 2021. Creating a personal access token. https://docs.github.com/en/github/authenticating-to-github/keeping-your-account-and-data-secure/creating-a-personal-access-token

[6]

Georgios Gousios. 2013. The GHTorent Dataset and Tool Suite. In Proceedings of the 10th Working Conference on Mining Software Repositories(MSR ’13). IEEE Press, San Francisco, CA, USA, 233–236.

Digital Library

[7]

Georgios Gousios and Diomidis Spinellis. 2009. Alitheia Core: An extensible software quality monitoring platform. In IEEE 31st International Conference on Software Engineering. IEEE, Vancouver, BC, Canada, 579–582.

Digital Library

[8]

Hadi Hemmati, Sarah Nadi, Olga Baysal, Oleksii Kononenko, Wei Wang, Reid Holmes, and Michael W. Godfrey. 2013. The MSR Cookbook: Mining a decade of research. In 10th Working Conference on Mining Software Repositories (MSR). IEEE, San Francisco, CA, USA, 343–352.

Digital Library

[9]

Javier Luis Cánovas Izquierdo, Valerio Cosentino, Belén Rolandi, Alexandre Bergel, and Jordi Cabot. 2015. GiLA: GitHub label analyzer. In 22nd International Conference on Software Analysis, Evolution, and Reengineering (SANER). IEEE, Montreal, QC, Canada, 479–483.

[10]

Iman Keivanloo, Christopher Forbes, Aseel Hmood, Mostafa Erfani, Christopher Neal, George Peristerakis, and Juergen Rilling. 2012. A Linked Data platform for mining software repositories. In 9th IEEE Working Conference on Mining Software Repositories (MSR). IEEE, Zurich, Switzerland, 32–35. https://doi.org/10.1109/MSR.2012.6224296

[11]

Elvis Ligu, Theodoros Chaikalis, and Alexander Chatzigeorgiou. 2013. BuCo Reporter: Mining Software and Bug Repositories.BCI (Local), CEUR Workshop Proceedings 1036 (2013), 7 pages.

[12]

Kumiyo Nakakoji, Yasuhiro Yamamoto, Yoshiyuki Nishinaka, Kouichi Kishida, and Yunwen Ye. 2002. Evolution Patterns of Open-Source Software Systems and Communities. In Proceedings of the International Workshop on Principles of Software Evolution(IWPSE). ACM, New York, NY, USA, 10 pages.

Digital Library

[13]

strudel.scraper. 2020. stscraper - Python interface for GitHub API. https://cmustrudel.github.io/strudel.scraper/

[14]

A. Tarvo. 2009. Mining Software History to Improve Software Maintenance Quality: A Case Study. IEEE Software 26, 1 (2009), 34–40.

Digital Library

[15]

Hyrum K. Wright, Miryung Kim, and Dewayne E. Perry. 2010. Validity Concerns in Software Engineering Research. In Proceedings of the FSE/SDP Workshop on Future of Software Engineering Research (Santa Fe, New Mexico, USA) (FoSER ’10). Association for Computing Machinery, New York, NY, USA, 411–414.

Digital Library

[16]

T. Xie, S. Thummalapenta, D. Lo, and C. Liu. 2009. Data Mining for Software Engineering. Computer 42, 8 (2009), 55–62.

Digital Library

Cited By

Qiu HLieb AChou JCarneal MMok JAmspoker EVasilescu BDabbish L(2023)Climate Coach: A Dashboard for Open-Source Maintainers to Overview Community DynamicsProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3581317(1-18)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544548.3581317

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SBES '21: Proceedings of the XXXV Brazilian Symposium on Software Engineering

September 2021

473 pages

ISBN:9781450390613

DOI:10.1145/3474624

Copyright © 2021 ACM.

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]

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Published: 05 October 2021

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SBES '21

SBES '21: Brazilian Symposium on Software Engineering

September 27 - October 1, 2021

Joinville, Brazil

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Cited By

Qiu HLieb AChou JCarneal MMok JAmspoker EVasilescu BDabbish L(2023)Climate Coach: A Dashboard for Open-Source Maintainers to Overview Community DynamicsProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3581317(1-18)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544548.3581317

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