Detecting and Characterizing Bots that Commit Code

التفاصيل البيبلوغرافية
العنوان: Detecting and Characterizing Bots that Commit Code
المؤلفون: Tapajit Dey, Sara Mousavi, Eduardo Ponce, Tanner Fry, Bogdan Vasilescu, Anna Filippova, Audris Mockus
المصدر: MSR, Mining Software Repositories, 2020
بيانات النشر: Zenodo
سنة النشر: 2020
المجموعة: Zenodo
مصطلحات موضوعية: Bots, Code Commits, Bot Commits, Bot Characterization
الوصف: Preprint of a paper accepted in MSR 2020 conference. Abstract: Background: Some developer activity traditionally performed manually, such as making code commits, opening, managing, or closing issues is increasingly subject to automation in many OSS projects. Specifically, such activity is often performed by tools that react to events or run at specific times. We refer to such automation tools as bots and, in many software mining scenarios related to developer productivity or code quality it is desirable to identify bots in order to separate their actions from actions of individuals. Aim: Find an automated way of identifying bots and code committed by these bots, and to characterize the types of bots based on their activity patterns. Method and Result: We propose BIMAN , a systematic approach to detect bots using author names, commit messages, files modified by the commit, and projects associated with the commits. For our test data, the value for AUC-ROC was 0.9. We also characterized these bots based on the time patterns of their code commits and the types of files modified, and found that they primarily work with documentation files and web pages, and these files are most prevalent in HTML and JavaScript ecosystems. We have compiled a shareable dataset containing detailed information about 461 bots we found (all of whom have more than 1000 commits) and 13,762,430 commits they created.
نوع الوثيقة: report
اللغة: English
Relation: https://doi.org/10.5281/zenodo.3695948; https://doi.org/10.5281/zenodo.3695949; oai:zenodo.org:3695949
DOI: 10.5281/zenodo.3695949
الاتاحة: https://doi.org/10.5281/zenodo.3695949
Rights: info:eu-repo/semantics/openAccess ; Creative Commons Attribution 4.0 International ; https://creativecommons.org/licenses/by/4.0/legalcode
رقم الانضمام: edsbas.BFAA2DF9
قاعدة البيانات: BASE