Software bug report dataset from Eclipse projects

IF 1.4 Q3 MULTIDISCIPLINARY SCIENCES

Data in Brief Pub Date : 2025-09-05 DOI:10.1016/j.dib.2025.112016

Noelia Lopez-Duran, David Romero-Organvidez, Fermín L. Cruz, David Benavides

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引用次数: 0

Abstract

In recent decades, the analysis of data from software projects — including source control systems, defect tracking systems, and code review repositories — has greatly improved our understanding of software development and its evolution. However, obtaining this information can be time-consuming, and the extracted data is not always well-maintained. This paper introduces an extensive dataset generated from Bugzilla repositories, focusing on key products from the Eclipse bug-tracking system. This dataset addresses the need for up-to-date data in existing repositories, preserving crucial historical information that may be lost due to the transition from Bugzilla to newer bug-tracking systems like Jira or GitHub Issues. Our dataset includes 301,378 bug reports along with all related information, organised into different folders that indicate the project in which the bug was filed. Additionally, we present a custom and lightweight Command Line Interface (CLI) tool designed to efficiently extract detailed information from Bugzilla repositories, automating data collection across various Bugzilla instances. The dataset and tool can be utilized for defect prediction, software maintenance, and evolutionary analysis. To the best of our knowledge, this is the largest, most complete, and up-to-date dataset of Eclipse bug reports available.

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来自Eclipse项目的软件bug报告数据集

近几十年来，对软件项目数据的分析——包括源代码控制系统、缺陷跟踪系统和代码审查存储库——极大地提高了我们对软件开发及其演变的理解。然而，获取这些信息可能很耗时，而且提取的数据并不总是得到很好的维护。本文介绍了从Bugzilla存储库生成的广泛数据集，重点关注Eclipse bug跟踪系统中的关键产品。该数据集解决了对现有存储库中最新数据的需求，保留了可能因从Bugzilla过渡到Jira或GitHub Issues等较新的错误跟踪系统而丢失的关键历史信息。我们的数据集包括301,378个bug报告以及所有相关信息，组织到不同的文件夹中，这些文件夹表明bug被归档的项目。此外，我们还提供了一个定制的轻量级命令行接口（CLI）工具，旨在有效地从Bugzilla存储库中提取详细信息，自动收集各种Bugzilla实例的数据。数据集和工具可以用于缺陷预测、软件维护和进化分析。据我们所知，这是目前可用的最大、最完整和最新的Eclipse bug报告数据集。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Data in Brief MULTIDISCIPLINARY SCIENCES-

CiteScore

3.10

自引率

0.00%

发文量

996

审稿时长

70 days

期刊介绍： Data in Brief provides a way for researchers to easily share and reuse each other''s datasets by publishing data articles that: -Thoroughly describe your data, facilitating reproducibility. -Make your data, which is often buried in supplementary material, easier to find. -Increase traffic towards associated research articles and data, leading to more citations. -Open up doors for new collaborations. Because you never know what data will be useful to someone else, Data in Brief welcomes submissions that describe data from all research areas.