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Data Reporting and Recording

Data Reporting and Recording

Reporting and recording are crucial in data documentation. The timely, thorough, and accurate documentation of facts is essential when recording patient data. Failure to record findings during an assessment or interpretation of a problem will result in loss of information and make the patient document unreliable. The reader is left with general impressions if the information is not specific. A recording is documenting data of the individual's health information in a traceable, secure, and...

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In Silico Modeling Method for Computational Aquatic Toxicology of Endocrine Disruptors: A Software-Based Approach Using QSAR Toolbox

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Software bug report dataset from Eclipse projects.

Noelia Lopez-Duran¹, David Romero-Organvidez¹, Fermín L Cruz¹

¹I3US, Department of Computer Languages and Systems, Universidad de Sevilla, Spain.

|October 27, 2025

Summary

This summary is machine-generated.

This study presents a comprehensive dataset of 301,378 Eclipse bug reports from Bugzilla, along with a CLI tool for data extraction. This resource aids in software defect prediction and maintenance analysis.

Keywords:

Bug extraction Bug report Bug report extraction tool Mining software repository Software

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Area of Science:

Software Engineering
Empirical Software Engineering
Data Science in Software Development

Background:

Analysis of software project data (e.g., source control, defect tracking) enhances understanding of software development.
Existing data extraction methods are time-consuming and data maintenance is often poor.
Transitioning from Bugzilla to newer systems risks losing historical bug data.

Purpose of the Study:

To introduce an extensive, up-to-date dataset of bug reports from the Eclipse bug-tracking system (Bugzilla).
To provide a custom Command Line Interface (CLI) tool for efficient Bugzilla data extraction.
To support research in defect prediction, software maintenance, and evolutionary analysis.

Main Methods:

Generated a dataset comprising 301,378 bug reports and associated information from Bugzilla repositories for Eclipse products.
Organized the dataset into project-specific folders for clarity.
Developed a lightweight CLI tool to automate detailed data extraction from Bugzilla instances.

Main Results:

Created the largest, most complete, and up-to-date publicly available dataset of Eclipse bug reports.
The CLI tool enables efficient and automated data collection from diverse Bugzilla repositories.
The dataset preserves historical bug information potentially lost during system migrations.

Conclusions:

The presented dataset and CLI tool offer valuable resources for the software engineering research community.
Facilitates advanced analyses in defect prediction, software maintenance, and understanding software evolution.
Addresses the need for accessible and well-maintained historical software project data.