Evidence map›Paper›PMID 41143270›Full record

ArticleData in brief2025

Software bug report dataset from Eclipse projects.

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

Abstract read
In one paragraph

Article in Data in brief, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Noelia Lopez-DuranI3US, Department of Computer Languages and Systems, Universidad de Sevilla, Spain.
David Romero-OrganvidezI3US, Department of Computer Languages and Systems, Universidad de Sevilla, Spain.
Fermín L CruzI3US, Department of Computer Languages and Systems, Universidad de Sevilla, Spain.
David BenavidesI3US, Department of Computer Languages and Systems, Universidad de Sevilla, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Bug extractionBug reportBug report extraction toolMining software repositorySoftware

Identifiers

PMID41143270
PMCPMC12545829

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.