UP Research Data Repository2026 · dataset
Before it Breaks<p dir="ltr"><b>Before It Breaks: Detecting Breaking Dependency Updates with Large Language Models</b></p><p dir="ltr">This package contains everything needed to (1) rebuild the dataset of breaking and safe dependency updates, (2) re-run the LLM-based detector and its ablation study, (3) re-run the non-LLM baselines (SemVer and Maracas), and (4) recompute every number reported in the paper's evalu
figshare + Loughborough Research Repository + GRANTS Data + UP Research Data Repository2026 · Astronomical catalogue
Understanding Unfaithful Reporting by Coding Agents<p dir="ltr">Replication Package.</p>
ZivaHub + Deakin Research Online + DMU Figshare + HKU DataHub + Swinburne Figshare + DaYta Ya Rona + SUNScholarData + figshare + Loughborough Research Repository + GRANTS Data + UP Research Data Repository2026 · Astronomical catalogue
<i>A Four-Language Corpus of 11,809 Novice Comment-Code Pairs (Python, Java, C, C++)</i><p dir="ltr">This dataset accompanies the paper "Can a Professional Comment Taxonomy Label Student Code? A Four-Language Corpus of 11,809 Comment-Code Pairs" submitted to SIGCSE '27.</p><h3 dir="ltr"><b>Overview</b></h3><p dir="ltr">The corpus contains 11,809 cleaned and associate-mapped novice comment-code pairs extracted across four programming languages: Java (7,194), C (2,493), Python (2,092),
ZivaHub + Deakin Research Online + DMU Figshare2026 · dataset
Materials | Exploring LLMs and AI Agents for User Stories Production: Lessons Learned from a Classroom Experience<p dir="ltr">This research compares three strategies for creating USs: manual, supported by a general-purpose LLM, and supported by a specialized AI Agent. We analyze students' perceptions of the USs produced and the advantages and disadvantages of each approach.</p>
ZivaHub + Deakin Research Online + DMU Figshare + HKU DataHub + Swinburne Figshare + DaYta Ya Rona + SUNScholarData + figshare + Loughborough Research Repository + GRANTS Data + UP Research Data Repository2026 · Astronomical catalogue
Supplementary Material: Heterogeneous Adoption of LLM-Based Coding Assistants in Software Maintenance: Emerging Usage Archetypes<p dir="ltr">This directory contains the supplementary material associated with the study Heterogeneous Adoption of LLM-Based Coding Assistants in Software Maintenance: Emerging Usage Archetypes. Its purpose is to document the supporting artifacts used in the literature-informed contrast, the survey-based statistical analysis, and the generation of triangulation figures reported in the manuscript.
ZivaHub + Deakin Research Online + DMU Figshare2026 · dataset
Data package for "How developers split roles among them and a coding agent and what 'collaboration' means"<p dir="ltr">This is the data package accompanying an article with the following abstract:</p><p dir="ltr">Background: Coding agents such as Claude Code become more and more competent, so that their role in the development process can become more and more prominent.<br>Objective: How do developers characterize the role-split between them and their agent? How would they ideally want to collaborate
ZivaHub + Deakin Research Online + HKU DataHub + DaYta Ya Rona + figshare + Loughborough Research Repository + UP Research Data Repository2026 · Astronomical catalogue
Modeling Dependency-Propagated Ecosystem Impact of Changes in Maintenance Activities: Evaluating Support Strategies in the PyPI Network<h3 dir="ltr">Overview</h3><p dir="ltr">This replication package accompanies the paper:</p><p dir="ltr"><i>“Modeling Dependency-Propagated Ecosystem Impact of Changes in Maintenance Activities: Evaluating Support Strategies in the PyPI Network.”</i></p><p dir="ltr">It contains all code, configuration files, and datasets required to reproduce the study’s analyses of:</p><ul><li>impact-driven librar
ZivaHub + Deakin Research Online + DMU Figshare2026 · dataset
Arquivos usados na pesquisa<p dir="ltr">Arquivos utilizados na pesquisa, que deram suporte à aplicação do método, à obtenção dos resultados e à fundamentação da discussão. Cada um cumpre um propósito distinto dentro do processo:</p><ul><li><b>dados_bugs.csv</b> - Dados brutos extraídos do Jira, que constituem a população de bugs analisada na pesquisa.</li><li><b>sort_bugs.py</b> - Script que extrai da população de bugs uma
ZivaHub2026 · dataset
A Comprehensive Study of Large Language Models for Software Requirements Classification<p dir="ltr">Journal</p>
ZivaHub + HKU DataHub + DaYta Ya Rona + figshare + Loughborough Research Repository + UP Research Data Repository2026 · Astronomical catalogue
Supplementary material - Communication in Software Development Context: Characteristics, Challenges and Perceived Impacts<p dir="ltr">Supplementary material related to the work of Communication in Software Development Context: Characteristics, Challenges and Perceived Impacts.</p>
HKU DataHub + figshare + Loughborough Research Repository + UP Research Data Repository2026 · Astronomical catalogue
Replication Package<p dir="ltr">Replication Package</p>
ZivaHub2026 · dataset
An Empirical Investigation of Pre-Trained Deep Learning Model Reuse in the Scientific Process<p dir="ltr">Deep learning has achieved recognition for its impact within natural sciences, yet the prohibitive financial and technical cost of training models from scratch inhibits adoption. Following software engineering community guidance, natural scientists are reusing pre-trained deep learning models (PTMs) to amortize these costs. While prior works recommend PTM reuse patterns, we present th
HKU DataHub + figshare + Loughborough Research Repository2026 · Astronomical catalogue
Experimental materials for DOM to Source approach.<p dir="ltr">This dataset contains empirical data, metrics, and training materials from the controlled experiment conducted to evaluate the D2S approach and the C2C toolset.<br><br>1. Experimental Data (EXPERIMENTAL_DATA)</p><p dir="ltr">Individual participant metrics recorded during the experiment:</p><ul><li>Group and Expertise Level: Assigned group (Control vs. Experimental) and skill level (de
figshare + Loughborough Research Repository2026 · Astronomical catalogue
List Of Studies<p dir="ltr">This Excel workbook contains the study-extraction and evidence-mapping data used for my MSc dissertation on AI-assisted programming and AI-generated code. It records the studies considered in the review, including their titles, authors, publication years, study types, AI tools, programming languages, inclusion decisions, quality-appraisal notes and relevance to four research questions
figshare + Loughborough Research Repository2026 · Astronomical catalogue
Malva<h2 dir="ltr">Malva<br></h2><p dir="ltr">Malva is an artifact for studying tool-mediated interaction failures in agentic GUI software. It contains a defect library built from 40 open-source applications, a task suite for reproducing representative failures, and MalvaGuard, a static checker that detects missing tool-interaction guards before agent execution.</p><p dir="ltr">The defect library follo
figshare + Loughborough Research Repository2026 · Astronomical catalogue
Replication Package for “The Review-Priority Label in OpenStack: An Empirical Study of a Unilateral Triage Signal”<p dir="ltr">This replication package supports the paper “The Review-Priority Label in OpenStack: An Empirical Study of a Unilateral Triage Signal”.</p><p><br></p><p dir="ltr">It contains the full pipeline used in the study, including:</p><p dir="ltr">- A dataset of 11,132 OpenStack changes with review-priority (RP) signals</p><p dir="ltr">- Extracted RP disagreement cases and assigner-level stati
figshare + Loughborough Research Repository2026 · Astronomical catalogue
Open Data Package for Book Chapter "On the Introduction of Clean Code Violations in Open-Source Python Projects"<p dir="ltr">The data package comprises 20,699 SonarQube issues arising in 57 open-source Python projects. It is a filtered and processed version of the original contribution from <a href="https://doi.org/10.6084/m9.figshare.25008653" target="_blank" rel="noreferrer">https://doi.org/10.6084/m9.figshare.25008653</a>.</p><p dir="ltr"><b>Files in this data package:</b></p><p dir="ltr"><b>application_
figshare + Loughborough Research Repository2026 · Astronomical catalogue
Forecasting the Maintained Score from the OpenSSF Scorecard: A Study of GitHub Repositories Linked to PyPI Packages<h2 dir="ltr">Overview</h2><p dir="ltr">This replication package accompanies the paper <b>“</b><b>Forecasting the Maintained Score from the OpenSSF Scorecard: A Study of GitHub Repositories Linked to PyPI Packages</b><b>”</b>. It contains all code, configuration files, input datasets, and generated outputs required to reproduce the study’s experiments on forecasting the OpenSSF Maintained score fo
figshare + Loughborough Research Repository2026 · Astronomical catalogue
Investigating Metadata Practices for Repository and Donation Platform URLs in PyPI Libraries: An Empirical Study<h2 dir="ltr">Overview</h2><p dir="ltr">Replication package for a full research paper enabling end-to-end reproduction of:</p><ol><li>LLM-based topic modeling pipeline of open-ended survey responses.</li><li>Two quantitative results replicated from prior work using curated Jupyter notebooks.</li></ol><h2 dir="ltr">Contents</h2><ul><li><b>Surveys:</b> PDF copies of both survey instruments.</li><li>
figshare + Loughborough Research Repository2026 · Astronomical catalogue
Analyzing the Availability of Private Contact Channels for PyPI Libraries<p dir="ltr">The dataset is a JSON file mapping library names to the following information:</p><ul><li>their direct dependencies</li><li>available e-mail addresses on PyPI</li><li>where available, e-mail addresses and repository ownership type found on GitHub</li></ul><p dir="ltr">The notebook analyzes the data to calculate the following metrics:</p><ul><li>Distribution of sources where e-mail add
figshare2026 · Astronomical catalogue
CoverUp-CM full online-evolve results (coverup_cm_full_002_m20)Retained report-level results for historical CoverUp-CM full-dataset online Skill evolution experiment coverup_cm_full_002_m20. Evaluated 425 modules across 24 projects comparing no_skill, static_skill, feedback_only, self_evolve, and online_evolve. Files include final detailed report, summary table, result summary, and ZIP bundle.
figshare2026 · Astronomical catalogue
Experimental Materials and Dataset - "Literature-Grounded Generation of README Files with Large Language Models: A Dual Human–LLM Evaluation"<p dir="ltr">This is the complete replication package for the ISE 2026 paper "Literature-Grounded Generation of README Files with Large Language Models: A Dual Human–LLM Evaluation". It contains every artifact behind every number reported in the paper: the prompts, the generated README files, the raw human and automated evaluations, and the analysis scripts that turn them into the reported statist
figshare2026 · Astronomical catalogue
Interviews SE<p dir="ltr">How Many Interviews Are Enough in a Software Engineering Study? Preliminary Findings on Sample Size and Saturation</p>
figshare2026 · Astronomical catalogue
K8S-Commits<p dir="ltr">Dataset with Kubernetes commits classified.</p>
figshare2026 · Astronomical catalogue
Variance-Aware Regression Testing for Model Migration in Compound LLM Pipelines - Reproducibility Artifact<p dir="ltr">Reproducibility artifact for the manuscript "Variance-Aware Regression Testing for Model Migration in Compound LLM Pipelines." Includes recorded model-call outputs/ledger, analysis code, figures, tables, tests, and reproduction instructions. Raw ContractNLI files are intentionally excluded and must be obtained separately from the original source.</p>