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On Wasted Contributions: Understanding the Dynamics of Contributor-Abandoned Pull Requests–A Mixed-Methods Study of 10 Large Open-Source Projects
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Hyperparameters and tuning strategies for random forest
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Studying Software Engineers: Data Collection Techniques for Software Field Studies
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An in-depth study of the promises and perils of mining GitHub
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How does code style inconsistency affect pull request integration? An exploratory study on 117 GitHub projects
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Pull request latency explained: an empirical overview
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Detecting Duplicate Contributions in Pull-Based Model Combining Textual and Change Similarities
inferredcites →https://doi.org/10.1007/s11432-016-5595-8openalex-snapshot
Determinants of pull-based development in the context of continuous integration
inferredcites →https://doi.org/10.1016/j.jss.2018.09.016openalex-snapshot
What’s in a GitHub Star? Understanding Repository Starring Practices in a Social Coding Platform
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Does code quality affect pull request acceptance? An empirical study
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An introduction to ROC analysis
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The use of the area under the ROC curve in the evaluation of machine learning algorithms
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Efficient Global Optimization of Expensive Black-Box Functions
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Dominance statistics: Ordinal analyses to answer ordinal questions.
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Between facets and domains: 10 aspects of the Big Five.
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Violin Plots: A Box Plot-Density Trace Synergism
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The proof and measurement of association between two things
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Qualitative methods in empirical studies of software engineering
inferredcites →https://doi.org/10.1109/botse.2019.00018openalex-snapshot
Should I Stale or Should I Close? An Analysis of a Bot That Closes Abandoned Issues and Pull Requests
inferredcites →https://doi.org/10.1109/chase.2013.6614728openalex-snapshot
Why do newcomers abandon open source software projects?
inferredcites →https://doi.org/10.1109/icse.2015.55openalex-snapshot
Work Practices and Challenges in Pull-Based Development: The Integrator's Perspective
inferredcites →https://doi.org/10.1109/icsme.2016.31openalex-snapshot
Understanding the Factors That Impact the Popularity of GitHub Repositories
inferredcites →https://doi.org/10.1109/ms.2020.3036758openalex-snapshot
Insights Into Nonmerged Pull Requests in GitHub: Is There Evidence of Bias Based on Perceptible Race?
inferredcites →https://doi.org/10.1109/ms.2020.3044020openalex-snapshot
How Successful Are Open Source Contributions From Countries With Different Levels of Human Development?
inferredcites →https://doi.org/10.1109/msr.2013.6624034openalex-snapshot
The GHTorent dataset and tool suite
inferredcites →https://doi.org/10.1109/msr.2015.42openalex-snapshot
Wait for It: Determinants of Pull Request Evaluation Latency on GitHub
inferredcites →https://doi.org/10.1109/saner.2016.68openalex-snapshot
More Common Than You Think: An In-depth Study of Casual Contributors
inferredcites →https://doi.org/10.1109/saner.2019.8668023openalex-snapshot
Identifying Redundancies in Fork-based Development
inferredcites →https://doi.org/10.1109/sbes.2014.9openalex-snapshot
Preliminary Empirical Identification of Barriers Faced by Newcomers to Open Source Software Projects
inferredcites →https://doi.org/10.1109/tse.2019.2960357openalex-snapshot
Effects of Personality Traits on Pull Request Acceptance
inferredcites →https://doi.org/10.1109/tse.2020.3018726openalex-snapshot
Redundancy, Context, and Preference: An Empirical Study of Duplicate Pull Requests in OSS Projects
inferredcites →https://doi.org/10.1109/tse.2021.3053403openalex-snapshot
Are You Still Working on This? An Empirical Study on Pull Request Abandonment
inferredcites →https://doi.org/10.1109/tse.2021.3073773openalex-snapshot
On the Relationship Between the Developer’s Perceptible Race and Ethnicity and the Evaluation of Contributions in OSS
inferredcites →https://doi.org/10.1109/tse.2022.3165056openalex-snapshot
Pull Request Decisions Explained: An Empirical Overview
inferredcites →https://doi.org/10.1111/j.1600-0587.2012.07348.xopenalex-snapshot
Collinearity: a review of methods to deal with it and a simulation study evaluating their performance
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Visualizing the Effects of Predictor Variables in Black Box Supervised Learning Models
inferredcites →https://doi.org/10.1145/2568225openalex-snapshot
Proceedings of the 36th International Conference on Software Engineering
inferredcites →https://doi.org/10.1145/2568225.2568260openalex-snapshot
An exploratory study of the pull-based software development model
inferredcites →https://doi.org/10.1145/2568225.2568315openalex-snapshot
Influence of social and technical factors for evaluating contribution in GitHub
inferredcites →https://doi.org/10.1145/2593702openalex-snapshot
Proceedings of the 7th International Workshop on Cooperative and Human Aspects of Software Engineering
inferredcites →https://doi.org/10.1145/2597073openalex-snapshot
Proceedings of the 11th Working Conference on Mining Software Repositories
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A dataset for pull-based development research
inferredcites →https://doi.org/10.1145/2677832openalex-snapshot
Proceedings of the 6th Asia-Pacific Symposium on Internetware on Internetware
inferredcites →https://doi.org/10.1145/2695664.2695856openalex-snapshot
Acceptance factors of pull requests in open-source projects
inferredcites →https://doi.org/10.1145/2889160.2891035openalex-snapshot
Do biases related to geographical location influence work-related decisions in GitHub?
inferredcites →https://doi.org/10.1145/2950290.2950364openalex-snapshot
Effectiveness of code contribution: from patch-based to pull-request-based tools
inferredcites →https://doi.org/10.1145/3131704.3131725openalex-snapshot
Detecting Duplicate Pull-requests in GitHub
inferredcites →https://doi.org/10.1145/3195836.3195858openalex-snapshot
Who gets a patch accepted first?
inferredcites →https://doi.org/10.1145/3196398.3196455openalex-snapshot
A dataset of duplicate pull-requests in github
inferredcites →https://doi.org/10.1145/3239235.3240504openalex-snapshot
Relationship between geographical location and evaluation of developer contributions in github
inferredcites →https://doi.org/10.1145/3361242.3361254openalex-snapshot
Duplicate Pull Request Detection
inferredcites →https://doi.org/10.1145/3387940.3391504openalex-snapshot
The Inconvenient Side of Software Bots on Pull Requests
inferredcites →https://doi.org/10.1177/001316446002000104openalex-snapshot
A Coefficient of Agreement for Nominal Scales
inferredcites →https://doi.org/10.1177/0013164496056005002openalex-snapshot
Practical Significance: A Concept Whose Time Has Come
inferredcites →https://doi.org/10.1214/aoms/1177730491openalex-snapshot
On a Test of Whether one of Two Random Variables is Stochastically Larger than the Other
inferredcites →https://doi.org/10.18637/jss.v077.i01openalex-snapshot
ranger : A Fast Implementation of Random Forests for High Dimensional Data in C++ and R
inferredcites →https://doi.org/10.21105/joss.00786openalex-snapshot
iml: An R package for Interpretable Machine Learning
inferredcites →https://doi.org/10.21105/joss.02815openalex-snapshot
effectsize: Estimation of Effect Size Indices and Standardized Parameters
inferredcites →https://doi.org/10.21105/joss.03167openalex-snapshot
Visualizations with statistical details: The 'ggstatsplot' approach
inferredcites →https://doi.org/10.2307/2291607openalex-snapshot
Straightforward Statistics for the Behavioral Sciences.
inferredcites →https://doi.org/10.2307/2529310openalex-snapshot
The Measurement of Observer Agreement for Categorical Data
inferredcites →https://doi.org/10.32614/r.manualsopenalex-snapshot
R: A Language and Environment for Statistical Computing
inferredcites →https://doi.org/10.48550/arxiv.1201.0490openalex-snapshot
Scikit-learn: Machine Learning in Python
inferredcites →https://doi.org/10.48550/arxiv.1801.01489openalex-snapshot
All Models are Wrong, but Many are Useful: Learning a Variable's Importance by Studying an Entire Class of Prediction Models Simultaneously
inferredcites →https://doi.org/10.48550/arxiv.2105.13970openalex-snapshot
Pull Request Decision Explained: An Empirical Overview
inferredcites →https://doi.org/10.48550/arxiv.2109.10430openalex-snapshot
GAP2WSS: A Genetic Algorithm based on the Pareto Principle for Web Service Selection
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Gender differences and bias in open source: pull request acceptance of women versus men
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Why Not Fix This Bug? Characterizing and Identifying Bug‐Tagged Issues That Are Truly Fixed by Developers
inferred← citeshttps://doi.org/10.1002/spe.70104openalex-snapshot
An Empirical Study of Factors Associated With Contributor‐Abandoned Pull Requests in Open Source Software Projects
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Motivations, Development Challenges and Project Desertion in Public Blockchain: A Pilot Study
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Repeated Builds During Code Review: An Empirical Study of the OpenStack Community
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What About Our Bug? A Study on the Responsiveness of NPM Package Maintainers
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Understanding the Amount of Changes Required for Merge Request Acceptance: An Empirical Study
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On the Impact of Draft Pull Requests on Accelerating Feedback
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Are All Code Reviews the Same? Identifying and Assessing the Impact of Merge Request Deviations
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Understanding the Time to First Response in GitHub Pull Requests
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The SBOM Gap: Adoption and Compliance in Open Source Software
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Bringing Open Source Communication and Development Together: A Cross-Platform Study on Gitter and GitHub
inferred← citeshttps://doi.org/10.1109/tse.2024.3443741openalex-snapshot
Predicting the First Response Latency of Maintainers and Contributors in Pull Requests
inferred← citeshttps://doi.org/10.1109/tse.2025.3633310openalex-snapshot
Facilitating Wise Decision-Making for Bounty Backers in Open Source Software Communities
inferred← citeshttps://doi.org/10.1109/tse.2026.3685588openalex-snapshot
Cross-Project Flakiness: A Case Study of the OpenStack Ecosystem
inferred← citeshttps://doi.org/10.1145/3624739openalex-snapshot
Understanding the Helpfulness of Stale Bot for Pull-Based Development: An Empirical Study of 20 Large Open-Source Projects
inferred← citeshttps://doi.org/10.1145/3680472openalex-snapshot
MULTICR: Predicting Merged and Abandoned Code Changes in Modern Code Review Using Multi-Objective Search
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Explaining Explanations: An Empirical Study of Explanations in Code Reviews
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The Impact of Environment Configurations on the Stability of AI-Enabled Systems
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LGTM! Characteristics of Auto-Merged LLM-based Agentic PRs
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Understanding and Predicting Accepted Code Suggestions in AI-Assisted Programming
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The Impact of Large Language Models (LLMs) on Code Review Process
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