On the public citation graph

https://doi.org/10.2139/ssrn.4575968

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Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-642-29044-2openalex-extracted
Experimentation in Software Engineering
inferredcites →https://doi.org/10.1007/s10664-015-9381-9openalex-extracted
An empirical study of the impact of modern code review practices on software quality
inferredcites →https://doi.org/10.1016/j.infsof.2019.106241openalex-extracted
Intelligent software engineering in the context of agile software development: A systematic literature review
inferredcites →https://doi.org/10.1109/icse.2013.6606617openalex-extracted
Expectations, outcomes, and challenges of modern code review
inferredcites →https://doi.org/10.1109/ieeestd.1998.237324openalex-extracted
IEEE Standard for Software Reviews
inferredcites →https://doi.org/10.1109/isco.2017.7855962openalex-extracted
Code review analysis of software system using machine learning techniques
inferredcites →https://doi.org/10.1109/issre59848.2023.00026openalex-extracted
LLaMA-Reviewer: Advancing Code Review Automation with Large Language Models through Parameter-Efficient Fine-Tuning
inferredcites →https://doi.org/10.1109/qrs.2016.19openalex-extracted
A Faceted Classification Scheme for Change-Based Industrial Code Review Processes
inferredcites →https://doi.org/10.1109/saner.2015.7081824openalex-extracted
Who should review my code? A file location-based code-reviewer recommendation approach for Modern Code Review
inferredcites →https://doi.org/10.1109/tse.2022.3214764openalex-extracted
Managing Technical Debt Using Intelligent Techniques - A Systematic Mapping Study
inferredcites →https://doi.org/10.1145/3196321.3196334openalex-extracted
Deep code comment generation
inferredcites →https://doi.org/10.1145/3510003.3510067openalex-extracted
AutoTransform
inferredcites →https://doi.org/10.1145/3540250.3549081openalex-extracted
Automating code review activities by large-scale pre-training
inferredcites →https://doi.org/10.48550/arxiv.2203.09095openalex-extracted
inferredcites →https://doi.org/10.48550/arxiv.2308.11148openalex-extracted
inferredcites →https://doi.org/10.48550/arxiv.2309.08221openalex-extracted
inferredcites →https://doi.org/10.5555/2486788.2486882openalex-extracted
Expectations, outcomes, and challenges of modern code review
inferredcites →https://doi.org/10.5753/vem.2022.226597openalex-extracted
ConCAD: A Tool for Interactive Detection of Code Anomalies

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1007/978-3-032-19675-0_9openalex-snapshot
AI in Software Testing: Automated Error Identification and Resolution
inferred← citeshttps://doi.org/10.1145/3658644.3690190openalex-snapshot
Skipping the Security Side Quests: A Qualitative Study on Security Practices and Challenges in Game Development
inferred← citeshttps://doi.org/10.34218/ijrcait_08_01_004openalex-snapshot
ENHANCING DEVELOPER PRODUCTIVITY WITH AI-DRIVEN TOOLS: THE FUTURE OF CODING ASSISTANCE
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