On the public citation graph

Can GPT-4 Replicate Empirical Software Engineering Research?

https://doi.org/10.1145/3660767
0 signed · 71 inferred · view as graph

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.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

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

inferredcites →https://doi.org/10.1007/978-1-84800-044-5_3openalex-snapshot
Personal Opinion Surveys
inferredcites →https://doi.org/10.1007/s10664-013-9279-3openalex-snapshot
A practical guide to controlled experiments of software engineering tools with human participants
inferredcites →https://doi.org/10.1038/s41598-023-33607-zopenalex-snapshot
The SciQA Scientific Question Answering Benchmark for Scholarly Knowledge
inferredcites →https://doi.org/10.1080/0144929x.2022.2072768openalex-snapshot
Measuring user competence in using artificial intelligence: validity and reliability of artificial intelligence literacy scale
inferredcites →https://doi.org/10.1080/10508406.2013.802652openalex-snapshot
Confusing Claims for Data: A Critique of Common Practices for Presenting Qualitative Research on Learning
inferredcites →https://doi.org/10.1109/icse.2009.5070550openalex-snapshot
Does distributed development affect software quality? An empirical case study of Windows Vista
inferredcites →https://doi.org/10.1109/icse48619.2023.00047openalex-snapshot
A Qualitative Study on the Implementation Design Decisions of Developers
inferredcites →https://doi.org/10.1109/isese.2004.1334912openalex-snapshot
Understanding the impact of assumptions on experimental validity
inferredcites →https://doi.org/10.1109/ms.2021.3071086openalex-snapshot
On The Introduction of Automatic Program Repair in Bloomberg
inferredcites →https://doi.org/10.1109/re48521.2020.00028openalex-snapshot
NoRBERT: Transfer Learning for Requirements Classification
inferredcites →https://doi.org/10.1109/tse.2007.70731openalex-snapshot
Change Distilling:Tree Differencing for Fine-Grained Source Code Change Extraction
inferredcites →https://doi.org/10.1109/tse.2017.2754374openalex-snapshot
Data Scientists in Software Teams: State of the Art and Challenges
inferredcites →https://doi.org/10.1109/tse.2022.3201209openalex-snapshot
Flakify: A Black-Box, Language Model-Based Predictor for Flaky Tests
inferredcites →https://doi.org/10.1145/1806799.1806871openalex-snapshot
Characterizing and predicting which bugs get fixed
inferredcites →https://doi.org/10.1145/1985441.1985464openalex-snapshot
Do time of day and developer experience affect commit bugginess?
inferredcites →https://doi.org/10.1145/1985793.1985815openalex-snapshot
An empirical investigation into the role of API-level refactorings during software evolution
inferredcites →https://doi.org/10.1145/2568225.2568233openalex-snapshot
Analyze this! 145 questions for data scientists in software engineering
inferredcites →https://doi.org/10.1145/2597073.2597117openalex-snapshot
Security and emotion: sentiment analysis of security discussions on GitHub
inferredcites →https://doi.org/10.1145/2597073.2597118openalex-snapshot
Sentiment analysis of commit comments in GitHub: an empirical study
inferredcites →https://doi.org/10.1145/2786805.2786809openalex-snapshot
How practitioners perceive the relevance of software engineering research
inferredcites →https://doi.org/10.1145/2884781.2884829openalex-snapshot
Performance issues and optimizations in JavaScript
inferredcites →https://doi.org/10.1145/3188720openalex-snapshot
Lessons from building static analysis tools at Google
inferredcites →https://doi.org/10.1145/3236024.3236061openalex-snapshot
Towards a theory of software development expertise
inferredcites →https://doi.org/10.1145/3332165.3347940openalex-snapshot
Tea
inferredcites →https://doi.org/10.1145/3338112openalex-snapshot
Scaling static analyses at Facebook
inferredcites →https://doi.org/10.1145/3360311openalex-snapshot
Threats of a replication crisis in empirical computer science
inferredcites →https://doi.org/10.1145/3368089.3409717openalex-snapshot
Questions for data scientists in software engineering: a replication
inferredcites →https://doi.org/10.1145/3411764.3445267openalex-snapshot
Glinda: Supporting Data Science with Live Programming, GUIs and a Domain-specific Language
inferredcites →https://doi.org/10.1145/3463274.3463356openalex-snapshot
On Implicit Assumptions Underlying Software Engineering Research
inferredcites →https://doi.org/10.1145/3487567openalex-snapshot
A Tale of Two Cities: Software Developers Working from Home during the COVID-19 Pandemic
inferredcites →https://doi.org/10.1145/3490100.3516464openalex-snapshot
Language Models Can Generate Human-Like Self-Reports of Emotion
inferredcites →https://doi.org/10.1145/3491102.3501888openalex-snapshot
Tisane: Authoring Statistical Models via Formal Reasoning from Conceptual and Data Relationships
inferredcites →https://doi.org/10.1145/3510003.3510159openalex-snapshot
CLEAR
inferredcites →https://doi.org/10.1145/3510003.3510205openalex-snapshot
What makes a good commit message?
inferredcites →https://doi.org/10.1145/3520312.3534862openalex-snapshot
A systematic evaluation of large language models of code
inferredcites →https://doi.org/10.1145/3533767.3534396openalex-snapshot
Using pre-trained language models to resolve textual and semantic merge conflicts (experience paper)
inferredcites →https://doi.org/10.1145/3540250.3549082openalex-snapshot
Understanding skills for OSS communities on GitHub
inferredcites →https://doi.org/10.1145/3540250.3549177openalex-snapshot
First come first served: the impact of file position on code review
inferredcites →https://doi.org/10.1145/3544548.3580688openalex-snapshot
Evaluating Large Language Models in Generating Synthetic HCI Research Data: a Case Study
inferredcites →https://doi.org/10.1145/3581754.3584136openalex-snapshot
Supporting Qualitative Analysis with Large Language Models: Combining Codebook with GPT-3 for Deductive Coding
inferredcites →https://doi.org/10.1145/3586030openalex-snapshot
Grounded Copilot: How Programmers Interact with Code-Generating Models
inferredcites →https://doi.org/10.1145/3597503.3608128openalex-snapshot
A Large-Scale Survey on the Usability of AI Programming Assistants: Successes and Challenges
inferredcites →https://doi.org/10.1145/3613904.3641891openalex-snapshot
How Do Data Analysts Respond to AI Assistance? A Wizard-of-Oz Study
inferredcites →https://doi.org/10.1145/3613904.3641936openalex-snapshot
Reading Between the Lines: Modeling User Behavior and Costs in AI-Assisted Programming
inferredcites →https://doi.org/10.1145/3695988openalex-snapshot
Large Language Models for Software Engineering: A Systematic Literature Review
inferredcites →https://doi.org/10.1162/tacl_a_00638openalex-snapshot
Lost in the Middle: How Language Models Use Long Contexts
inferredcites →https://doi.org/10.1177/1077800405284363openalex-snapshot
Five Misunderstandings About Case-Study Research
inferredcites →https://doi.org/10.13016/m2nw1f-p0jxopenalex-snapshot
HCI Guidelines for Gender Equity and Inclusivity
inferredcites →https://doi.org/10.18653/v1/2024.findings-acl.321openalex-snapshot
Evaluating Large Language Models on Wikipedia-Style Survey Generation
inferredcites →https://doi.org/10.4230/lipics.giscience.2023.43openalex-snapshot
Aion Framework: Dimensional Emergence of AI Consciousness, Observer-Induced Collapse, and Cosmological Portal Dynamics
inferredcites →https://doi.org/10.48550/arxiv.2201.11903openalex-snapshot
BNAI, NO-TOKEN, and MIND-UNITY: Pillars of a Systemic Revolution in Artificial Intelligence
inferredcites →https://doi.org/10.6084/m9.figshare.24210468openalex-snapshot
Supplemental Materials for Can GPT-4 Replicate Empirical Software Engineering Research?

What points at this work

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

inferred← citeshttps://doi.org/10.1007/978-3-032-08977-9_41openalex-snapshot
Open-Source LLMs for Technical Q&A: Lessons from StackExchange
inferred← citeshttps://doi.org/10.1007/s10515-026-00629-6openalex-snapshot
An exploratory study on effectiveness of GPT-4o in conducting sub-tasks of systematic literature reviews
inferred← citeshttps://doi.org/10.1016/j.jss.2025.112541openalex-snapshot
LLMs and Stack Overflow discussions: Reliability, impact, and challenges
inferred← citeshttps://doi.org/10.1016/j.jss.2026.113110openalex-snapshot
History matters: Automatically estimating code quality in multi-round reviews via context-aware prompt-tuning
inferred← citeshttps://doi.org/10.1049/sfw2/3348017openalex-snapshot
Refactoring Object‐Oriented Software With ChatGPT: An Empirical Study
inferred← citeshttps://doi.org/10.1108/ecam-11-2024-1595openalex-snapshot
Evolution path, hot spots and frontiers of big data research in the construction industry from 2010 to 2024
inferred← citeshttps://doi.org/10.1109/icsme64153.2025.00089openalex-snapshot
Detecting Adversarial Prompted AI-Generated Code on Stack Overflow: A Benchmark Dataset and an Enhanced Detection Approach
inferred← citeshttps://doi.org/10.1109/msr66628.2025.00122openalex-snapshot
TestMigrationsInPy: A Dataset of Test Migrations from Unittest to Pytest
inferred← citeshttps://doi.org/10.1109/saner64311.2025.00009openalex-snapshot
Beyond pip Install: Evaluating LLM Agents for the Automated Installation of Python Projects
inferred← citeshttps://doi.org/10.1109/saner64311.2025.00067openalex-snapshot
Does the Tool Matter? Exploring Some Causes of Threats to Validity in Mining Software Repositories
inferred← citeshttps://doi.org/10.1109/sccc67219.2025.11420613openalex-snapshot
Generative Artificial Intelligence for AgileRE: A Systematic Mapping
inferred← citeshttps://doi.org/10.1109/tse.2026.3659293openalex-snapshot
Human Cognitive Pattern Simulation for Crowdsourced Test Report Consistency Detection
inferred← citeshttps://doi.org/10.1145/3663529.3663794openalex-snapshot
Predicting Test Results without Execution
inferred← citeshttps://doi.org/10.1145/3756681.3757002openalex-snapshot
Bridging AI and Human Knowledge: Towards a Deeper Understanding of Stack Overflow and ChatGPT
inferred← citeshttps://doi.org/10.1145/3765756openalex-snapshot
LLM-based Crowdsourced Test Report Clustering
inferred← citeshttps://doi.org/10.1145/3786149.3788304openalex-snapshot
An Investigation on How AI-Generated Responses Affect Software Engineering Surveys
inferred← citeshttps://doi.org/10.1145/3793302.3793362openalex-snapshot
Are Coding Agents Generating Over-Mocked Tests? An Empirical Study
inferred← citeshttps://doi.org/10.1145/3793654.3793749openalex-snapshot
Testing Framework Migration with Large Language Models
inferred← citeshttps://doi.org/10.3390/info17010073openalex-snapshot
Foundation Models in Software Engineering: A Taxonomy, Systematic Review, and In-Depth Analysis of Testing Support
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.