Investigating Autonomous Agent Contributions in the Wild: Activity Patterns and Code Change over Time
Fuente:
arXiv
Saved in:
| Main Authors: | Popescu, Razvan Mihai, Gros, David, Botocan, Andrei, Pandita, Rahul, Devanbu, Prem, Izadi, Maliheh |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
An Exploratory Investigation into Code License Infringements in Large Language Model Training Datasets
by: Katzy, Jonathan, et al.
Published: (2024)
by: Katzy, Jonathan, et al.
Published: (2024)
Localized Calibrated Uncertainty in Code Language Models
by: Gros, David, et al.
Published: (2025)
by: Gros, David, et al.
Published: (2025)
Does In-IDE Calibration of Large Language Models work at Scale?
by: Koohestani, Roham, et al.
Published: (2025)
by: Koohestani, Roham, et al.
Published: (2025)
Model See, Model Do? Exposure-Aware Evaluation of Bug-vs-Fix Preference in Code LLMs
by: Al-Kaswan, Ali, et al.
Published: (2026)
by: Al-Kaswan, Ali, et al.
Published: (2026)
Language Models for Code Completion: A Practical Evaluation
by: Izadi, Maliheh, et al.
Published: (2024)
by: Izadi, Maliheh, et al.
Published: (2024)
A Multi-agent Onboarding Assistant based on Large Language Models, Retrieval Augmented Generation, and Chain-of-Thought
by: Ionescu, Andrei Cristian, et al.
Published: (2025)
by: Ionescu, Andrei Cristian, et al.
Published: (2025)
Evaluating Large Language Models for Functional and Maintainable Code in Industrial Settings: A Case Study at ASML
by: Mundhra, Yash, et al.
Published: (2025)
by: Mundhra, Yash, et al.
Published: (2025)
Rethinking IDE Customization for Enhanced HAX: A Hyperdimensional Perspective
by: Koohestani, Roham, et al.
Published: (2025)
by: Koohestani, Roham, et al.
Published: (2025)
HyperSeq: A Hyper-Adaptive Representation for Predictive Sequencing of States
by: Koohestani, Roham, et al.
Published: (2025)
by: Koohestani, Roham, et al.
Published: (2025)
RepairAgent: An Autonomous, LLM-Based Agent for Program Repair
by: Bouzenia, Islem, et al.
Published: (2024)
by: Bouzenia, Islem, et al.
Published: (2024)
On LLMs' Internal Representation of Code Correctness
by: Ribeiro, Francisco, et al.
Published: (2025)
by: Ribeiro, Francisco, et al.
Published: (2025)
Developer Interaction Patterns with Proactive AI: A Five-Day Field Study
by: Kuo, Nadine, et al.
Published: (2026)
by: Kuo, Nadine, et al.
Published: (2026)
AST-PAC: AST-guided Membership Inference for Code
by: Koohestani, Roham, et al.
Published: (2026)
by: Koohestani, Roham, et al.
Published: (2026)
Traces of Memorisation in Large Language Models for Code
by: Al-Kaswan, Ali, et al.
Published: (2023)
by: Al-Kaswan, Ali, et al.
Published: (2023)
Calibration and Correctness of Language Models for Code
by: Spiess, Claudio, et al.
Published: (2024)
by: Spiess, Claudio, et al.
Published: (2024)
How Robustly do LLMs Understand Execution Semantics?
by: Spiess, Claudio, et al.
Published: (2026)
by: Spiess, Claudio, et al.
Published: (2026)
Code4MeV2: a Research-oriented Code-completion Platform
by: Koohestani, Roham, et al.
Published: (2025)
by: Koohestani, Roham, et al.
Published: (2025)
In-IDE Human-AI Experience in the Era of Large Language Models; A Literature Review
by: Sergeyuk, Agnia, et al.
Published: (2024)
by: Sergeyuk, Agnia, et al.
Published: (2024)
A Survey of Trojans in Neural Models of Source Code: Taxonomy and Techniques
by: Hussain, Aftab, et al.
Published: (2023)
by: Hussain, Aftab, et al.
Published: (2023)
TreeRanker: Fast and Model-agnostic Ranking System for Code Suggestions in IDEs
by: Cipollone, Daniele, et al.
Published: (2025)
by: Cipollone, Daniele, et al.
Published: (2025)
A Qualitative Investigation into LLM-Generated Multilingual Code Comments and Automatic Evaluation Metrics
by: Katzy, Jonathan, et al.
Published: (2025)
by: Katzy, Jonathan, et al.
Published: (2025)
Ecosystem of Large Language Models for Code
by: Yang, Zhou, et al.
Published: (2024)
by: Yang, Zhou, et al.
Published: (2024)
Code Red! On the Harmfulness of Applying Off-the-shelf Large Language Models to Programming Tasks
by: Al-Kaswan, Ali, et al.
Published: (2025)
by: Al-Kaswan, Ali, et al.
Published: (2025)
Towards Understanding What Code Language Models Learned
by: Ahmed, Toufique, et al.
Published: (2023)
by: Ahmed, Toufique, et al.
Published: (2023)
Leveraging Large Language Models for Enhancing the Understandability of Generated Unit Tests
by: Deljouyi, Amirhossein, et al.
Published: (2024)
by: Deljouyi, Amirhossein, et al.
Published: (2024)
Prompt-with-Me: in-IDE Structured Prompt Management for LLM-Driven Software Engineering
by: Li, Ziyou, et al.
Published: (2025)
by: Li, Ziyou, et al.
Published: (2025)
Calibration of Large Language Models on Code Summarization
by: Virk, Yuvraj, et al.
Published: (2024)
by: Virk, Yuvraj, et al.
Published: (2024)
A Transformer-Based Approach for Smart Invocation of Automatic Code Completion
by: de Moor, Aral, et al.
Published: (2024)
by: de Moor, Aral, et al.
Published: (2024)
Benchmarking AI Models in Software Engineering: A Review, Search Tool, and Unified Approach for Elevating Benchmark Quality
by: Koohestani, Roham, et al.
Published: (2025)
by: Koohestani, Roham, et al.
Published: (2025)
CoDocBench: A Dataset for Code-Documentation Alignment in Software Maintenance
by: Pai, Kunal, et al.
Published: (2025)
by: Pai, Kunal, et al.
Published: (2025)
Do Autonomous Agents Contribute Test Code? A Study of Tests in Agentic Pull Requests
by: Haque, Sabrina, et al.
Published: (2026)
by: Haque, Sabrina, et al.
Published: (2026)
CodeAgent: Autonomous Communicative Agents for Code Review
by: Tang, Xunzhu, et al.
Published: (2024)
by: Tang, Xunzhu, et al.
Published: (2024)
Robustness, Security, Privacy, Explainability, Efficiency, and Usability of Large Language Models for Code
by: Yang, Zhou, et al.
Published: (2024)
by: Yang, Zhou, et al.
Published: (2024)
Promises, Perils, and (Timely) Heuristics for Mining Coding Agent Activity
by: Robbes, Romain, et al.
Published: (2026)
by: Robbes, Romain, et al.
Published: (2026)
TriCEGAR: A Trace-Driven Abstraction Mechanism for Agentic AI
by: Koohestani, Roham, et al.
Published: (2026)
by: Koohestani, Roham, et al.
Published: (2026)
Do Agents Dream of Root Shells? Partial-Credit Evaluation of LLM Agents in Capture the Flag Challenges
by: Al-Kaswan, Ali, et al.
Published: (2026)
by: Al-Kaswan, Ali, et al.
Published: (2026)
Human-AI Experience in Integrated Development Environments: A Systematic Literature Review
by: Sergeyuk, Agnia, et al.
Published: (2025)
by: Sergeyuk, Agnia, et al.
Published: (2025)
Developer Needs and Feasible Features for AI Assistants in IDEs
by: Sergeyuk, Agnia, et al.
Published: (2024)
by: Sergeyuk, Agnia, et al.
Published: (2024)
Automatic Semantic Augmentation of Language Model Prompts (for Code Summarization)
by: Ahmed, Toufique, et al.
Published: (2023)
by: Ahmed, Toufique, et al.
Published: (2023)
When is Generated Code Difficult to Comprehend? Assessing AI Agent Python Code Proficiency in the Wild
by: Temkulkiat, Nanthit, et al.
Published: (2026)
by: Temkulkiat, Nanthit, et al.
Published: (2026)
Similar Items
-
An Exploratory Investigation into Code License Infringements in Large Language Model Training Datasets
by: Katzy, Jonathan, et al.
Published: (2024) -
Localized Calibrated Uncertainty in Code Language Models
by: Gros, David, et al.
Published: (2025) -
Does In-IDE Calibration of Large Language Models work at Scale?
by: Koohestani, Roham, et al.
Published: (2025) -
Model See, Model Do? Exposure-Aware Evaluation of Bug-vs-Fix Preference in Code LLMs
by: Al-Kaswan, Ali, et al.
Published: (2026) -
Language Models for Code Completion: A Practical Evaluation
by: Izadi, Maliheh, et al.
Published: (2024)