Image de couverture de livre

Benchmarking Educational Program Repair

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Koutcheme, Charles, Dainese, Nicola, Sarsa, Sami, Leinonen, Juho, Hellas, Arto, Denny, Paul
Format:	Preprint
Publié:	2024
Sujets:	Software Engineering Artificial Intelligence Computation and Language Computers and Society
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Open Source Language Models Can Provide Feedback: Evaluating LLMs' Ability to Help Students Using GPT-4-As-A-Judge
par: Koutcheme, Charles, et autres
Publié: (2024)

Evaluating Language Models for Generating and Judging Programming Feedback
par: Koutcheme, Charles, et autres
Publié: (2024)

Using Large Language Models to Enhance Programming Error Messages
par: Leinonen, Juho, et autres
Publié: (2022)

Comparing Code Explanations Created by Students and Large Language Models
par: Leinonen, Juho, et autres
Publié: (2023)

Teaching Language Models How to Code Like Learners: Conversational Serialization for Student Simulation
par: Koutcheme, Charles, et autres
Publié: (2026)

LLM-itation is the Sincerest Form of Data: Generating Synthetic Buggy Code Submissions for Computing Education
par: Leinonen, Juho, et autres
Publié: (2024)

Narrowing the Gap: Supervised Fine-Tuning of Open-Source LLMs as a Viable Alternative to Proprietary Models for Pedagogical Tools
par: Solano, Lorenzo Lee, et autres
Publié: (2025)

Evaluating Contextually Personalized Programming Exercises Created with Generative AI
par: Logacheva, Evanfiya, et autres
Publié: (2024)

AI-Generated Slides: Are They Good? Can Students Tell?
par: Leinonen, Juho, et autres
Publié: (2026)

On the Opportunities of Large Language Models for Programming Process Data
par: Edwards, John, et autres
Publié: (2024)

"Like a Nesting Doll": Analyzing Recursion Analogies Generated by CS Students using Large Language Models
par: Bernstein, Seth, et autres
Publié: (2024)

Synthetic Students: A Comparative Study of Bug Distribution Between Large Language Models and Computing Students
par: MacNeil, Stephen, et autres
Publié: (2024)

"Sometimes You Just Gotta Risk It for the Biscuit": A Portrait of Student Risk-Taking
par: Leinonen, Juho, et autres
Publié: (2024)

Let's Ask AI About Their Programs: Exploring ChatGPT's Answers To Program Comprehension Questions
par: Lehtinen, Teemu, et autres
Publié: (2024)

Automated Program Repair of Uncompilable Student Code
par: Pitts, Griffin, et autres
Publié: (2025)

The Role of Generative AI in Software Student CollaborAItion
par: Kiesler, Natalie, et autres
Publié: (2025)

InvAASTCluster: On Applying Invariant-Based Program Clustering to Introductory Programming Assignments
par: Orvalho, Pedro, et autres
Publié: (2022)

Knowledge Tracing in Programming Education Integrating Students' Questions
par: Kim, Doyoun, et autres
Publié: (2025)

Towards Automated Smart Contract Generation: Evaluation, Benchmarking, and Retrieval-Augmented Repair
par: Chen, Zaoyu, et autres
Publié: (2025)

Explaining Code with a Purpose: An Integrated Approach for Developing Code Comprehension and Prompting Skills
par: Denny, Paul, et autres
Publié: (2024)

Knowledge-Augmented Reasoning for EUAIA Compliance and Adversarial Robustness of LLMs
par: Momcilovic, Tomas Bueno, et autres
Publié: (2024)

McMining: Automated Discovery of Misconceptions in Student Code
par: Al-Hossami, Erfan, et autres
Publié: (2025)

Architectures of Error: A Philosophical Inquiry into AI and Human Code Generation
par: Sartori, Camilo Chacón
Publié: (2025)

Safety Analysis in the Era of Large Language Models: A Case Study of STPA using ChatGPT
par: Qi, Yi, et autres
Publié: (2023)

Learner-Tailored Program Repair: A Solution Generator with Iterative Edit-Driven Retrieval Enhancement
par: Dai, Zhenlong, et autres
Publié: (2026)

The Art of Repair: Optimizing Iterative Program Repair with Instruction-Tuned Models
par: Ruiz, Fernando Vallecillos, et autres
Publié: (2025)

MemRepair: Hierarchical Memory for Agentic Repository-Level Vulnerability Repair
par: Liu, Simiao, et autres
Publié: (2026)

Experiences from Integrating Large Language Model Chatbots into the Classroom
par: Hellas, Arto, et autres
Publié: (2024)

CangjieBench: Benchmarking LLMs on a Low-Resource General-Purpose Programming Language
par: Cheng, Junhang, et autres
Publié: (2026)

Towards the Ultimate Programming Language: Trust and Benevolence in the Age of Artificial Intelligence
par: Sawicki, Bartosz, et autres
Publié: (2024)

UA-Code-Bench: A Competitive Programming Benchmark for Evaluating LLM Code Generation in Ukrainian
par: Syromiatnikov, Mykyta, et autres
Publié: (2025)

Enhancing Educational Efficiency: Generative AI Chatbots and DevOps in Education 4.0
par: Mekić, Edis, et autres
Publié: (2024)

Academic Vibe Coding: Opportunities for Accelerating Research in an Era of Resource Constraint
par: Crowson, Matthew G, et autres
Publié: (2025)

LeafTutor: An AI Agent for Programming Assignment Tutoring
par: Bochard, Madison, et autres
Publié: (2025)

Investigating Markers and Drivers of Gender Bias in Machine Translations
par: Barclay, Peter J, et autres
Publié: (2024)

Benchmarking LLM Code Generation for Audio Programming with Visual Dataflow Languages
par: Zhang, William, et autres
Publié: (2024)

Beyond the Hype: A Comprehensive Review of Current Trends in Generative AI Research, Teaching Practices, and Tools
par: Prather, James, et autres
Publié: (2024)

The Impact of Fine-tuning Large Language Models on Automated Program Repair
par: Macháček, Roman, et autres
Publié: (2025)

PPM: Automated Generation of Diverse Programming Problems for Benchmarking Code Generation Models
par: Chen, Simin, et autres
Publié: (2024)

Logic Error Localization in Student Programming Assignments Using Pseudocode and Graph Neural Networks
par: Xu, Zhenyu, et autres
Publié: (2024)