Copertina

Automated Classification of Source Code Changes Based on Metrics Clustering in the Software Development Process

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autore principale:	Kniazev, Evgenii
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Software Engineering Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Lingma SWE-GPT: An Open Development-Process-Centric Language Model for Automated Software Improvement
di: Ma, Yingwei, et al.
Pubblicazione: (2024)

app.build: A Production Framework for Scaling Agentic Prompt-to-App Generation with Environment Scaffolding
di: Kniazev, Evgenii, et al.
Pubblicazione: (2025)

A Process Mining-Based System For The Analysis and Prediction of Software Development Workflows
di: Dorado, Antía, et al.
Pubblicazione: (2025)

Hallucinations in Code Change to Natural Language Generation: Prevalence and Evaluation of Detection Metrics
di: Liu, Chunhua, et al.
Pubblicazione: (2025)

CIAO - Code In Architecture Out - Automated Software Architecture Documentation with Large Language Models
di: De Luca, Marco, et al.
Pubblicazione: (2026)

Beyond Final Code: A Process-Oriented Error Analysis of Software Development Agents in Real-World GitHub Scenarios
di: Chen, Zhi, et al.
Pubblicazione: (2025)

An Empirical Study of Proactive Coding Assistants in Real-World Software Development
di: Li, Lehui, et al.
Pubblicazione: (2026)

Automating a Complete Software Test Process Using LLMs: An Automotive Case Study
di: Wang, Shuai, et al.
Pubblicazione: (2025)

ReDef: Do Code Language Models Truly Understand Code Changes for Just-in-Time Software Defect Prediction?
di: Nam, Doha, et al.
Pubblicazione: (2025)

Leveraging Large Language Models for Code Translation and Software Development in Scientific Computing
di: Dhruv, Akash, et al.
Pubblicazione: (2024)

Survey of GenAI for Automotive Software Development: From Requirements to Executable Code
di: Petrovic, Nenad, et al.
Pubblicazione: (2025)

Generating Software Architecture Description from Source Code using Reverse Engineering and Large Language Model
di: Hatahet, Ahmad, et al.
Pubblicazione: (2025)

Bridging LLM-Generated Code and Requirements: Reverse Generation technique and SBC Metric for Developer Insights
di: Ponnusamy, Ahilan Ayyachamy Nadar
Pubblicazione: (2025)

AgentMesh: A Cooperative Multi-Agent Generative AI Framework for Software Development Automation
di: Khanzadeh, Sourena
Pubblicazione: (2025)

CODE-DITING: A Reasoning-Based Metric for Functional Alignment in Code Evaluation
di: Yang, Guang, et al.
Pubblicazione: (2025)

AutoEmpirical: LLM-Based Automated Research for Empirical Software Fault Analysis
di: Yu, Jiongchi, et al.
Pubblicazione: (2025)

Generating Automotive Code: Large Language Models for Software Development and Verification in Safety-Critical Systems
di: Kirchner, Sven, et al.
Pubblicazione: (2025)

SOEN-101: Code Generation by Emulating Software Process Models Using Large Language Model Agents
di: Lin, Feng, et al.
Pubblicazione: (2024)

Vibe-Coding: Feedback-Based Automated Verification with no Human Code Inspection, a Feasibility Study
di: Töpfer, Michal, et al.
Pubblicazione: (2026)

Multilingual Multimodal Software Developer for Code Generation
di: Chai, Linzheng, et al.
Pubblicazione: (2025)

Enhancing LLM-Based Code Generation with Complexity Metrics: A Feedback-Driven Approach
di: Sepidband, Melika, et al.
Pubblicazione: (2025)

A Defect Classification Framework for AI-Based Software Systems (AI-ODC)
di: Alannsary, Mohammed O.
Pubblicazione: (2025)

Software Development Life Cycle Perspective: A Survey of Benchmarks for Code Large Language Models and Agents
di: Wang, Kaixin, et al.
Pubblicazione: (2025)

Chatbot-Based Assessment of Code Understanding in Automated Programming Assessment Systems
di: Frankford, Eduard, et al.
Pubblicazione: (2026)

Previously on... Automating Code Review
di: Heumüller, Robert, et al.
Pubblicazione: (2025)

Code for Machines, Not Just Humans: Quantifying AI-Friendliness with Code Health Metrics
di: Borg, Markus, et al.
Pubblicazione: (2026)

Theory of Code Space: Do Code Agents Understand Software Architecture?
di: Sapunov, Grigory
Pubblicazione: (2026)

AI-Driven Self-Evolving Software: A Promising Path Toward Software Automation
di: Cai, Liyi, et al.
Pubblicazione: (2025)

A Benchmark for Localizing Code and Non-Code Issues in Software Projects
di: Zhang, Zejun, et al.
Pubblicazione: (2025)

SourceP: Detecting Ponzi Schemes on Ethereum with Source Code
di: Lu, Pengcheng, et al.
Pubblicazione: (2023)

Automatic Identification of Parallelizable Loops Using Transformer-Based Source Code Representations
di: Correia, Izavan dos S., et al.
Pubblicazione: (2026)

Distilled GPT for Source Code Summarization
di: Su, Chia-Yi, et al.
Pubblicazione: (2023)

Evaluating Software Development Agents: Patch Patterns, Code Quality, and Issue Complexity in Real-World GitHub Scenarios
di: Chen, Zhi, et al.
Pubblicazione: (2024)

Towards a Classification of Open-Source ML Models and Datasets for Software Engineering
di: González, Alexandra, et al.
Pubblicazione: (2024)

Predicting the Understandability of Computational Notebooks through Code Metrics Analysis
di: Ghahfarokhi, Mojtaba Mostafavi, et al.
Pubblicazione: (2024)

Benchmarks and Metrics for Evaluations of Code Generation: A Critical Review
di: Paul, Debalina Ghosh, et al.
Pubblicazione: (2024)

CodeClash: Benchmarking Goal-Oriented Software Engineering
di: Yang, John, et al.
Pubblicazione: (2025)

In-Context Code-Text Learning for Bimodal Software Engineering
di: Tang, Xunzhu, et al.
Pubblicazione: (2024)

Breaking Barriers in Software Testing: The Power of AI-Driven Automation
di: Naqvi, Saba, et al.
Pubblicazione: (2025)

Automated Validation of LLM-based Evaluators for Software Engineering Artifacts
di: Fandina, Ora Nova, et al.
Pubblicazione: (2025)