Software Engineering

Papers filed under cs.SE on arXiv, each one already summarized by Paperlayer. Open any of them to read the summary beside the original PDF, with every point linked to the line, figure, or table it came from.

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421 to 480 of 1,389

NVIDIA FLARE: Federated Learning from Simulation to Real-World
Holger R. Roth, Yan Cheng, Yuhong Wen +20
cs.LGcs.AIcs.CVarXiv:2210.13291v32022
Detecting DBMS Bugs by Constructing Equivalent Representations of Intermediate Query Results
Xiaoxu Niu, Gong Chen, Jinfu Chen +1
cs.DBcs.SEarXiv:2608.30385v12026
Astra: A Multi-Agent System for GPU Kernel Performance Optimization
Anjiang Wei, Tianran Sun, Yogesh Seenichamy +5
cs.DCcs.AIcs.CLarXiv:2509.07506v22025
Agent Behavioral Contracts: Formal Specification and Runtime Enforcement for Reliable Autonomous AI Agents
Varun Pratap Bhardwaj
cs.AIcs.MAcs.SEarXiv:2602.22302v12026
Getting pwn'd by AI: Penetration Testing with Large Language Models
Andreas Happe, Jürgen Cito
cs.CLcs.AIcs.CRarXiv:2308.00121v32023
SWE-Lego: Pushing the Limits of Supervised Fine-tuning for Software Issue Resolving
Chaofan Tao, Jierun Chen, Yuxin Jiang +11
cs.SEcs.CLarXiv:2601.01426v22026
Pandemic Programming: How COVID-19 affects software developers and how their organizations can help
Paul Ralph, Sebastian Baltes, Gianisa Adisaputri +14
cs.SEcs.CYarXiv:2005.01127v32020
Contrastive Code Representation Learning
Paras Jain, Ajay Jain, Tianjun Zhang +3
cs.LGcs.AIcs.PLarXiv:2007.04973v42020
Natural Language to Code Translation with Execution
Freda Shi, Daniel Fried, Marjan Ghazvininejad +2
cs.CLcs.SEarXiv:2204.11454v22022
Who Needs MLOps: What Data Scientists Seek to Accomplish and How Can MLOps Help?
Sasu Mäkinen, Henrik Skogström, Eero Laaksonen +1
cs.SEarXiv:2103.08942v12021
Legacy System Modernization with Coding Agents: A Case Study
Iago da Silva Rodrigues Alves, Cristiano Politowski, João Eduardo Montandon
cs.SEarXiv:2608.28972v12026
What Is a System? An Interaction-Based Account of Structure-Behavior Coalescence in General Systems Theory
William S. Chao
cs.SEeess.SYarXiv:2609.00043v12026
FEA-Bench: A Benchmark for Evaluating Repository-Level Code Generation for Feature Implementation
Wei Li, Xin Zhang, Zhongxin Guo +6
cs.SEcs.CLarXiv:2503.06680v22025
ProgramBench: Can Language Models Rebuild Programs From Scratch?
John Yang, Kilian Lieret, Jeffrey Ma +9
cs.SEcs.AIarXiv:2605.03546v12026
In-IDE Code Generation from Natural Language: Promise and Challenges
Frank F. Xu, Bogdan Vasilescu, Graham Neubig
cs.SEarXiv:2101.11149v32021
Hints Help But Do They Teach? Evaluating Skills Transfer in Code Generation
Will Badr
cs.SEcs.AIcs.CLarXiv:2609.01106v12026
Towards Robust Agentic CUDA Kernel Benchmarking, Verification, and Optimization
Robert Tjarko Lange, Qi Sun, Aaditya Prasad +3
cs.SEcs.AIcs.LGarXiv:2509.14279v12025
Seed-Coder: Let the Code Model Curate Data for Itself
ByteDance Seed, Yuyu Zhang, Jing Su +24
cs.CLcs.SEarXiv:2506.03524v22025
A Critical Review of "Automatic Patch Generation Learned from Human-Written Patches": Essay on the Problem Statement and the Evaluation of Automatic Software Repair
Martin Monperrus
cs.SEarXiv:1408.2103v12014
UML Class Diagram Evaluation and Repair Strategies based on LLMs
Jie Liang, Peng Liang, Chong Wang
cs.SEarXiv:2608.28800v12026
LiveCodeBench Pro: How Do Olympiad Medalists Judge LLMs in Competitive Programming?
Zihan Zheng, Zerui Cheng, Zeyu Shen +16
cs.SEcs.AIcs.CLarXiv:2506.11928v12025
AIOpsLab: A Holistic Framework to Evaluate AI Agents for Enabling Autonomous Clouds
Yinfang Chen, Manish Shetty, Gagan Somashekar +6
cs.AIcs.DCcs.MAarXiv:2501.06706v12025
Evaluating a 4B open-weights local LLM for agentic DFT workflows: a literature reproducibility audit
Shambhu Bhandari Sharma
cond-mat.mtrl-scics.SEarXiv:2608.29665v12026
PostTrainBench: Can LLM Agents Automate LLM Post-Training?
Ben Rank, Hardik Bhatnagar, Ameya Prabhu +4
cs.SEcs.AIcs.LGarXiv:2603.08640v22026
Write, Execute, Assess: Program Synthesis with a REPL
Kevin Ellis, Maxwell Nye, Yewen Pu +3
cs.PLcs.AIcs.LGarXiv:1906.04604v12019
Self-Edit: Fault-Aware Code Editor for Code Generation
Kechi Zhang, Zhuo Li, Jia Li +2
cs.SEcs.CLarXiv:2305.04087v52023
SWE-Debate: Competitive Multi-Agent Debate for Software Issue Resolution
Han Li, Yuling Shi, Shaoxin Lin +6
cs.SEcs.CLcs.LGarXiv:2507.23348v12025
Collaboration Challenges in Building ML-Enabled Systems: Communication, Documentation, Engineering, and Process
Nadia Nahar, Shurui Zhou, Grace Lewis +1
cs.SEcs.LGarXiv:2110.10234v42021
Towards Agentic Cloud Engineering: Graph and Loop Engineering with a Zero-Trust Agent Harness
Sagar Srinivas Sakhinana, Venkataramana Runkana
cs.SEcs.AIcs.LGarXiv:2609.00050v12026
A Survey of LLM-based Automated Program Repair: Taxonomies, Design Paradigms, and Applications
Boyang Yang, Zijian Cai, Fengling Liu +5
cs.SEarXiv:2506.23749v32025
Assistance or Disruption? Exploring and Evaluating the Design and Trade-offs of Proactive AI Programming Support
Kevin Pu, Daniel Lazaro, Ian Arawjo +4
cs.HCcs.AIcs.SEarXiv:2502.18658v42025
AgentLogs: A Dataset for Opening the Black Box of GitHub's Cloud Agent
Jonan Richards, Kosei Horikawa, Youmei Fan +2
cs.SEcs.AIarXiv:2608.29204v12026
SWE-Exp: Experience-Driven Software Issue Resolution
Silin Chen, Shaoxin Lin, Yuling Shi +8
cs.SEcs.CLcs.LGarXiv:2507.23361v22025
OpenCodeInstruct: A Large-scale Instruction Tuning Dataset for Code LLMs
Wasi Uddin Ahmad, Aleksander Ficek, Mehrzad Samadi +4
cs.SEcs.CLarXiv:2504.04030v22025
On the Effectiveness of LLM-as-a-judge for Code Generation and Summarization
Giuseppe Crupi, Rosalia Tufano, Alejandro Velasco +3
cs.SEarXiv:2507.16587v12025
VulnBot: Autonomous Penetration Testing for A Multi-Agent Collaborative Framework
He Kong, Die Hu, Jingguo Ge +3
cs.SEarXiv:2501.13411v12025
OrcaLoca: An LLM Agent Framework for Software Issue Localization
Zhongming Yu, Hejia Zhang, Yujie Zhao +4
cs.SEcs.AIarXiv:2502.00350v22025
SkillForge: Forging Domain-Specific, Self-Evolving Agent Skills in Cloud Technical Support
Xingyan Liu, Xiyue Luo, Linyu Li +3
cs.IRcs.AIcs.SEarXiv:2604.08618v22026
Fine-Tuning Large Language Models to Classify Pull Request-Issue Alignments: Going Beyond Prompting
Mustafa Yasir Altunhan, Hüseyin Özgür Kamalı, Eray Tüzün
cs.SEarXiv:2609.01087v12026
From Failed Trajectories to Reliable LLM Agents: Diagnosing and Repairing Harness Flaws
Mengzhuo Chen, Junjie Wang, Zhe Liu +3
cs.SEcs.MAarXiv:2606.06324v22026
Agentic Much? Adoption of Coding Agents on GitHub
Romain Robbes, Théo Matricon, Thomas Degueule +2
cs.SEarXiv:2601.18341v22026
Vibe Coding vs. Agentic Coding: Fundamentals and Practical Implications of Agentic AI
Ranjan Sapkota, Konstantinos I. Roumeliotis, Manoj Karkee
cs.SEcs.AIcs.CLarXiv:2505.19443v12025
SAVIOR: Towards Bug-Driven Hybrid Testing
Yaohui Chen, Peng Li, Jun Xu +5
cs.SEarXiv:1906.07327v12019
SWE-PolyBench: A multi-language benchmark for repository level evaluation of coding agents
Muhammad Shihab Rashid, Christian Bock, Yuan Zhuang +10
cs.SEarXiv:2504.08703v32025
A Survey of AIOps in the Era of Large Language Models
Lingzhe Zhang, Tong Jia, Mengxi Jia +7
cs.SEcs.CLarXiv:2507.12472v12025
Deep Learning for Source Code Modeling and Generation: Models, Applications and Challenges
Triet H. M. Le, Hao Chen, M. Ali Babar
cs.SEcs.AIcs.LGarXiv:2002.05442v12020
Empirical Software Engineering in Practice: Insights from Google
Roberto Verdecchia, Justus Bogner
cs.SEarXiv:2609.00247v12026
CUDA-Harness: Harnessing Agentic CUDA Kernel Generation and Optimization from Natural Language
Qi Fan, An Zou, Yehan Ma
cs.CLcs.AIcs.MAarXiv:2609.00058v12026
sbom-unifier: Integration Framework for Heterogeneous SBOMs
Yusuke Moriwaki, Tetsuya Kanda, Yuki Manabe +5
cs.SEarXiv:2608.30708v12026
Exploring the Potential of ChatGPT in Automated Code Refinement: An Empirical Study
Qi Guo, Junming Cao, Xiaofei Xie +4
cs.SEarXiv:2309.08221v12023
How Do AI Agents Spend Your Money? Analyzing and Predicting Token Consumption in Agentic Coding Tasks
Longju Bai, Zhemin Huang, Xingyao Wang +5
cs.CLcs.AIcs.CYarXiv:2604.22750v22026
Continuous Autonomous Refactoring: A Research Roadmap for AI-Driven Code Quality Maintenance
Xin Sun, Daniel Ståhl, Kristian Sandahl +1
cs.SEarXiv:2609.01236v12026
TOGA: A Neural Method for Test Oracle Generation
Elizabeth Dinella, Gabriel Ryan, Todd Mytkowicz +1
cs.SEarXiv:2109.09262v22021
Code-Aware Prompting: A study of Coverage Guided Test Generation in Regression Setting using LLM
Gabriel Ryan, Siddhartha Jain, Mingyue Shang +4
cs.SEcs.LGarXiv:2402.00097v22024
MCP-Atlas: A Large-Scale Benchmark for Tool-Use Competency with Real MCP Servers
Chaithanya Bandi, Razvan-Gabriel Dumitru, Ben Hertzberg +20
cs.SEcs.AIarXiv:2602.00933v32026
BugsInPy: A Database of Existing Bugs in Python Programs to Enable Controlled Testing and Debugging Studies
Ratnadira Widyasari, Sheng Qin Sim, Camellia Lok +13
cs.SEarXiv:2401.15481v12024
LeetCodeDataset: A Temporal Dataset for Robust Evaluation and Efficient Training of Code LLMs
Yunhui Xia, Wei Shen, Yan Wang +5
cs.LGcs.CLcs.SEarXiv:2504.14655v12025
ACECODER: Acing Coder RL via Automated Test-Case Synthesis
Huaye Zeng, Dongfu Jiang, Haozhe Wang +3
cs.SEcs.AIcs.CLarXiv:2502.01718v42025
A Tale of Two Cities: Software Developers Working from Home During the COVID-19 Pandemic
Denae Ford, Margaret-Anne Storey, Thomas Zimmermann +6
cs.SEcs.CYcs.HCarXiv:2008.11147v32020
Montage: a grid portal and software toolkit for science-grade astronomical image mosaicking
Joseph C. Jacob, Daniel S. Katz, G. Bruce Berriman +8
astro-ph.IMcs.DCcs.SEarXiv:1005.4454v12010

Software Engineering

NVIDIA FLARE: Federated Learning from Simulation to Real-World

Detecting DBMS Bugs by Constructing Equivalent Representations of Intermediate Query Results

Astra: A Multi-Agent System for GPU Kernel Performance Optimization

Agent Behavioral Contracts: Formal Specification and Runtime Enforcement for Reliable Autonomous AI Agents

Getting pwn'd by AI: Penetration Testing with Large Language Models

SWE-Lego: Pushing the Limits of Supervised Fine-tuning for Software Issue Resolving

Pandemic Programming: How COVID-19 affects software developers and how their organizations can help

Contrastive Code Representation Learning

Natural Language to Code Translation with Execution

Who Needs MLOps: What Data Scientists Seek to Accomplish and How Can MLOps Help?

Legacy System Modernization with Coding Agents: A Case Study

What Is a System? An Interaction-Based Account of Structure-Behavior Coalescence in General Systems Theory

FEA-Bench: A Benchmark for Evaluating Repository-Level Code Generation for Feature Implementation

ProgramBench: Can Language Models Rebuild Programs From Scratch?

In-IDE Code Generation from Natural Language: Promise and Challenges

Hints Help But Do They Teach? Evaluating Skills Transfer in Code Generation

Towards Robust Agentic CUDA Kernel Benchmarking, Verification, and Optimization

Seed-Coder: Let the Code Model Curate Data for Itself

A Critical Review of "Automatic Patch Generation Learned from Human-Written Patches": Essay on the Problem Statement and the Evaluation of Automatic Software Repair

UML Class Diagram Evaluation and Repair Strategies based on LLMs

LiveCodeBench Pro: How Do Olympiad Medalists Judge LLMs in Competitive Programming?

AIOpsLab: A Holistic Framework to Evaluate AI Agents for Enabling Autonomous Clouds

Evaluating a 4B open-weights local LLM for agentic DFT workflows: a literature reproducibility audit

PostTrainBench: Can LLM Agents Automate LLM Post-Training?

Write, Execute, Assess: Program Synthesis with a REPL

Self-Edit: Fault-Aware Code Editor for Code Generation

SWE-Debate: Competitive Multi-Agent Debate for Software Issue Resolution

Collaboration Challenges in Building ML-Enabled Systems: Communication, Documentation, Engineering, and Process

Towards Agentic Cloud Engineering: Graph and Loop Engineering with a Zero-Trust Agent Harness

A Survey of LLM-based Automated Program Repair: Taxonomies, Design Paradigms, and Applications

Assistance or Disruption? Exploring and Evaluating the Design and Trade-offs of Proactive AI Programming Support

AgentLogs: A Dataset for Opening the Black Box of GitHub's Cloud Agent

SWE-Exp: Experience-Driven Software Issue Resolution

OpenCodeInstruct: A Large-scale Instruction Tuning Dataset for Code LLMs

On the Effectiveness of LLM-as-a-judge for Code Generation and Summarization

VulnBot: Autonomous Penetration Testing for A Multi-Agent Collaborative Framework

OrcaLoca: An LLM Agent Framework for Software Issue Localization

SkillForge: Forging Domain-Specific, Self-Evolving Agent Skills in Cloud Technical Support

Fine-Tuning Large Language Models to Classify Pull Request-Issue Alignments: Going Beyond Prompting

From Failed Trajectories to Reliable LLM Agents: Diagnosing and Repairing Harness Flaws

Agentic Much? Adoption of Coding Agents on GitHub

Vibe Coding vs. Agentic Coding: Fundamentals and Practical Implications of Agentic AI

SAVIOR: Towards Bug-Driven Hybrid Testing

SWE-PolyBench: A multi-language benchmark for repository level evaluation of coding agents

A Survey of AIOps in the Era of Large Language Models

Deep Learning for Source Code Modeling and Generation: Models, Applications and Challenges

Empirical Software Engineering in Practice: Insights from Google

CUDA-Harness: Harnessing Agentic CUDA Kernel Generation and Optimization from Natural Language

sbom-unifier: Integration Framework for Heterogeneous SBOMs

Exploring the Potential of ChatGPT in Automated Code Refinement: An Empirical Study

How Do AI Agents Spend Your Money? Analyzing and Predicting Token Consumption in Agentic Coding Tasks

Continuous Autonomous Refactoring: A Research Roadmap for AI-Driven Code Quality Maintenance

TOGA: A Neural Method for Test Oracle Generation

Code-Aware Prompting: A study of Coverage Guided Test Generation in Regression Setting using LLM

MCP-Atlas: A Large-Scale Benchmark for Tool-Use Competency with Real MCP Servers

BugsInPy: A Database of Existing Bugs in Python Programs to Enable Controlled Testing and Debugging Studies

LeetCodeDataset: A Temporal Dataset for Robust Evaluation and Efficient Training of Code LLMs

ACECODER: Acing Coder RL via Automated Test-Case Synthesis

A Tale of Two Cities: Software Developers Working from Home During the COVID-19 Pandemic

Montage: a grid portal and software toolkit for science-grade astronomical image mosaicking