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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2,221 to 2,280 of 2,806

  1. Mitigating Uncertainty Interactions in GenAI-based Adaptive Systems: Vision, Challenges and Preliminary Guidelines

    Karthik Vaidhyanathan, Norha Villegas, Raffaela Mirandola +5

    cs.SEarXiv:2610.08881v12026
  2. From Monolith to Microservices: A Classification of Refactoring Approaches

    Jonas Fritzsch, Justus Bogner, Alfred Zimmermann +1

    cs.SEarXiv:1807.10059v22018
  3. PolyCodeEval: Benchmarking Multilingual Code Generation from Functions to Repositories

    Bowen Yang, Jiajun Jiang, Luxue Yu +3

    cs.SEarXiv:2610.11618v12026
  4. ParaRecover: A Process-Level Benchmark for Error Localization and Recovery in Parallel Tool-Use Agents

    Bowen Guan, Zhentao Yin, Yanming Shen

    cs.LGcs.SEarXiv:2609.12345v12026
  5. Characterizing Overconfident Failure in LLM-Based Code Generation

    Ravishka Rathnasuriya, Wei Yang

    cs.SEcs.AIarXiv:2610.11300v12026
  6. Who Pays the Review Cost? Triage, Fairness, and Accountability in AI-authored Pull Requests

    Md Shamimur Rahman, Khairul Alam, Banani Roy +1

    cs.SEarXiv:2610.11179v12026
  7. An Investigation into the Use of Common Libraries in Android Apps

    Li Li, Tegawendé F. Bissyandé, Jacques Klein +1

    cs.SEarXiv:1511.06554v12015
  8. Forms of LLM-Integrated Applications from LLM-Chats to Autonomous AI Agent System

    Irene Weber

    cs.CLcs.AIcs.SEarXiv:2610.11899v12026
  9. What Drives Recovery in Agentic Text-to-Cypher? LAST-CQ: An LLM Agent Self-Refinement Framework

    Ioannis Prokopiou, Athanasios Aidinis, Panagiotis-Christos Kyrmpatsos +1

    cs.AIcs.CLcs.LGarXiv:2609.12746v12026
  10. Evaluating Representation Learning of Code Changes for Predicting Patch Correctness in Program Repair

    Haoye Tian, Kui Liu, Abdoul Kader Kaboreé +4

    cs.SEarXiv:2008.02944v12020
  11. Confidence-Gated Transductive Test Generation for Code Reranking

    Sungjae Lee, Youngsik Yoon, Seockbean Song +3

    cs.AIcs.CLcs.SEarXiv:2609.12489v12026
  12. Cross-Provider Review as a Runtime Contract for Coding Agents: A Controlled Pilot and Fault-Injection Study

    Bowen Xu, Boyu Chen

    cs.SEcs.AIarXiv:2610.10961v12026
  13. Has LLM Screening Performance Stalled in Software Engineering Systematic Reviews?

    Aleksi Huotala, Miikka Kuutila, Mika Mäntylä

    cs.SEcs.AIarXiv:2610.10633v12026
  14. A Survey and Taxonomy of Self-Aware and Self-Adaptive Cloud Autoscaling Systems

    Tao Chen, Rami Bahsoon, Xin Yao

    cs.SEcs.DCarXiv:1609.03590v42016
  15. An Insight into the Pull Requests of GitHub

    Mohammad Masudur Rahman, Chanchal K. Roy

    cs.SEarXiv:1807.01853v12018
  16. Scan the Skill, Govern the Action: Composing Registry Verdicts with Runtime Consequence Control

    Rohit Taneja, Travis Weber

    cs.CRcs.SEarXiv:2609.12001v12026
  17. Open Source Stewardship Communities: "We need you, but not your pull request"

    Gregorio Robles, Daniel M. German

    cs.SEarXiv:2609.12236v12026
  18. Mission Performance: Automatic and Adaptive Race Pace Progression for Autonomous Racing

    Giovanni Lambertini, Matteo Pini, Nicola Musiu +3

    cs.ROcs.SEcs.SYarXiv:2609.12292v12026
  19. Missing Dimensions: Integrating Human and Social Systems into Digital Twin Engineering

    Francis Bordeleau, Mark van den Brand

    cs.SEarXiv:2609.12131v12026
  20. Investigating Developer-Reported Software Security Testing Challenges

    Md Erfan, Ahmed Ryan, Md Rayhanur Rahman

    cs.SEcs.CRarXiv:2609.12008v12026
  21. Reality Is the Final Verifier: On Two Key Gaps in Agentic Software Engineering

    Alexander Krentsel, Shubham Agarwal, Mert Cemri +5

    cs.SEcs.AIarXiv:2609.12039v12026
  22. Where Do the Tokens Go? Understanding and Reducing Costs in LLM Agents for Vulnerability Discovery

    Li Lu, Yanjie Zhao, Hongjie Chen +1

    cs.CRcs.SEarXiv:2610.11602v12026
  23. Runnable Commit Untangling for Coding Agents

    Jinfeng Jiang, Dongsun Kim, Dayi Lin +1

    cs.SEcs.AIarXiv:2610.11593v12026
  24. L2CEval: Evaluating Language-to-Code Generation Capabilities of Large Language Models

    Ansong Ni, Pengcheng Yin, Yilun Zhao +11

    cs.CLcs.LGcs.PLarXiv:2309.17446v22023
  25. REPOFUSE: Repository-Level Code Completion with Fused Dual Context

    Ming Liang, Xiaoheng Xie, Gehao Zhang +6

    cs.SEcs.AIarXiv:2402.14323v22024
  26. RepoFusion: Training Code Models to Understand Your Repository

    Disha Shrivastava, Denis Kocetkov, Harm de Vries +2

    cs.LGcs.AIcs.PLarXiv:2306.10998v12023
  27. Is Bash All You Need? An Empirical Study of Tool Interfaces for Enterprise Digital Worker Agents

    Hazel Mak, Susheel Suresh, Sahil Bhatnagar +3

    cs.SEcs.AIcs.CLarXiv:2609.11999v12026
  28. One Skill Too Many: How Co-Installed Skills Conflict in Coding Agents

    Chaoliang Yan, Zihao Xu, Yuekang Li +4

    cs.SEcs.AIarXiv:2610.11647v12026
  29. Skill Constellations: Tracing the Supply Chain of Agent Skills on GitHub

    Fahd Seddik

    cs.SEcs.CRcs.SIarXiv:2610.11169v12026
  30. GPTutor: a ChatGPT-powered programming tool for code explanation

    Eason Chen, Ray Huang, Han-Shin Chen +2

    cs.HCcs.AIcs.CLarXiv:2305.01863v22023
  31. Categorizing Bugs with Social Networks: A Case Study on Four Open Source Software Communities

    Marcelo Serrano Zanetti, Ingo Scholtes, Claudio Juan Tessone +1

    cs.SEcs.LGcs.SIarXiv:1302.6764v22013
  32. Adaptive-GEPA: Make Your Harness Fit Heterogeneous Requests

    Tianyu Chen, Yasi Zhang, Ruiyi Wang +3

    cs.SEcs.AIarXiv:2609.38762v12026
  33. Robust Failure Diagnosis of Microservice System through Multimodal Data

    Shenglin Zhang, Pengxiang Jin, Zihan Lin +10

    cs.SEarXiv:2302.10512v22023
  34. TaoD2C-Bench: Benchmarking MLLMs for Industrial UI Code Generation Beyond Visual Fidelity

    Chengwei Shi, Yunnong Chen, Tingting Zhou +5

    cs.SEcs.AIarXiv:2610.10374v12026
  35. Combining Fine-Tuning and LLM-based Agents for Intuitive Smart Contract Auditing with Justifications

    Wei Ma, Daoyuan Wu, Yuqiang Sun +5

    cs.SEarXiv:2403.16073v32024
  36. RepoGraph: Enhancing AI Software Engineering with Repository-level Code Graph

    Siru Ouyang, Wenhao Yu, Kaixin Ma +6

    cs.SEcs.AIcs.CLarXiv:2410.14684v22024
  37. When Sub-Agents Work in Parallel: The Promises and Pitfalls of Dynamic Concurrency in Long-Horizon Coding Tasks

    Han Li, HanHaoNing Li, Ziqian Jiang +1

    cs.SEarXiv:2610.10263v12026
  38. Rethinking Smart Contract Fuzzing: Fuzzing With Invocation Ordering and Important Branch Revisiting

    Zhenguang Liu, Peng Qian, Jiaxu Yang +4

    cs.CRcs.PLcs.SEarXiv:2301.03943v22023
  39. SelfAPR: Self-supervised Program Repair with Test Execution Diagnostics

    He Ye, Matias Martinez, Xiapu Luo +2

    cs.SEarXiv:2203.12755v32022
  40. Measuring the Security of the Evolving Software Supply Chain: a Research Agenda

    Sarah Meriem Ourari

    cs.CRcs.SEarXiv:2609.08810v12026
  41. Tool Retrievers Are Underestimated: Annotation Expansion Reveals True Capability

    Yanyu Zhu, Chenheng Zhang, Shaoshen Chen +8

    cs.SEcs.IRarXiv:2609.08327v12026
  42. Agent ATO: Visualizing Agent Interaction Timelines from Logs

    Takuto Kawamoto, Yoshiki Higo, Raula Gaikovina Kula

    cs.SEarXiv:2609.08301v12026
  43. HarnessSecurity-Bench: Do Security Mechanisms Really Protect Coding Agent Harnesses?

    Zhengyang Zhu, Liming Huang, Runmin Ji +8

    cs.CRcs.SEarXiv:2610.07639v12026
  44. A Case Study in Assuring AI-Written Software

    Lindsey Ferris, Sierra Bonilla

    cs.SEcs.AIcs.MAarXiv:2610.08651v12026
  45. Acquiring and Verifying Repository Norms for Coding Agents

    Kaifeng He, Xiaojun Zhang, Zhenxi Chen +2

    cs.SEarXiv:2610.07757v12026
  46. solc-verify: A Modular Verifier for Solidity Smart Contracts

    Ákos Hajdu, Dejan Jovanović

    cs.PLcs.LOcs.SEarXiv:1907.04262v22019
  47. Technical Report on the Turba Fertilizer Machine Learning Stack in Morocco

    Abdelghani Belgaid, Zakaria Mahmoud, Fahd Chibani +3

    cs.LGcs.SEarXiv:2610.05949v12026
  48. Newer and Bigger, but Safer? A Longitudinal Study of the Functionality-Security Gap in LLM-Generated Code

    Thiago Santos de Moura, Fynn Matuschek, Flavio Toffalini +1

    cs.SEcs.CRarXiv:2610.08240v12026
  49. A Surrogate-based Approach for Fast Multi-objective Architectural Refactoring Optimization

    J. Andrés Diaz-Pace, Daniele Di Pompeo, Antonela Tommasel

    cs.SEarXiv:2609.07389v12026
  50. When Stakeholder-centric Requirements Engineering is Not Enough: An Action Research Study on Legacy System Modernisation

    Ruward S. Karper, Damian A. Tamburri, Alessio Ferrari +1

    cs.SEarXiv:2609.07340v12026
  51. A First Look at Blockchain-based Decentralized Applications

    Kaidong Wu, Yun Ma, Gang Huang +1

    cs.SEarXiv:1909.00939v12019
  52. Do AI Coding Assistants Check Before They Install? A Pre-Registered Demand-Side Audit of Trust Signals in the Research Software Supply Chain

    Pengyin Shan

    cs.CRcs.AIcs.SEarXiv:2609.07754v12026
  53. Complex Agents, Shallow Tests: Demystifying and Enhancing Test Adequacy of Agent Harness in the Wild

    Yifan Xiong, Jingyi Ge, Zhenpeng Chen +1

    cs.SEcs.AIarXiv:2610.04921v12026
  54. Recompilation Is Not Enough: Test-Guided Decompiled-C Repair

    Yuhan Huang, Puzhuo Liu, Jianlei Chi

    cs.SEcs.AIarXiv:2609.07201v12026
  55. You can contribute if you... An Empirical Framework of AI Contribution Policies in OSS

    Gregorio Robles, Daniel M. German

    cs.SEarXiv:2609.07919v12026
  56. No More Translation at Runtime: LLM-Empowered Static Binary Translation

    Zhibo Liu, Huaijin Wang, Wai Kin Wong +2

    cs.OScs.SEarXiv:2610.05999v12026
  57. AI Agent Pull Requests on GitHub: Frequency, Structure, and Merge Conflict Rates

    George Xu, Arjun Subramanian, Nithilan Karthik

    cs.SEcs.AIcs.MAarXiv:2607.04697v22026
  58. From Reading Code to Reading Spec: A Verified Layer for LLM-Driven Codebase Maintenance

    Xinhao Zhang, Jingjie Lu, Kunpeng Liu +1

    cs.SEcs.CLarXiv:2609.06383v12026
  59. Can It Edit? Evaluating the Ability of Large Language Models to Follow Code Editing Instructions

    Federico Cassano, Luisa Li, Akul Sethi +8

    cs.SEcs.AIcs.LGarXiv:2312.12450v62023
  60. NaturalCodeBench: Examining Coding Performance Mismatch on HumanEval and Natural User Prompts

    Shudan Zhang, Hanlin Zhao, Xiao Liu +6

    cs.CLcs.LGcs.SEarXiv:2405.04520v12024