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MSR 2026

A

International Conference on Mining Software Repositories

Official site ↗
145
accepted papers
462
authors
April 13-14, 2026
dates
Brazil
location

145 / 145 papers

  1. 1
    A Blueprint for Trustworthy Code Annotation at Scale: An LLM-Powered Pipeline for Industrial Software Analytics
    Ailon dos Santos Teixeira
    ,
    Jaine Brito da Silva da Silva
    ,
    Nikolas Rocha da Silva de Medeiros
    ,
    Raimundo da Silva Barreto
    ,
    José Reginaldo Hughes da Silva Carvalho
    ,
    Alex Fernando da Silva Monteiro
  2. 2
    A Large-Scale Dataset of MCP Implementations on GitHub
    Benny Toeppe
    ,
    Amine Barrak
    ,
    Emna Ksontini
  3. 3
    A Match Made in Heaven? AI-driven Matching of Vulnerabilities and Security Unit Tests
    Emanuele Iannone
    ,
    Quang-Cuong Bui
    ,
    Riccardo Scandariato
  4. 4
    A Study of Library Usage in Agent-Authored Pull Requests
    Lukas Twist
    ,
    Jie M. Zhang
  5. 5
    A Study on Code Clone Lifecycles in Pull Requests Created by AI Agents
    Italo Uchoa
    ,
    Denis Sousa
    ,
    Henrique Chuvas
    ,
    Matheus Paixão
    ,
    Chaiyong Ragkhitwetsagul
    ,
    Thiago Lima Matos
  6. 6
    A Task-Level Evaluation of AI Agents in Open-Source Projects
    Shojibur Rahman
    ,
    Md. Fazle Rabbi
    ,
    Minhaz F. Zibran
  7. 7
    Adversarial Bug Reports as a Security Risk in Language Model-Based Automated Program Repair
    Piotr Przymus
    ,
    Andreas Happe
    ,
    Jürgen Cito
  8. 8
    AFGNN: API Misuse Detection using Graph Neural Networks and Clustering
    Ponnampalam Pirapuraj
    ,
    Tamal Mondal
    ,
    Sharanya Gupta
    ,
    Akash Lal
    ,
    Somak Aditya
    ,
    Jyothi Vedurada
  9. 9
    AI builds, We Analyze: An Empirical Study of AI-Generated Build Code Quality
    Anwar Ghammam
    ,
    Mohamed Almukhtar
  10. 10
    AI IDEs or Autonomous Agents? Measuring the Impact of Coding Agents on Software Development
    Shyam Agarwal
    ,
    Hao He
    ,
    Bogdan Vasilescu
  11. 11
    AIDev: Studying AI Coding Agents on GitHub
    Hao Li
    ,
    Haoxiang Zhang
    ,
    Ahmed E. Hassan
  12. 12
    An Empirical Analysis of Cross-OS Portability Issues in Python Projects
    Denini Gabriel Silva
    ,
    MohamadAli Farahat
    ,
    Marcelo d'Amorim
  13. 13
    An Empirical Analysis of Test Failures in AI-Generated Pull Requests
    Alireza Hoseinpour
    ,
    Sajjad Rezvani Boroujeni
    ,
    Jashhvanth Tamilselvan Kunthavai
    ,
    Kyle Cusimano
    ,
    Abbas Heydarnoori
  14. 14
    An Empirical Study of Code Clone Genealogies in Human-AI Collaborative Development
    Denis Sousa
    ,
    Italo Uchoa
    ,
    Matheus Paixão
    ,
    Chaiyong Ragkhitwetsagul
    ,
    Thiago Lima Matos
  15. 15
    An Empirical Study of Policy as Code: Adoption, Purpose, and Maintenance
    Ruben Opdebeeck
    ,
    Mahmoud Alfadel
    ,
    Akond Rahman
    ,
    Yutaro Kashiwa
    ,
    João F. Ferreira
    ,
    Raula Gaikovina Kula
    ,
    Coen De Roover
  16. 16
    An Empirical Study of Tests in Agentic Pull Requests
    Sabrina Haque
    ,
    Sarvesh Ingale
    ,
    Christoph Csallner
  17. 17
    An Empirical Study of Vulnerabilities in Python Packages and Their Detection
    Haowei Quan
    ,
    Junjie Wang
    ,
    Xinzhe Li
    ,
    Terry Yue Zhuo
    ,
    Xiao Chen
    ,
    Xiaoning Du
  18. 18
    An Empirical Study on Deep Learning-based Line-Level Software Defect Prediction
    Enci Zhang
    ,
    Yutong Jiang
    ,
    Tianmeng Zhang
    ,
    Haonan Tong
  19. 19
    Analyzing Dependency Distribution Changes Arising from Code Smell Interactions
    Zushuai Zhang
    ,
    Elliott Wen
    ,
    Ewan D. Tempero
  20. 20
    Analyzing GitHub Issues and Pull Requests in nf-core Pipelines: Insights into nf-core Pipeline Repositories
    Khairul Alam
    ,
    Banani Roy
  21. 21
    Analyzing Message-Code Inconsistency in AI Coding Agent-Authored Pull Requests
    Jingzhi Gong
    ,
    Giovanni Pinna
    ,
    Yixin Bian
    ,
    Jie M. Zhang
  22. 22
    AndroMetric: Bridging Multi-Dimensional Software Metrics and Mobile Application Security
    Sebastian Siedler
    ,
    Karim Elish
  23. 23
    AndroT: A Dataset of Android Apps with Tests
    Hovhannes Muradyan
    ,
    Mattia Fazzini
  24. 24
    AnoMod: A Dataset for Anomaly Detection and Root Cause Analysis in Microservice System
    Ke Ping
    ,
    Hamza Bin Mazhar
    ,
    Yuqing Wang
    ,
    Ying Song
    ,
    Mika V. Mäntylä
  25. 25
    Are Coding Agents Generating Over-Mocked Tests? An Empirical Study
    Andre Hora
    ,
    Romain Robbes
  26. 26
    Are We All Using Agents the Same Way? An Empirical Study of Core and Peripheral Developers' Use of Coding Agents
    Shamse Tasnim Cynthia
    ,
    Joy Krishan Das
    ,
    Banani Roy
  27. 27
    Assessing Task-based Chatbots: Snapshot and Curated Datasets for Dialogflow
    Elena Masserini
    ,
    Diego Clerissi
    ,
    Daniela Micucci
    ,
    Leonardo Mariani
  28. 28
    Behavioral Analysis of AI Code Generation Agents: Edit, Rewrite, and Repetition
    Mahdieh Abazar
    ,
    Reyhaneh Farahmand
    ,
    Gouri Ginde
    ,
    Benjamin Tan
    ,
    Lorenzo De Carli
  29. 29
    Behind Agentic Pull Requests: An Empirical Study on Developer Interventions in AI Agent-Authored Pull Requests
    Syrine Khelifi
    ,
    Ali Ouni
    ,
    Maha Khemaja
  30. 30
    Beyond Bug Fixes: An Empirical Investigation of Post-Merge Code Quality Issues in Agent-Generated Pull Requests
    Shamse Tasnim Cynthia
    ,
    Al Muttakin
    ,
    Banani Roy
  31. 31
    Beyond Single Code Changes: An Empirical Study of Topic-Based Code Review Practices in Gerrit for OpenStack
    Moataz Chouchen
    ,
    Mahi Begoug
    ,
    Ali Ouni
  32. 32
    Beyond the Prompt: An Empirical Study of Cursor Rules
    Shaokang Jiang
    ,
    Daye Nam
  33. 33
    Bridging Design and Implementation: A Study of Multi-Agent LLM Architectures for Automated Front-End Generation
    Caren Rizk
    ,
    SayedHassan Khatoonabadi
    ,
    Emad Shihab
  34. 34
    Bug-Fixing in the Age of AI: Human vs. Agentic Pull Requests
    Renato Domingues
    ,
    Fernando Castor
    ,
    Fernanda Madeiral
  35. 35
    Can Data Mining Help to Survive the Annual Compiler Upgrade?
    Gunnar Kudrjavets
    ,
    Aditya Kumar
    ,
    Piotr Przymus
  36. 36
    Characterizing and Modeling the GitHub Security Advisories Review Pipeline
    Claudio Marcos Durand Segal
    ,
    Paulo Marcos Durand Segal
    ,
    Carlos Eduardo De Schuller Banjar
    ,
    Felipe de Sant'Anna Paixão
    ,
    Hudson Borges
    ,
    Paulo Anselmo da Mota Silveira Neto
    ,
    Eduardo Santana de Almeida
    ,
    Joanna C. S. Santos
    ,
    Anton Kocheturov
    ,
    Gaurav Kumar Srivastava
    ,
    Daniel Sadoc Menasché
  37. 37
    Characterizing Self-Admitted Technical Debt Generated by AI Coding Agents
    Zaki Brahmi
    ,
    Ali Ouni
    ,
    Mohammed Sayagh
    ,
    Mohamed Aymen Saied
  38. 38
    Code Change Characteristics and Description Alignment: A Comparative Study of Agentic versus Human Pull Requests
    Dung Pham
    ,
    Taher Ahmed Ghaleb
  39. 39
    Combining Example-Based and Rule-Based Program Transformations to Resolve Build Conflicts
    Sheikh Shadab Towqir
    ,
    Fei He
    ,
    Todd Mytkowicz
    ,
    Na Meng
  40. 40
    Comparing AI Coding Agents: A Task-Stratified Analysis of Pull Request Acceptance
    Giovanni Pinna
    ,
    Jingzhi Gong
    ,
    David Williams
    ,
    Federica Sarro
  41. 41
    Consistent or Sensitive? Automated Code Revision Tools Against Semantics-Preserving Perturbations
    Shirin Pirouzkhah
    ,
    Souhaila Serbout
    ,
    Alberto Bacchelli
  42. 42
    Context Engineering for AI Agents in Open-Source Software
    Seyedmoein Mohsenimofidi
    ,
    Matthias Galster
    ,
    Christoph Treude
    ,
    Sebastian Baltes
  43. 43
    Coordination at Scale in Large Distributed Development: The Case of Kubernetes
    Sabrina Aufiero
    ,
    Matteo Vaccargiu
    ,
    Silvia Bartolucci
    ,
    Fabio Caccioli
    ,
    Giuseppe Destefanis
  44. 44
    DBSecQA: A Curated Dataset of Developer Discussions on Database Security from Stack Exchange
    Md. Rakibul Islam
    ,
    Farha Kamal
    ,
    Md Humaun Kabir
    ,
    Md Murad Sharif
  45. 45
    Do AI Agents Really Improve Code Readability?
    Kyogo Horikawa
    ,
    Kosei Horikawa
    ,
    Yutaro Kashiwa
    ,
    Hidetake Uwano
    ,
    Hajimu Iida
  46. 46
    Do AI-Generated Pull Requests Get Rejected More? (Yes but Why?)
    Yiru Wang
    ,
    Zhou Yang
  47. 47
    Do We Agree on What an "Audit" Is? Toward Standardized Smart Contract Audit Reporting
    Ilham A. Qasse
    ,
    Mohammad Hamdaqa
    ,
    Gísli Hjálmtýsson
  48. 48
    Does Programming Language Matter? An Empirical Study of Fuzzing Bug Detection
    Tatsuya Shirai
    ,
    Olivier Nourry
    ,
    Yutaro Kashiwa
    ,
    Kenji Fujiwara
    ,
    Hajimu Iida
  49. 49
    Early-Stage Prediction of Review Effort in AI-Generated Pull Requests
    Dao Sy Duy Minh
    ,
    Huynh Trung Kiet
    ,
    Nguyen Lam Phu Quy
    ,
    Pham Phu Hoa
    ,
    Tran Chi Nguyen
    ,
    Nguyen Dinh Ha Duong
    ,
    Truong Bao Tran
  50. 50
    Evaluating the Use of LLMs for Automated DOM-Level Resolution of Web Performance Issues
    Gideon Peters
    ,
    SayedHassan Khatoonabadi
    ,
    Emad Shihab