Real Faults in Model Context Protocol (MCP) Software: a Comprehensive Taxonomy
Fuente:
arXiv
Saved in:
| Main Authors: | Taraghi, Mina, Morovati, Mohammad Mehdi, Khomh, Foutse |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Common Challenges of Deep Reinforcement Learning Applications Development: An Empirical Study
by: Morovati, Mohammad Mehdi, et al.
Published: (2023)
by: Morovati, Mohammad Mehdi, et al.
Published: (2023)
Fault Localization in Deep Learning-based Software: A System-level Approach
by: Morovati, Mohammad Mehdi, et al.
Published: (2024)
by: Morovati, Mohammad Mehdi, et al.
Published: (2024)
Characterizing Faults in Agentic AI: A Taxonomy of Types, Symptoms, and Root Causes
by: Shah, Mehil B, et al.
Published: (2026)
by: Shah, Mehil B, et al.
Published: (2026)
Deep Learning Model Reuse in the HuggingFace Community: Challenges, Benefit and Trends
by: Taraghi, Mina, et al.
Published: (2024)
by: Taraghi, Mina, et al.
Published: (2024)
Towards Understanding the Impact of Data Bugs on Deep Learning Models in Software Engineering
by: Shah, Mehil B, et al.
Published: (2024)
by: Shah, Mehil B, et al.
Published: (2024)
Protecting Privacy in Software Logs: What Should Be Anonymized?
by: Aghili, Roozbeh, et al.
Published: (2024)
by: Aghili, Roozbeh, et al.
Published: (2024)
A Taxonomy of Inefficiencies in LLM-Generated Python Code
by: Abbassi, Altaf Allah, et al.
Published: (2025)
by: Abbassi, Altaf Allah, et al.
Published: (2025)
Mock Deep Testing: Toward Separate Development of Data and Models for Deep Learning
by: Manke, Ruchira, et al.
Published: (2025)
by: Manke, Ruchira, et al.
Published: (2025)
RefAgent: A Multi-agent LLM-based Framework for Automatic Software Refactoring
by: Oueslati, Khouloud, et al.
Published: (2025)
by: Oueslati, Khouloud, et al.
Published: (2025)
An Empirical Study of Self-Admitted Technical Debt in Machine Learning Software
by: Bhatia, Aaditya, et al.
Published: (2023)
by: Bhatia, Aaditya, et al.
Published: (2023)
PathOCL: Path-Based Prompt Augmentation for OCL Generation with GPT-4
by: Abukhalaf, Seif, et al.
Published: (2024)
by: Abukhalaf, Seif, et al.
Published: (2024)
Leveraging Data Characteristics for Bug Localization in Deep Learning Programs
by: Manke, Ruchira, et al.
Published: (2024)
by: Manke, Ruchira, et al.
Published: (2024)
An Empirical Study of Policy-as-Code Adoption in Open-Source Software Projects
by: Foalem, Patrick Loic, et al.
Published: (2026)
by: Foalem, Patrick Loic, et al.
Published: (2026)
SDLog: A Deep Learning Framework for Detecting Sensitive Information in Software Logs
by: Aghili, Roozbeh, et al.
Published: (2025)
by: Aghili, Roozbeh, et al.
Published: (2025)
Adversarial Attack Classification and Robustness Testing for Large Language Models for Code
by: Liu, Yang, et al.
Published: (2025)
by: Liu, Yang, et al.
Published: (2025)
Trained Without My Consent: Detecting Code Inclusion In Language Models Trained on Code
by: Majdinasab, Vahid, et al.
Published: (2024)
by: Majdinasab, Vahid, et al.
Published: (2024)
A Taxonomy of Real Faults in Hybrid Quantum-Classical Architectures
by: Bensoussan, Avner, et al.
Published: (2025)
by: Bensoussan, Avner, et al.
Published: (2025)
Towards Enhancing the Reproducibility of Deep Learning Bugs: An Empirical Study
by: Shah, Mehil B., et al.
Published: (2024)
by: Shah, Mehil B., et al.
Published: (2024)
Tracing Optimization for Performance Modeling and Regression Detection
by: Shahedi, Kaveh, et al.
Published: (2024)
by: Shahedi, Kaveh, et al.
Published: (2024)
Model Context Protocol (MCP) at First Glance: Studying the Security and Maintainability of MCP Servers
by: Hasan, Mohammed Mehedi, et al.
Published: (2025)
by: Hasan, Mohammed Mehedi, et al.
Published: (2025)
On the Effectiveness of Log Representation for Log-based Anomaly Detection
by: Wu, Xingfang, et al.
Published: (2023)
by: Wu, Xingfang, et al.
Published: (2023)
GIST: Generated Inputs Sets Transferability in Deep Learning
by: Tambon, Florian, et al.
Published: (2023)
by: Tambon, Florian, et al.
Published: (2023)
Dynasto: Validity-Aware Dynamic-Static Parameter Optimization for Autonomous Driving Testing
by: Humeniuk, Dmytro, et al.
Published: (2026)
by: Humeniuk, Dmytro, et al.
Published: (2026)
Understanding Web Application Workloads and Their Applications: Systematic Literature Review and Characterization
by: Aghili, Roozbeh, et al.
Published: (2024)
by: Aghili, Roozbeh, et al.
Published: (2024)
Reputation Gaming in Stack Overflow
by: Mazloomzadeh, Iren, et al.
Published: (2021)
by: Mazloomzadeh, Iren, et al.
Published: (2021)
Evaluating and Enhancing Segmentation Model Robustness with Metamorphic Testing
by: Mzoughi, Seif, et al.
Published: (2025)
by: Mzoughi, Seif, et al.
Published: (2025)
Exploring Security Practices in Infrastructure as Code: An Empirical Study
by: Verdet, Alexandre, et al.
Published: (2023)
by: Verdet, Alexandre, et al.
Published: (2023)
BloomAPR: A Bloom's Taxonomy-based Framework for Assessing the Capabilities of LLM-Powered APR Solutions
by: Ma, Yinghang, et al.
Published: (2025)
by: Ma, Yinghang, et al.
Published: (2025)
An Efficient Model Maintenance Approach for MLOps
by: Majidi, Forough, et al.
Published: (2024)
by: Majidi, Forough, et al.
Published: (2024)
On Fixing Insecure AI-Generated Code through Model Fine-Tuning and Prompting Strategies
by: Jahromi, Ali Soltanian Fard, et al.
Published: (2026)
by: Jahromi, Ali Soltanian Fard, et al.
Published: (2026)
Beyond the Protocol: Unveiling Attack Vectors in the Model Context Protocol (MCP) Ecosystem
by: Song, Hao, et al.
Published: (2025)
by: Song, Hao, et al.
Published: (2025)
Improving the Robustness of Large Language Models for Code Tasks via Fine-tuning with Perturbed Data
by: Liu, Yang, et al.
Published: (2026)
by: Liu, Yang, et al.
Published: (2026)
Machine Learning Robustness: A Primer
by: Braiek, Houssem Ben, et al.
Published: (2024)
by: Braiek, Houssem Ben, et al.
Published: (2024)
Mitigating False Positives in Static Memory Safety Analysis of Rust Programs via Reinforcement Learning
by: P, Akilesh, et al.
Published: (2026)
by: P, Akilesh, et al.
Published: (2026)
Performance Smells in ML and Non-ML Python Projects: A Comparative Study
by: Belias, François, et al.
Published: (2025)
by: Belias, François, et al.
Published: (2025)
Imitation Game: Reproducing Deep Learning Bugs Leveraging an Intelligent Agent
by: Shah, Mehil B, et al.
Published: (2025)
by: Shah, Mehil B, et al.
Published: (2025)
A Context-Driven Approach for Co-Auditing Smart Contracts with The Support of GPT-4 code interpreter
by: Bouafif, Mohamed Salah, et al.
Published: (2024)
by: Bouafif, Mohamed Salah, et al.
Published: (2024)
LLMs and Stack Overflow Discussions: Reliability, Impact, and Challenges
by: Da Silva, Leuson, et al.
Published: (2024)
by: Da Silva, Leuson, et al.
Published: (2024)
What Information Contributes to Log-based Anomaly Detection? Insights from a Configurable Transformer-Based Approach
by: Wu, Xingfang, et al.
Published: (2024)
by: Wu, Xingfang, et al.
Published: (2024)
Structural Anchors and Reasoning Fragility:Understanding CoT Robustness in LLM4Code
by: Liu, Yang, et al.
Published: (2026)
by: Liu, Yang, et al.
Published: (2026)
Similar Items
-
Common Challenges of Deep Reinforcement Learning Applications Development: An Empirical Study
by: Morovati, Mohammad Mehdi, et al.
Published: (2023) -
Fault Localization in Deep Learning-based Software: A System-level Approach
by: Morovati, Mohammad Mehdi, et al.
Published: (2024) -
Characterizing Faults in Agentic AI: A Taxonomy of Types, Symptoms, and Root Causes
by: Shah, Mehil B, et al.
Published: (2026) -
Deep Learning Model Reuse in the HuggingFace Community: Challenges, Benefit and Trends
by: Taraghi, Mina, et al.
Published: (2024) -
Towards Understanding the Impact of Data Bugs on Deep Learning Models in Software Engineering
by: Shah, Mehil B, et al.
Published: (2024)