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Foutse Khomh

Identifiers

  • name variant Foutse Khomh 0.60 · backfill

Papers (156)

  1. Game-Theoretic Multi-Agent Control for Robust Contextual Reasoning in LLMs cs.CR · 2026 · author #5
  2. Hallucination Cascade: Analyzing Error Propagation in Multi-Agent LLM Systems cs.CR · 2026 · author #4
  3. An Empirical Study on Logging Evolution On Stack Overflow: Trends, Topics, and Challenges cs.SE · 2026 · author #3
  4. A Research Agenda on Agents and Software Engineering: Outcomes from the Rio A2SE Seminar cs.SE · 2026 · author #12
  5. On Fixing Insecure AI-Generated Code through Model Fine-Tuning and Prompting Strategies cs.SE · 2026 · author #4
  6. Mitigating False Positives in Static Memory Safety Analysis of Rust Programs via Reinforcement Learning cs.SE · 2026 · author #3
  7. Self-Adaptive Multi-Agent LLM-Based Security Pattern Selection for IoT Systems cs.CR · 2026 · author #2
  8. Structural Anchors and Reasoning Fragility:Understanding CoT Robustness in LLM4Code cs.SE · 2026 · author #5
  9. Multi-Agent LLM Governance for Safe Two-Timescale Reinforcement Learning in SDN-IoT Defense cs.CR · 2026 · author #3
  10. QUARE: Quality-Aware Requirements Analysis through Multi-Agent Dialectical Negotiation cs.SE · 2026 · author #3
  11. Characterizing Faults in Agentic AI: A Taxonomy of Types, Symptoms, and Root Causes cs.SE · 2026 · author #4
  12. Securing Time Integrity in Energy IoT Against Clock Drift and Y2K38 Failures cs.LG · 2026 · author #4
  13. Verifiable Manifest Signing and Transparency Enforcement for Secure MCP-Based LLM Pipelines cs.CR · 2026 · author #4
  14. Semantic Attacks on Tool-Augmented LLMs: Securing the Model Context Protocol Against Descriptor-Level Manipulation cs.CR · 2025 · author #4
  15. Carbon-Aware Intrusion Detection: A Comparative Study of Supervised and Unsupervised DRL for Sustainable IoT Edge Gateways cs.CR · 2025 · author #2
  16. Logging Requirement for Continuous Auditing of Responsible Machine Learning-based Applications cs.SE · 2025 · author #3
  17. FairFLRep: Fairness aware fault localization and repair of Deep Neural Networks cs.LG · 2025 · author #3
  18. An Empirical Study on Method-Level Performance Evolution in Open-Source Java Projects cs.SE · 2025 · author #5
  19. From Technical Excellence to Practical Adoption: Lessons Learned Building an ML-Enhanced Trace Analysis Tool cs.SE · 2025 · author #5
  20. ReCatcher: Towards LLMs Regression Testing for Code Generation cs.SE · 2025 · author #4
  21. Adversarial Attack Classification and Robustness Testing for Large Language Models for Code cs.SE · 2025 · author #3
  22. SDLog: A Deep Learning Framework for Detecting Sensitive Information in Software Logs cs.SE · 2025 · author #3
  23. Performance Smells in ML and Non-ML Python Projects: A Comparative Study cs.SE · 2025 · author #3
  24. Application of Deep Reinforcement Learning for Intrusion Detection in Internet of Things: A Systematic Review cs.CR · 2025 · author #4
  25. Evaluating Machine Learning-Driven Intrusion Detection Systems in IoT: Performance and Energy Consumption cs.NI · 2025 · author #4
  26. Leveraging Machine Learning Techniques in Intrusion Detection Systems for Internet of Things cs.CR · 2025 · author #4
  27. Prism: Dynamic and Flexible Benchmarking of LLMs Code Generation with Monte Carlo Tree Search cs.AI · 2025 · author #3
  28. Evaluating and Enhancing Segmentation Model Robustness with Metamorphic Testing cs.CV · 2025 · author #3
  29. Towards Assessing Deep Learning Test Input Generators cs.LG · 2025 · author #4
  30. Representation Improvement in Latent Space for Search-Based Testing of Autonomous Robotic Systems cs.NE · 2025 · author #2
  31. MMLU-ProX: A Multilingual Benchmark for Advanced Large Language Model Evaluation cs.CL · 2025 · author #21
  32. A Taxonomy of Inefficiencies in LLM-Generated Python Code cs.SE · 2025 · author #4
  33. AILuminate: Introducing v1.0 of the AI Risk and Reliability Benchmark from MLCommons cs.CY · 2025 · author #75
  34. Mock Deep Testing: Toward Separate Development of Data and Models for Deep Learning cs.SE · 2025 · author #3
  35. Continuously Learning Bug Locations cs.SE · 2024 · author #4
  36. Leveraging Data Characteristics for Bug Localization in Deep Learning Programs cs.SE · 2024 · author #3
  37. An Efficient Model Maintenance Approach for MLOps cs.SE · 2024 · author #2
  38. Tracing Optimization for Performance Modeling and Regression Detection cs.SE · 2024 · author #4
  39. Towards Understanding the Impact of Data Bugs on Deep Learning Models in Software Engineering cs.SE · 2024 · author #3
  40. Fault Localization in Deep Learning-based Software: A System-level Approach cs.SE · 2024 · author #3
  41. Impact of LLM-based Review Comment Generation in Practice: A Mixed Open-/Closed-source User Study cs.SE · 2024 · author #8
  42. Towards Optimizing SQL Generation via LLM Routing cs.DB · 2024 · author #3
  43. In-Simulation Testing of Deep Learning Vision Models in Autonomous Robotic Manipulators cs.RO · 2024 · author #4
  44. Toward Debugging Deep Reinforcement Learning Programs with RLExplorer cs.SE · 2024 · author #7
  45. What Information Contributes to Log-based Anomaly Detection? Insights from a Configurable Transformer-Based Approach cs.SE · 2024 · author #3
  46. Understanding Web Application Workloads and Their Applications: Systematic Literature Review and Characterization cs.SE · 2024 · author #4
  47. Protecting Privacy in Software Logs: What Should Be Anonymized? cs.SE · 2024 · author #3
  48. Trimming the Risk: Towards Reliable Continuous Training for Deep Learning Inspection Systems cs.LG · 2024 · author #3
  49. DeepCodeProbe: Towards Understanding What Models Trained on Code Learn cs.SE · 2024 · author #3
  50. Chain of Targeted Verification Questions to Improve the Reliability of Code Generated by LLMs cs.SE · 2024 · author #4
  51. Mining Action Rules for Defect Reduction Planning cs.SE · 2024 · author #4
  52. PathOCL: Path-Based Prompt Augmentation for OCL Generation with GPT-4 cs.SE · 2024 · author #3
  53. Introducing v0.5 of the AI Safety Benchmark from MLCommons cs.CL · 2024 · author #40
  54. Machine Learning Robustness: A Primer cs.LG · 2024 · author #2
  55. Bugs in Large Language Models Generated Code: An Empirical Study cs.SE · 2024 · author #4
  56. Trained Without My Consent: Detecting Code Inclusion In Language Models Trained on Code cs.SE · 2024 · author #3
  57. LLMs and Stack Overflow Discussions: Reliability, Impact, and Challenges cs.SE · 2024 · author #3
  58. Deep Learning Model Reuse in the HuggingFace Community: Challenges, Benefit and Trends cs.SE · 2024 · author #5
  59. Towards Enhancing the Reproducibility of Deep Learning Bugs: An Empirical Study cs.SE · 2024 · author #3
  60. Harnessing Pre-trained Generalist Agents for Software Engineering Tasks cs.SE · 2023 · author #3
  61. Refining GPT-3 Embeddings with a Siamese Structure for Technical Post Duplicate Detection cs.SE · 2023 · author #5
  62. Characterizing and Classifying Developer Forum Posts with their Intentions cs.SE · 2023 · author #4
  63. An empirical study of testing machine learning in the wild cs.SE · 2023 · author #2
  64. Assessing the Security of GitHub Copilot Generated Code -- A Targeted Replication Study cs.SE · 2023 · author #6
  65. GIST: Generated Inputs Sets Transferability in Deep Learning cs.LG · 2023 · author #2
  66. Detection and Evaluation of bias-inducing Features in Machine learning cs.LG · 2023 · author #3
  67. Common Challenges of Deep Reinforcement Learning Applications Development: An Empirical Study cs.SE · 2023 · author #5
  68. A Large-Scale Exploratory Study of Android Sports Apps in the Google Play Store cs.SE · 2023 · author #3
  69. Data Cleaning and Machine Learning: A Systematic Literature Review cs.LG · 2023 · author #5
  70. Effective Test Generation Using Pre-trained Large Language Models and Mutation Testing cs.SE · 2023 · author #4
  71. Reinforcement Learning Informed Evolutionary Search for Autonomous Systems Testing cs.RO · 2023 · author #2
  72. An Intentional Forgetting-Driven Self-Healing Method For Deep Reinforcement Learning Systems cs.LG · 2023 · author #4
  73. Deploying Deep Reinforcement Learning Systems: A Taxonomy of Challenges cs.LG · 2023 · author #5
  74. On the Effectiveness of Log Representation for Log-based Anomaly Detection cs.SE · 2023 · author #3
  75. Exploring Security Practices in Infrastructure as Code: An Empirical Study cs.CR · 2023 · author #4
  76. Bug Characterization in Machine Learning-based Systems cs.SE · 2023 · author #4
  77. An Empirical Study on Bugs Inside PyTorch: A Replication Study cs.SE · 2023 · author #6
  78. Quality Issues in Machine Learning Software Systems cs.SE · 2023 · author #6
  79. Responsible Design Patterns for Machine Learning Pipelines cs.SE · 2023 · author #3
  80. Leveraging Data Mining Algorithms to Recommend Source Code Changes cs.SE · 2023 · author #6
  81. On Codex Prompt Engineering for OCL Generation: An Empirical Study cs.SE · 2023 · author #3
  82. Mutation Testing of Deep Reinforcement Learning Based on Real Faults cs.LG · 2023 · author #4
  83. Studying Logging Practice in Machine Learning-based Applications cs.SE · 2023 · author #2
  84. AmbieGen: A Search-based Framework for Autonomous Systems Testing cs.RO · 2023 · author #2
  85. Studying the Characteristics of AIOps Projects on GitHub cs.SE · 2022 · author #3
  86. Can Ensembling Pre-processing Algorithms Lead to Better Machine Learning Fairness? cs.LG · 2022 · author #8
  87. An Empirical Study of Library Usage and Dependency in Deep Learning Frameworks cs.SE · 2022 · author #4
  88. Reliable Malware Analysis and Detection using Topology Data Analysis cs.CR · 2022 · author #2
  89. SmOOD: Smoothness-based Out-of-Distribution Detection Approach for Surrogate Neural Networks in Aircraft Design cs.LG · 2022 · author #3
  90. Physics-Guided Adversarial Machine Learning for Aircraft Systems Simulation cs.LG · 2022 · author #3
  91. An Empirical Study on the Usage of Automated Machine Learning Tools cs.SE · 2022 · author #3
  92. A Comparison of Reinforcement Learning Frameworks for Software Testing Tasks cs.SE · 2022 · author #3
  93. Quality issues in Machine Learning Software Systems cs.SE · 2022 · author #4
  94. Data-access performance anti-patterns in data-intensive systems cs.SE · 2022 · author #3
  95. A Probabilistic Framework for Mutation Testing in Deep Neural Networks cs.SE · 2022 · author #2
  96. DiverGet: A Search-Based Software Testing Approach for Deep Neural Network Quantization Assessment cs.LG · 2022 · author #3
  97. Dev2vec: Representing Domain Expertise of Developers in an Embedding Space cs.SE · 2022 · author #3
  98. Threat Assessment in Machine Learning based Systems cs.CR · 2022 · author #2
  99. GitHub Copilot AI pair programmer: Asset or Liability? cs.SE · 2022 · author #4
  100. An Empirical Study of Challenges in Converting Deep Learning Models cs.LG · 2022 · author #4
  101. Bugs in Machine Learning-based Systems: A Faultload Benchmark cs.SE · 2022 · author #3
  102. Never trust, always verify : a roadmap for Trustworthy AI? cs.AI · 2022 · author #2
  103. Studying the Practices of Deploying Machine Learning Projects on Docker cs.SE · 2022 · author #3
  104. Technical Debts and Faults in Open-source Quantum Software Systems: An Empirical Study cs.SE · 2022 · author #4
  105. Fool SHAP with Stealthily Biased Sampling cs.LG · 2022 · author #5
  106. The Different Faces of AI Ethics Across the World: A Principle-Implementation Gap Analysis cs.CY · 2022 · author #2
  107. Understanding Quantum Software Engineering Challenges An Empirical Study on Stack Exchange Forums and GitHub Issues cs.SE · 2022 · author #3
  108. Bug Characteristics in Quantum Software Ecosystem cs.SE · 2022 · author #3
  109. Testing Feedforward Neural Networks Training Programs cs.SE · 2022 · author #2
  110. A Search-Based Framework for Automatic Generation of Testing Environments for Cyber-Physical Systems cs.NE · 2022 · author #2
  111. Do Developers Refactor Data Access Code? An Empirical Study cs.SE · 2022 · author #2
  112. On the Prevalence, Impact, and Evolution of SQL Code Smells in Data-Intensive Systems cs.SE · 2022 · author #5
  113. FIXME: Synchronize with Database An Empirical Study of Data Access Self-Admitted Technical Debt cs.SE · 2022 · author #4
  114. Machine Learning Application Development: Practitioners' Insights cs.SE · 2021 · author #2
  115. Silent Bugs in Deep Learning Frameworks: An Empirical Study of Keras and TensorFlow cs.SE · 2021 · author #4
  116. On Assessing The Safety of Reinforcement Learning algorithms Using Formal Methods cs.LG · 2021 · author #3
  117. An Empirical Study of the Effectiveness of an Ensemble of Stand-alone Sentiment Detection Tools for Software Engineering Datasets cs.SE · 2021 · author #3
  118. Partial Order in Chaos: Consensus on Feature Attributions in the Rashomon Set cs.LG · 2021 · author #4
  119. The challenge of reproducible ML: an empirical study on the impact of bugs cs.SE · 2021 · author #2
  120. Failure Analysis of Hadoop Schedulers using an Integration of Model Checking and Simulation cs.SE · 2021 · author #2
  121. The Forgotten Role of Search Queries in IR-based Bug Localization: An Empirical Study cs.SE · 2021 · author #2
  122. Why are Some Bugs Non-Reproducible? An Empirical Investigation using Data Fusion cs.SE · 2021 · author #2
  123. Improved Retrieval of Programming Solutions With Code Examples Using a Multi-featured Score cs.SE · 2021 · author #5
  124. Clones in Deep Learning Code: What, Where, and Why? cs.SE · 2021 · author #3
  125. Models of Computational Profiles to Study the Likelihood of DNN Metamorphic Test Cases cs.LG · 2021 · author #3
  126. How to Certify Machine Learning Based Safety-critical Systems? A Systematic Literature Review cs.LG · 2021 · author #7
  127. HOMRS: High Order Metamorphic Relations Selector for Deep Neural Networks cs.LG · 2021 · author #3
  128. Design Smells in Deep Learning Programs: An Empirical Study cs.SE · 2021 · author #2
  129. Automatic Fault Detection for Deep Learning Programs Using Graph Transformations cs.SE · 2021 · author #4
  130. Investigating Design Anti-pattern and Design Pattern Mutations and Their Change- and Fault-proneness cs.SE · 2021 · author #3
  131. Data Driven Testing of Cyber Physical Systems cs.CR · 2021 · author #3
  132. Mining API Usage Scenarios from Stack Overflow cs.SE · 2021 · author #2
  133. Automatic API Usage Scenario Documentation from Technical Q&A Sites cs.SE · 2021 · author #2
  134. Understanding How and Why Developers Seek and Analyze API-related Opinions cs.SE · 2021 · author #4
  135. Faults in Deep Reinforcement Learning Programs: A Taxonomy and A Detection Approach cs.SE · 2021 · author #3
  136. Are Multi-language Design Smells Fault-prone? An Empirical Study cs.SE · 2020 · author #4
  137. A Large Scale Empirical Study of the Impact of Spaghetti Code and Blob Anti-patterns on Program Comprehension cs.SE · 2020 · author #2
  138. SIGMA : Strengthening IDS with GAN and Metaheuristics Attacks cs.CR · 2019 · author #3
  139. Deep Learning Anti-patterns from Code Metrics History cs.SE · 2019 · author #2
  140. Studying Software Engineering Patterns for Designing Machine Learning Systems cs.SE · 2019 · author #3
  141. An Empirical Study of C++ Vulnerabilities in Crowd-Sourced Code Examples cs.SE · 2019 · author #4
  142. DeepEvolution: A Search-Based Testing Approach for Deep Neural Networks cs.LG · 2019 · author #2 as printed: Foutse khomh
  143. TFCheck : A TensorFlow Library for Detecting Training Issues in Neural Network Programs cs.LG · 2019 · author #2
  144. Machine Learning Software Engineering in Practice: An Industrial Case Study cs.SE · 2019 · author #3
  145. Swarm Debugging: the Collective Intelligence on Interactive Debugging cs.SE · 2019 · author #5
  146. A Machine-learning Based Ensemble Method For Anti-patterns Detection cs.SE · 2019 · author #2
  147. On Testing Machine Learning Programs cs.SE · 2018 · author #2
  148. RePOR: Mimicking humans on refactoring tasks. Are we there yet? cs.SE · 2018 · author #2
  149. Is Fragmentation a Threat to the Success of the Internet of Things? cs.NI · 2018 · author #2
  150. Is It Safe to Uplift This Patch? An Empirical Study on Mozilla Firefox cs.SE · 2017 · author #3
  151. An App Performance Optimization Advisor for Mobile Device App Marketplaces cs.CY · 2017 · author #2
  152. Stack Overflow: A Code Laundering Platform? cs.SE · 2017 · author #3
  153. Comprehension of Ads-supported and Paid Android Applications: Are They Different? cs.SE · 2017 · author #2
  154. Anti-patterns and the energy efficiency of Android applications cs.SE · 2016 · author #3
  155. ATLAS: An Adaptive Failure-aware Scheduler for Hadoop cs.DC · 2015 · author #2
  156. Predicting Scheduling Failures in the Cloud cs.DC · 2015 · author #2

Mentions

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Frequent Coauthors