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ORCIDFoutse Khomh
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- affiliation: Polytechnique Montreal, Canada
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2020 – today
- 2023
[j81]Hosna Hooshyar
, Eduardo M. Guerra, Jorge Melegati, Dron Khanna, Abdullah Aldaeej, Gerardo Matturro, Luciana A. M. Zaina, Des Greer, Usman Rafiq, Rafael Chanin, Xiaofeng Wang, Juan Garbajosa, Pekka Abrahamsson, Foutse Khomh, Anh Nguyen-Duc:
Impact in Software Engineering Activities After One Year of COVID-19 Restrictions for Startups and Established Companies. IEEE Access 11: 55178-55203 (2023)- [j80]Khaled Badran, Pierre-Olivier Côté, Amanda Kolopanis, Rached Bouchoucha, Antonio Collante, Diego Elias Costa, Emad Shihab, Foutse Khomh:
Can Ensembling Preprocessing Algorithms Lead to Better Machine Learning Fairness? Computer 56(4): 71-79 (2023) - [j79]Biruk Asmare Muse, Foutse Khomh, Giuliano Antoniol:
Refactoring practices in the context of data-intensive systems. Empir. Softw. Eng. 28(2): 46 (2023) - [j78]Mohammad Mehdi Morovati, Amin Nikanjam, Foutse Khomh, Zhen Ming (Jack) Jiang:
Bugs in machine learning-based systems: a faultload benchmark. Empir. Softw. Eng. 28(3): 62 (2023) - [j77]Osama Ehsan, Foutse Khomh, Ying Zou, Dong Qiu:
Ranking code clones to support maintenance activities. Empir. Softw. Eng. 28(3): 70 (2023) - [j76]Florian Tambon, Foutse Khomh, Giuliano Antoniol:
A probabilistic framework for mutation testing in deep neural networks. Inf. Softw. Technol. 155: 107129 (2023) - [j75]Fatemeh Yousefifeshki, Heng Li, Foutse Khomh:
Studying the challenges of developing hardware description language programs. Inf. Softw. Technol. 159: 107196 (2023) - [j74]Arghavan Moradi Dakhel, Michel C. Desmarais, Foutse Khomh:
Dev2vec: Representing domain expertise of developers in an embedding space. Inf. Softw. Technol. 159: 107218 (2023) - [j73]Rached Bouchoucha, Houssem Ben Braiek, Foutse Khomh, Sonia Bouzidi, Rania Zaatour:
Robustness assessment of hyperspectral image CNNs using metamorphic testing. Inf. Softw. Technol. 162: 107281 (2023) - [j72]Arghavan Moradi Dakhel, Vahid Majdinasab, Amin Nikanjam, Foutse Khomh, Michel C. Desmarais, Zhen Ming (Jack) Jiang:
GitHub Copilot AI pair programmer: Asset or Liability? J. Syst. Softw. 203: 111734 (2023) - [j71]Lionel Nganyewou Tidjon, Foutse Khomh:
The Different Faces of AI Ethics Across the World: A Principle-to-Practice Gap Analysis. IEEE Trans. Artif. Intell. 4(4): 820-839 (2023) - [j70]Vittoria Nardone, Biruk Asmare Muse, Mouna Abidi, Foutse Khomh, Massimiliano Di Penta:
Video Game Bad Smells: What They Are and How Developers Perceive Them. ACM Trans. Softw. Eng. Methodol. 32(4): 88:1-88:35 (2023) - [j69]Houssem Ben Braiek, Foutse Khomh:
Testing Feedforward Neural Networks Training Programs. ACM Trans. Softw. Eng. Methodol. 32(4): 105:1-105:61 (2023) - [j68]Houssem Ben Braiek, Thomas Reid, Foutse Khomh:
Physics-Guided Adversarial Machine Learning for Aircraft Systems Simulation. IEEE Trans. Reliab. 72(3): 1161-1175 (2023) - [c139]Ilham A. Qasse, Shailesh Mishra, Björn Þór Jónsson, Foutse Khomh, Mohammad Hamdaqa:
Chat2Code: A Chatbot for Model Specification and Code Generation, The Case of Smart Contracts. SSE 2023: 50-60 - [c138]Solomon Berhe, Marc Maynard, Foutse Khomh:
Maintenance Cost of Software Ecosystem Updates. ANT/EDI40 2023: 608-615 - [c137]Gabriel Laberge, Ulrich Aïvodji, Satoshi Hara, Mario Marchand, Foutse Khomh:
Fooling SHAP with Stealthily Biased Sampling. ICLR 2023 - [c136]Dmytro Humeniuk, Foutse Khomh, Giuliano Antoniol:
RIGAA at the SBFT 2023 Tool Competition - Cyber-Physical Systems Track. SBFT 2023: 49-50 - [c135]Florian Tambon, Vahid Majdinasab, Amin Nikanjam, Foutse Khomh, Giuliano Antoniol:
Mutation Testing of Deep Reinforcement Learning Based on Real Faults. ICST 2023: 188-198 - [c134]Matteo Bosco, Pasquale Cavoto, Augusto Ungolo, Biruk Asmare Muse, Foutse Khomh, Vittoria Nardone, Massimiliano Di Penta:
UnityLint: A Bad Smell Detector for Unity. ICPC 2023: 186-190 - [c133]Seif Abukhalaf, Mohammad Hamdaqa, Foutse Khomh:
On Codex Prompt Engineering for OCL Generation: An Empirical Study. MSR 2023: 148-157 - [p3]Foutse Khomh, Mohammad Masudur Rahman, Antoine Barbez:
Intelligent Software Maintenance. Optimising the Software Development Process with Artificial Intelligence 2023: 241-275 - [i88]Dmytro Humeniuk, Foutse Khomh, Giuliano Antoniol:
AmbieGen: A Search-based Framework for Autonomous Systems Testing. CoRR abs/2301.01234 (2023) - [i87]Patrick Loic Foalem, Foutse Khomh, Heng Li:
Studying Logging Practice in Machine Learning-based Applications. CoRR abs/2301.04234 (2023) - [i86]Florian Tambon, Vahid Majdinasab, Amin Nikanjam, Foutse Khomh, Giuliano Antoniol:
Mutation Testing of Deep Reinforcement Learning Based on Real Faults. CoRR abs/2301.05651 (2023) - [i85]Seif Abukhalaf, Mohammad Hamdaqa, Foutse Khomh:
On Codex Prompt Engineering for OCL Generation: An Empirical Study. CoRR abs/2303.16244 (2023) - [i84]AmirHossein Naghshzan, Saeed Khalilazar, Pierre Poilane, Olga Baysal, Latifa Guerrouj, Foutse Khomh:
Leveraging Data Mining Algorithms to Recommend Source Code Changes. CoRR abs/2305.00323 (2023) - [i83]Saud Hakem Al Harbi, Lionel Nganyewou Tidjon, Foutse Khomh:
Responsible Design Patterns for Machine Learning Pipelines. CoRR abs/2306.01788 (2023) - [i82]Pierre-Olivier Côté, Amin Nikanjam, Rached Bouchoucha, Ilan Basta, Mouna Abidi, Foutse Khomh:
Quality Issues in Machine Learning Software Systems. CoRR abs/2306.15007 (2023) - [i81]Vahid Majdinasab, Sharon Chee Yin Ho, Mohayeminul Islam, Diego Elias Costa, Emad Shihab, Foutse Khomh, Sarah Nadi, Muhammad Raza:
An Empirical Study on Bugs Inside PyTorch: A Replication Study. CoRR abs/2307.13777 (2023) - [i80]Mohammad Mehdi Morovati, Amin Nikanjam, Florian Tambon, Foutse Khomh, Zhen Ming Jiang:
Bug Characterization in Machine Learning-based Systems. CoRR abs/2307.14512 (2023) - [i79]Alexandre Verdet, Mohammad Hamdaqa, Leuson Da Silva, Foutse Khomh:
Exploring Security Practices in Infrastructure as Code: An Empirical Study. CoRR abs/2308.03952 (2023) - [i78]Xingfang Wu, Heng Li, Foutse Khomh:
On the Effectiveness of Log Representation for Log-based Anomaly Detection. CoRR abs/2308.08736 (2023) - [i77]Ahmed Haj Yahmed, Altaf Allah Abbassi, Amin Nikanjam, Heng Li, Foutse Khomh:
Deploying Deep Reinforcement Learning Systems: A Taxonomy of Challenges. CoRR abs/2308.12438 (2023) - [i76]Ahmed Haj Yahmed, Rached Bouchoucha, Houssem Ben Braiek, Foutse Khomh:
An Intentional Forgetting-Driven Self-Healing Method For Deep Reinforcement Learning Systems. CoRR abs/2308.12445 (2023) - [i75]Dmytro Humeniuk, Foutse Khomh, Giuliano Antoniol:
Reinforcement Learning Informed Evolutionary Search for Autonomous Systems Testing. CoRR abs/2308.12762 (2023) - [i74]Arghavan Moradi Dakhel, Amin Nikanjam, Vahid Majdinasab, Foutse Khomh, Michel C. Desmarais:
Effective Test Generation Using Pre-trained Large Language Models and Mutation Testing. CoRR abs/2308.16557 (2023) - 2022
- [j67]Amin Nikanjam, Mohammad Mehdi Morovati, Foutse Khomh, Houssem Ben Braiek:
Faults in deep reinforcement learning programs: a taxonomy and a detection approach. Autom. Softw. Eng. 29(1): 8 (2022) - [j66]Florian Tambon, Gabriel Laberge, Le An, Amin Nikanjam, Paulina Stevia Nouwou Mindom, Yann Pequignot, Foutse Khomh, Giulio Antoniol, Ettore Merlo, François Laviolette:
How to certify machine learning based safety-critical systems? A systematic literature review. Autom. Softw. Eng. 29(2): 38 (2022) - [j65]Hironori Washizaki, Foutse Khomh, Yann-Gaël Guéhéneuc, Hironori Takeuchi, Naotake Natori, Takuo Doi, Satoshi Okuda:
Software-Engineering Design Patterns for Machine Learning Applications. Computer 55(3): 30-39 (2022) - [j64]Hadhemi Jebnoun, Md. Saidur Rahman, Foutse Khomh, Biruk Asmare Muse:
Clones in deep learning code: what, where, and why? Empir. Softw. Eng. 27(4): 84 (2022) - [j63]Mohammad Masudur Rahman, Foutse Khomh, Marco Castelluccio:
Works for Me! Cannot Reproduce - A Large Scale Empirical Study of Non-reproducible Bugs. Empir. Softw. Eng. 27(5): 111 (2022) - [j62]Mouna Abidi, Md. Saidur Rahman, Moses Openja, Foutse Khomh:
Multi-language design smells: a backstage perspective. Empir. Softw. Eng. 27(5): 116 (2022) - [j61]Biruk Asmare Muse, Csaba Nagy, Anthony Cleve, Foutse Khomh, Giuliano Antoniol:
FIXME: synchronize with database! An empirical study of data access self-admitted technical debt. Empir. Softw. Eng. 27(6): 130 (2022) - [j60]Ahmed Haj Yahmed, Houssem Ben Braiek, Foutse Khomh, Sonia Bouzidi, Rania Zaatour:
DiverGet: a Search-Based Software Testing approach for Deep Neural Network Quantization assessment. Empir. Softw. Eng. 27(7): 193 (2022) - [j59]Dmytro Humeniuk, Foutse Khomh, Giuliano Antoniol:
A search-based framework for automatic generation of testing environments for cyber-physical systems. Inf. Softw. Technol. 149: 106936 (2022) - [j58]Moses Openja, Mohammad Mehdi Morovati, Le An, Foutse Khomh, Mouna Abidi:
Technical debts and faults in open-source quantum software systems: An empirical study. J. Syst. Softw. 193: 111458 (2022) - [j57]Amin Nikanjam, Houssem Ben Braiek, Mohammad Mehdi Morovati, Foutse Khomh:
Automatic Fault Detection for Deep Learning Programs Using Graph Transformations. ACM Trans. Softw. Eng. Methodol. 31(1): 14:1-14:27 (2022) - [j56]Gias Uddin, Yann-Gaël Guéhéneuc, Foutse Khomh, Chanchal K. Roy:
An Empirical Study of the Effectiveness of an Ensemble of Stand-alone Sentiment Detection Tools for Software Engineering Datasets. ACM Trans. Softw. Eng. Methodol. 31(3): 48:1-48:38 (2022) - [j55]Morteza Verdi, Ashkan Sami, Jafar Akhondali, Foutse Khomh, Gias Uddin, Alireza Karami Motlagh:
An Empirical Study of C++ Vulnerabilities in Crowd-Sourced Code Examples. IEEE Trans. Software Eng. 48(5): 1497-1514 (2022) - [c132]Mira Marhaba, Ettore Merlo, Foutse Khomh, Giuliano Antoniol:
Identification of out-of-distribution cases of CNN using class-based surprise adequacy. CAIN 2022: 39-40 - [c131]Moses Openja, Forough Majidi, Foutse Khomh, Bhagya Chembakottu, Heng Li:
Studying the Practices of Deploying Machine Learning Projects on Docker. EASE 2022: 190-200 - [c130]Moses Openja, Amin Nikanjam, Ahmed Haj Yahmed, Foutse Khomh, Zhen Ming Jack Jiang:
An Empirical Study of Challenges in Converting Deep Learning Models. ICSME 2022: 13-23 - [c129]Forough Majidi, Moses Openja, Foutse Khomh, Heng Li:
An Empirical Study on the Usage of Automated Machine Learning Tools. ICSME 2022: 59-70 - [c128]Saumendu Roy, Gabriel Laberge, Banani Roy, Foutse Khomh, Amin Nikanjam, Saikat Mondal:
Why Don't XAI Techniques Agree? Characterizing the Disagreements Between Post-hoc Explanations of Defect Predictions. ICSME 2022: 444-448 - [c127]Houssem Ben Braiek, Ali Tfaily, Foutse Khomh, Thomas Reid, Ciro Guida:
SmOOD: Smoothness-based Out-of-Distribution Detection Approach for Surrogate Neural Networks in Aircraft Design. ASE 2022: 94:1-94:13 - [c126]Dmytro Humeniuk, Giuliano Antoniol, Foutse Khomh:
AmbieGen tool at the SBST 2022 Tool Competition. SBST@ICSE 2022: 43-46 - [c125]Aurel Ikama, Vincent Du, Philippe Belias, Biruk Asmare Muse, Foutse Khomh, Mohammad Hamdaqa:
Revisiting the Impact of Anti-patterns on Fault-Proneness: A Differentiated Replication. SCAM 2022: 56-65 - [c124]Foutse Khomh:
Data quality and model under-specification issues (keynote). SEA4DQ@ESEC/SIGSOFT FSE 2022: 2 - [c123]Poedjadevie Kadjel Ramkisoen, John Businge, Brent van Bladel, Alexandre Decan, Serge Demeyer, Coen De Roover, Foutse Khomh:
PaReco: patched clones and missed patches among the divergent variants of a software family. ESEC/SIGSOFT FSE 2022: 646-658 - [c122]Biruk Asmare Muse, Foutse Khomh, Giuliano Antoniol:
Do Developers Refactor Data Access Code? An Empirical Study. SANER 2022: 25-35 - [i73]Biruk Asmare Muse, Csaba Nagy, Anthony Cleve, Foutse Khomh, Giuliano Antoniol:
FIXME: Synchronize with Database An Empirical Study of Data Access Self-Admitted Technical Debt. CoRR abs/2201.02180 (2022) - [i72]Biruk Asmare Muse, Mohammad Masudur Rahman, Csaba Nagy, Anthony Cleve, Foutse Khomh, Giuliano Antoniol:
On the Prevalence, Impact, and Evolution of SQL Code Smells in Data-Intensive Systems. CoRR abs/2201.02215 (2022) - [i71]Biruk Asmare Muse, Foutse Khomh, Giuliano Antoniol:
Do Developers Refactor Data Access Code? An Empirical Study. CoRR abs/2202.03270 (2022) - [i70]Dmytro Humeniuk, Foutse Khomh, Giuliano Antoniol:
A Search-Based Framework for Automatic Generation of Testing Environments for Cyber-Physical Systems. CoRR abs/2203.12138 (2022) - [i69]Houssem Ben Braiek, Foutse Khomh:
Testing Feedforward Neural Networks Training Programs. CoRR abs/2204.00694 (2022) - [i68]Mohamed Raed El aoun, Heng Li, Foutse Khomh, Lionel N. Tidjon:
Bug Characteristics in Quantum Software Ecosystem. CoRR abs/2204.11965 (2022) - [i67]Mohamed Raed El aoun, Heng Li, Foutse Khomh, Moses Openja:
Understanding Quantum Software Engineering Challenges An Empirical Study on Stack Exchange Forums and GitHub Issues. CoRR abs/2205.03181 (2022) - [i66]Moses Openja, Mohammad Mehdi Morovati, Le An, Foutse Khomh, Mouna Abidi:
Technical Debts and Faults in Open-source Quantum Software Systems: An Empirical Study. CoRR abs/2206.00666 (2022) - [i65]Moses Openja, Forough Majidi, Foutse Khomh, Bhagya Chembakottu, Heng Li:
Studying the Practices of Deploying Machine Learning Projects on Docker. CoRR abs/2206.00699 (2022) - [i64]Lionel Nganyewou Tidjon, Foutse Khomh:
The Different Faces of AI Ethics Across the World: A Principle-Implementation Gap Analysis. CoRR abs/2206.03225 (2022) - [i63]Lionel Nganyewou Tidjon, Foutse Khomh:
Never trust, always verify : a roadmap for Trustworthy AI? CoRR abs/2206.11981 (2022) - [i62]Mohammad Mehdi Morovati, Amin Nikanjam, Foutse Khomh, Zhen Ming Jiang:
Bugs in Machine Learning-based Systems: A Faultload Benchmark. CoRR abs/2206.12311 (2022) - [i61]Moses Openja, Amin Nikanjam, Ahmed Haj Yahmed, Foutse Khomh, Zhen Ming Jiang:
An Empirical Study of Challenges in Converting Deep Learning Models. CoRR abs/2206.14322 (2022) - [i60]Arghavan Moradi Dakhel, Vahid Majdinasab, Amin Nikanjam, Foutse Khomh, Michel C. Desmarais, Zhen Ming Jiang:
GitHub Copilot AI pair programmer: Asset or Liability? CoRR abs/2206.15331 (2022) - [i59]Lionel Nganyewou Tidjon, Foutse Khomh:
Threat Assessment in Machine Learning based Systems. CoRR abs/2207.00091 (2022) - [i58]Arghavan Moradi Dakhel, Michel C. Desmarais, Foutse Khomh:
Dev2vec: Representing Domain Expertise of Developers in an Embedding Space. CoRR abs/2207.05132 (2022) - [i57]Ahmed Haj Yahmed, Houssem Ben Braiek, Foutse Khomh, Sonia Bouzidi, Rania Zaatour:
DiverGet: A Search-Based Software Testing Approach for Deep Neural Network Quantization Assessment. CoRR abs/2207.06282 (2022) - [i56]Florian Tambon, Foutse Khomh, Giuliano Antoniol:
A Probabilistic Framework for Mutation Testing in Deep Neural Networks. CoRR abs/2208.06018 (2022) - [i55]Biruk Asmare Muse, Kawser Wazed Nafi, Foutse Khomh, Giuliano Antoniol:
Data-access performance anti-patterns in data-intensive systems. CoRR abs/2208.08918 (2022) - [i54]Pierre-Olivier Côté, Amin Nikanjam, Rached Bouchoucha, Foutse Khomh:
Quality issues in Machine Learning Software Systems. CoRR abs/2208.08982 (2022) - [i53]Paulina Stevia Nouwou Mindom, Amin Nikanjam, Foutse Khomh:
A Comparison of Reinforcement Learning Frameworks for Software Testing Tasks. CoRR abs/2208.12136 (2022) - [i52]Forough Majidi, Moses Openja, Foutse Khomh, Heng Li:
An Empirical Study on the Usage of Automated Machine Learning Tools. CoRR abs/2208.13116 (2022) - [i51]Houssem Ben Braiek, Thomas Reid, Foutse Khomh:
Physics-Guided Adversarial Machine Learning for Aircraft Systems Simulation. CoRR abs/2209.03431 (2022) - [i50]Houssem Ben Braiek, Ali Tfaily, Foutse Khomh, Thomas Reid, Ciro Guida:
SmOOD: Smoothness-based Out-of-Distribution Detection Approach for Surrogate Neural Networks in Aircraft Design. CoRR abs/2209.03438 (2022) - [i49]Lionel Nganyewou Tidjon, Foutse Khomh:
Reliable Malware Analysis and Detection using Topology Data Analysis. CoRR abs/2211.01535 (2022) - [i48]Mohamed Raed El aoun, Lionel Nganyewou Tidjon, Benjamin Rombaut, Foutse Khomh, Ahmed E. Hassan:
An Empirical Study of Library Usage and Dependency in Deep Learning Frameworks. CoRR abs/2211.15733 (2022) - [i47]Khaled Badran, Pierre-Olivier Côté, Amanda Kolopanis, Rached Bouchoucha, Antonio Collante, Diego Elias Costa, Emad Shihab, Foutse Khomh:
Can Ensembling Pre-processing Algorithms Lead to Better Machine Learning Fairness? CoRR abs/2212.02614 (2022) - [i46]Roozbeh Aghili, Heng Li, Foutse Khomh:
Studying the Characteristics of AIOps Projects on GitHub. CoRR abs/2212.13245 (2022) - 2021
- [j54]Zeinab Azadeh Kermansaravi, Md. Saidur Rahman, Foutse Khomh, Fehmi Jaafar, Yann-Gaël Guéhéneuc:
Investigating design anti-pattern and design pattern mutations and their change- and fault-proneness. Empir. Softw. Eng. 26(1): 9 (2021) - [j53]Mohammad Masudur Rahman, Foutse Khomh, Shamima Yeasmin, Chanchal K. Roy:
The forgotten role of search queries in IR-based bug localization: an empirical study. Empir. Softw. Eng. 26(6): 116 (2021) - [j52]Gias Uddin, Fatima Sabir, Yann-Gaël Guéhéneuc, Omar Alam, Foutse Khomh:
An empirical study of IoT topics in IoT developer discussions on Stack Overflow. Empir. Softw. Eng. 26(6): 121 (2021) - [j51]Mohab Aly, Foutse Khomh, Soumaya Yacout:
What Do Practitioners Discuss about IoT and Industry 4.0 Related Technologies? Characterization and Identification of IoT and Industry 4.0 Categories in Stack Overflow Discussions. Internet Things 14: 100364 (2021) - [j50]Amine Barrak, Ellis E. Eghan, Bram Adams, Foutse Khomh:
Why do builds fail? - A conceptual replication study. J. Syst. Softw. 177: 110939 (2021) - [j49]Rodrigo F. Silva, Mohammad Masudur Rahman, Carlos Eduardo de Carvalho Dantas, Chanchal Kumar Roy, Foutse Khomh, Marcelo de Almeida Maia:
Improved retrieval of programming solutions with code examples using a multi-featured score. J. Syst. Softw. 181: 111063 (2021) - [j48]Patanamon Thongtanunam, Ayushi Rastogi, Foutse Khomh, Serge Demeyer, Meiyappan Nagappan, Kelly Blincoe, Gregorio Robles:
Shadow Program Committee Initiative: Process and Reflection. ACM SIGSOFT Softw. Eng. Notes 46(4): 16-18 (2021) - [j47]Mouna Abidi, Md. Saidur Rahman, Moses Openja, Foutse Khomh:
Are Multi-Language Design Smells Fault-Prone? An Empirical Study. ACM Trans. Softw. Eng. Methodol. 30(3): 29:1-29:56 (2021) - [j46]Gias Uddin, Foutse Khomh, Chanchal K. Roy:
Automatic API Usage Scenario Documentation from Technical Q&A Sites. ACM Trans. Softw. Eng. Methodol. 30(3): 31:1-31:45 (2021) - [j45]Gias Uddin, Foutse Khomh:
Automatic Mining of Opinions Expressed About APIs in Stack Overflow. IEEE Trans. Software Eng. 47(3): 522-559 (2021) - [j44]Gias Uddin, Olga Baysal, Latifa Guerrouj, Foutse Khomh:
Understanding How and Why Developers Seek and Analyze API-Related Opinions. IEEE Trans. Software Eng. 47(4): 694-735 (2021) - [c121]Arghavan Moradi Dakhel, Michel C. Desmarais, Foutse Khomh:
Assessing Developer Expertise from the Statistical Distribution of Programming Syntax Patterns. EASE 2021: 90-99 - [c120]Amin Nikanjam, Foutse Khomh:
Design Smells in Deep Learning Programs: An Empirical Study. ICSME 2021: 332-342 - [c119]Mohamed Raed El aoun, Heng Li, Foutse Khomh, Moses Openja:
Understanding Quantum Software Engineering Challenges An Empirical Study on Stack Exchange Forums and GitHub Issues. ICSME 2021: 343-354 - [c118]Paulina Stevia Nouwou Mindom, Amin Nikanjam, Foutse Khomh, John Mullins:
On Assessing The Safety of Reinforcement Learning algorithms Using Formal Methods. QRS 2021: 260-269 - [c117]Emilio Rivera-Landos, Foutse Khomh, Amin Nikanjam:
The Challenge of Reproducible ML: An Empirical Study on The Impact of Bugs. QRS 2021: 1079-1088 - [c116]Dmytro Humeniuk, Giuliano Antoniol, Foutse Khomh:
Data Driven Testing of Cyber Physical Systems. SBST@ICSE 2021: 16-19 - [c115]Dmytro Humeniuk, Giuliano Antoniol, Foutse Khomh:
SWAT tool at the SBST 2021 Tool Competition. SBST@ICSE 2021: 42-43 - [c114]Alaleh Hamidi, Giuliano Antoniol, Foutse Khomh, Massimiliano Di Penta, Mohammad Hamidi:
Towards Understanding Developers' Machine-Learning Challenges: A Multi-Language Study on Stack Overflow. SCAM 2021: 58-69 - [c113]Mahmood Vahedi, Mohammad Masudur Rahman, Foutse Khomh, Gias Uddin, Giuliano Antoniol:
Summarizing Relevant Parts from Technical Videos. SANER 2021: 434-445 - [c112]Mbarka Soualhia, Foutse Khomh, Sofiène Tahar:
Failure Analysis of Hadoop Schedulers using an Integration of Model Checking and Simulation. SCSS 2021: 114-128 - [p2]Osama Ehsan, Liliane Barbour, Foutse Khomh, Ying Zou:
Is Late Propagation a Harmful Code Clone Evolutionary Pattern? An Empirical Study. Code Clone Analysis 2021: 151-167 - [e9]Nobukazu Yoshioka, Hironori Washizaki, Eduardo B. Fernández, Tomoko Kaneko, Shuichiro Yamamoto, Fuyuki Ishikawa, Foutse Khomh, Giuliano Antoniol:
Proceedings of the International Workshop on Evidence-based Security and Privacy in the Wild and the 1st International Workshop on Machine Learning Systems Engineering co-located with 25th Asia-Pacific Software Engineering Conference (APSEC 2018), Nara, Japan, December 4, 2018. CEUR Workshop Proceedings 2809, CEUR-WS.org 2021 [contents] - [i45]Amin Nikanjam, Mohammad Mehdi Morovati, Foutse Khomh, Houssem Ben Braiek:
Faults in Deep Reinforcement Learning Programs: A Taxonomy and A Detection Approach. CoRR abs/2101.00135 (2021) - [i44]Gias Uddin, Olga Baysal, Latifa Guerrouj, Foutse Khomh:
Understanding How and Why Developers Seek and Analyze API-related Opinions. CoRR abs/2102.08495 (2021) - [i43]Gias Uddin, Foutse Khomh, Chanchal K. Roy:
Automatic API Usage Scenario Documentation from Technical Q&A Sites. CoRR abs/2102.08502 (2021) - [i42]Gias Uddin, Foutse Khomh, Chanchal K. Roy:
Mining API Usage Scenarios from Stack Overflow. CoRR abs/2102.08874 (2021) - [i41]Dmytro Humeniuk, Giuliano Antoniol, Foutse Khomh:
Data Driven Testing of Cyber Physical Systems. CoRR abs/2102.11491 (2021) - [i40]Zeinab Azadeh Kermansaravi, Md. Saidur Rahman, Foutse Khomh, Fehmi Jaafar, Yann-Gaël Guéhéneuc:
Investigating Design Anti-pattern and Design Pattern Mutations and Their Change- and Fault-proneness. CoRR abs/2104.00058 (2021) - [i39]Amin Nikanjam, Houssem Ben Braiek, Mohammad Mehdi Morovati, Foutse Khomh:
Automatic Fault Detection for Deep Learning Programs Using Graph Transformations. CoRR abs/2105.08095 (2021) - [i38]