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ORCIDFoutse Khomh
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- affiliation: Polytechnique Montreal, Canada
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2020 – today
- 2025
[j116]Mehil B. Shah
, Mohammad Masudur Rahman, Foutse Khomh:
Towards enhancing the reproducibility of deep learning bugs: an empirical study. Empir. Softw. Eng. 30(1): 23 (2025)- [j115]Paulina Stevia Nouwou Mindom, Amin Nikanjam, Foutse Khomh:
Harnessing pre-trained generalist agents for software engineering tasks. Empir. Softw. Eng. 30(1): 39 (2025) - [j114]Florian Tambon, Arghavan Moradi Dakhel, Amin Nikanjam, Foutse Khomh, Michel C. Desmarais, Giuliano Antoniol:
Bugs in large language models generated code: an empirical study. Empir. Softw. Eng. 30(3): 65 (2025) - [j113]Alexandre Verdet, Mohammad Hamdaqa, Léuson M. P. da Silva, Foutse Khomh:
Assessing the adoption of security policies by developers in terraform across different cloud providers. Empir. Softw. Eng. 30(3): 74 (2025) - [j112]Saeid Jamshidi, Amin Nikanjam, Kawser Wazed Nafi, Foutse Khomh:
Understanding the impact of IoT security patterns on CPU usage and energy consumption: a dynamic approach for selecting patterns with deep reinforcement learning. Int. J. Inf. Sec. 24(2): 91 (2025) - [j111]Saeid Jamshidi, Amin Nikanjam, Kawser Wazed Nafi, Foutse Khomh, Rasoul Rasta:
Application of deep reinforcement learning for intrusion detection in Internet of Things: A systematic review. Internet Things 31: 101531 (2025) - [j110]Chakkrit Kla Tantithamthavorn, Fabio Palomba, Foutse Khomh, Joselito Joey Chua:
MLOps, LLMOps, FMOps, and Beyond. IEEE Softw. 42(1): 26-32 (2025) - [j109]Qinghua Lu, Apostol Vassilev, Jun Zhu, Foutse Khomh:
Guest Editorial: Operationalizing Responsible AI. IEEE Trans. Artif. Intell. 6(2): 252-253 (2025) - [j108]Moses Openja, Foutse Khomh, Armstrong Foundjem, Zhen Ming (Jack) Jiang, Mouna Abidi, Ahmed E. Hassan:
An Empirical Study of Testing Machine Learning in the Wild. ACM Trans. Softw. Eng. Methodol. 34(1): 7:1-7:63 (2025) - [j107]Iren Mazloomzadeh, Gias Uddin, Foutse Khomh, Ashkan Sami:
Reputation Gaming in Crowd Technical Knowledge Sharing. ACM Trans. Softw. Eng. Methodol. 34(1): 10:1-10:41 (2025) - [i130]Ruchira Manke, Mohammad Wardat, Foutse Khomh, Hridesh Rajan:
Mock Deep Testing: Toward Separate Development of Data and Models for Deep Learning. CoRR abs/2502.07712 (2025) - [i129]Shaona Ghosh, Heather Frase, Adina Williams, Sarah Luger, Paul Röttger, Fazl Barez, Sean McGregor, Kenneth Fricklas, Mala Kumar, Quentin Feuillade--Montixi, Kurt Bollacker, Felix Friedrich, Ryan Tsang, Bertie Vidgen, Alicia Parrish, Chris Knotz, Eleonora Presani, Jonathan Bennion, Marisa Ferrara Boston, Mike Kuniavsky, Wiebke Hutiri, James Ezick, Malek Ben Salem, Rajat Sahay, Sujata S. Goswami, Usman Gohar, Ben Huang, Supheakmungkol Sarin, Elie Alhajjar, Canyu Chen, Roman Eng, Kashyap Ramanandula Manjusha, Virendra Mehta, Eileen Long, Murali Emani, Natan Vidra, Benjamin Rukundo, Abolfazl Shahbazi, Kongtao Chen, Rajat Ghosh, Vithursan Thangarasa, Pierre Peigné, Abhinav Singh, Max Bartolo, Satyapriya Krishna, Mubashara Akhtar, Rafael Gold, Cody Coleman, Luis Oala, Vassil Tashev, Joseph Marvin Imperial, Amy Russ, Sasidhar Kunapuli, Nicolas Miailhe, Julien Delaunay, Bhaktipriya Radharapu, Rajat Shinde, Tuesday, Debojyoti Dutta, Declan Grabb, Ananya Gangavarapu, Saurav Sahay, Agasthya Gangavarapu, Patrick Schramowski, Stephen Singam, Tom David, Xudong Han, Priyanka Mary Mammen, Tarunima Prabhakar, Venelin Kovatchev, Ahmed Ahmed, Kelvin N. Manyeki, Sandeep Madireddy, Foutse Khomh, Fedor Zhdanov, Joachim Baumann, Nina Vasan, Xianjun Yang, Carlos Mougn, Jibin Rajan Varghese, Hussain Chinoy, Seshakrishna Jitendar, Manil Maskey, Claire V. Hardgrove, Tianhao Li, Aakash Gupta, Emil Joswin, Yifan Mai, Shachi H. Kumar, Cigdem Patlak, Kevin Lu, Vincent Alessi, Sree Bhargavi Balija, Chenhe Gu, Robert Sullivan, James Gealy, Matt Lavrisa, James Goel, Peter Mattson, Percy Liang, Joaquin Vanschoren:
AILuminate: Introducing v1.0 of the AI Risk and Reliability Benchmark from MLCommons. CoRR abs/2503.05731 (2025) - [i128]Altaf Allah Abbassi, Léuson M. P. da Silva, Amin Nikanjam, Foutse Khomh:
Unveiling Inefficiencies in LLM-Generated Code: Toward a Comprehensive Taxonomy. CoRR abs/2503.06327 (2025) - [i127]Dmytro Humeniuk, Foutse Khomh:
Representation Improvement in Latent Space for Search-Based Testing of Autonomous Robotic Systems. CoRR abs/2503.20642 (2025) - 2024
- [j106]Bertrand Braunschweig, Stefan Buijsman, Faïcel Chamroukhi, Fredrik Heintz, Foutse Khomh, Juliette Mattioli, Maximilian Poretschkin:
AITA: AI trustworthiness assessment. AI Ethics 4(1): 1-3 (2024) - [j105]Pierre-Olivier Côté, Amin Nikanjam, Nafisa Ahmed, Dmytro Humeniuk, Foutse Khomh:
Data cleaning and machine learning: a systematic literature review. Autom. Softw. Eng. 31(2): 54 (2024) - [j104]Florian Tambon, Amin Nikanjam, Le An, Foutse Khomh, Giuliano Antoniol:
Silent bugs in deep learning frameworks: an empirical study of Keras and TensorFlow. Empir. Softw. Eng. 29(1): 10 (2024) - [j103]Mohammad Mehdi Morovati, Amin Nikanjam, Florian Tambon, Foutse Khomh, Zhen Ming (Jack) Jiang:
Bug characterization in machine learning-based systems. Empir. Softw. Eng. 29(1): 14 (2024) - [j102]Moses Openja, Gabriel Laberge, Foutse Khomh:
Detection and evaluation of bias-inducing features in machine learning. Empir. Softw. Eng. 29(1): 22 (2024) - [j101]Xingfang Wu, Eric Laufer, Heng Li, Foutse Khomh, Santhosh Srinivasan, Jayden Luo:
Characterizing and classifying developer forum posts with their intentions. Empir. Softw. Eng. 29(4): 84 (2024) - [j100]Mohammad Mehdi Morovati, Florian Tambon, Mina Taraghi, Amin Nikanjam, Foutse Khomh:
Common challenges of deep reinforcement learning applications development: an empirical study. Empir. Softw. Eng. 29(4): 95 (2024) - [j99]Mouna Abidi, Md. Saidur Rahman, Moses Openja, Foutse Khomh:
Design smells in multi-language systems and bug-proneness: a survival analysis. Empir. Softw. Eng. 29(5): 106 (2024) - [j98]Biruk Asmare Muse, Kawser Wazed Nafi, Foutse Khomh, Giuliano Antoniol:
Data-access performance anti-patterns in data-intensive systems. Empir. Softw. Eng. 29(6): 144 (2024) - [j97]Pierre-Olivier Côté, Amin Nikanjam, Rached Bouchoucha, Ilan Basta, Mouna Abidi, Foutse Khomh:
Quality issues in machine learning software systems. Empir. Softw. Eng. 29(6): 149 (2024) - [j96]Patrick Loic Foalem, Foutse Khomh, Heng Li:
Studying logging practice in machine learning-based applications. Inf. Softw. Technol. 170: 107450 (2024) - [j95]Arghavan Moradi Dakhel, Amin Nikanjam, Vahid Majdinasab, Foutse Khomh, Michel C. Desmarais:
Effective test generation using pre-trained Large Language Models and mutation testing. Inf. Softw. Technol. 171: 107468 (2024) - [j94]Foutse Khomh, Andreas Metzger, Phu Hong Nguyen, Sagar Sen:
Editorial: Special Issue on Software Engineering and AI for Data Quality. ACM J. Data Inf. Qual. 16(4): 20:1-20:3 (2024) - [j93]Daniel Russo, Sebastian Baltes, Niels van Berkel, Paris Avgeriou, Fabio Calefato, Beatriz Cabrero Daniel, Gemma Catolino, Jürgen Cito, Neil A. Ernst, Thomas Fritz, Hideaki Hata, Reid Holmes, Maliheh Izadi, Foutse Khomh, Mikkel Baun Kjærgaard, Grischa Liebel, Alberto Lluch-Lafuente, Stefano Lambiase, Walid Maalej, Gail C. Murphy, Nils Brede Moe, Gabrielle O'Brien, Elda Paja, Mauro Pezzè, John Stouby Persson, Rafael Prikladnicki, Paul Ralph, Martin P. Robillard, Thiago Rocha Silva, Klaas-Jan Stol, Margaret-Anne D. Storey, Viktoria Stray, Paolo Tell, Christoph Treude, Bogdan Vasilescu:
Generative AI in Software Engineering Must Be Human-Centered: The Copenhagen Manifesto. J. Syst. Softw. 216: 112115 (2024) - [j92]Khouloud Oueslati, Gabriel Laberge, Maxime Lamothe, Foutse Khomh:
Mining Action Rules for Defect Reduction Planning. Proc. ACM Softw. Eng. 1(FSE): 2309-2331 (2024) - [j91]Florian Tambon, Foutse Khomh, Giuliano Antoniol:
GIST: Generated Inputs Sets Transferability in Deep Learning. ACM Trans. Softw. Eng. Methodol. 33(8): 214:1-214:38 (2024) - [j90]Dmytro Humeniuk, Foutse Khomh, Giuliano Antoniol:
Reinforcement Learning Informed Evolutionary Search for Autonomous Systems Testing. ACM Trans. Softw. Eng. Methodol. 33(8): 216:1-216:45 (2024) - [c158]Gabriel Laberge, Yann Batiste Pequignot, Mario Marchand, Foutse Khomh:
Tackling the XAI Disagreement Problem with Regional Explanations. AISTATS 2024: 2017-2025 - [c157]Sylvain Kouemo Ngassom, Arghavan Moradi Dakhel, Florian Tambon, Foutse Khomh:
Chain of Targeted Verification Questions to Improve the Reliability of Code Generated by LLMs. AIware 2024 - [c156]Seif Abukhalaf, Mohammad Hamdaqa, Foutse Khomh:
PathOCL: Path-Based Prompt Augmentation for OCL Generation with GPT-4. FORGE 2024: 108-118 - [c155]Rached Bouchoucha, Ahmed Haj Yahmed, Darshan Patil, Janarthanan Rajendran, Amin Nikanjam, Sarath Chandar, Foutse Khomh:
Toward Debugging Deep Reinforcement Learning Programs with RLExplorer. ICSME 2024: 87-99 - [c154]Roozbeh Aghili, Qiaolin Qin, Heng Li, Foutse Khomh:
Understanding Web Application Workloads and Their Applications: Systematic Literature Review and Characterization. ICSME 2024: 474-486 - [c153]Dmytro Humeniuk, Houssem Ben Braiek, Thomas Reid, Foutse Khomh:
In-Simulation Testing of Deep Learning Vision Models in Autonomous Robotic Manipulators. ASE 2024: 2187-2198 - [c152]Dmytro Humeniuk, Foutse Khomh:
AmbieGenVAE at the SBFT 2024 Tool Competition - Cyber-Physical Systems Track. SBFT@ICSE 2024: 45-46 - [c151]Dmytro Humeniuk, Foutse Khomh:
AmbieGen at the SBFT 2024 Tool Competition - CPS-UAV Track. SBFT@ICSE 2024: 69-70 - [c150]Jihene Rezgui, Félix Jobin, Younes Kechout, Chritine Turgeon, Foutse Khomh:
Towards a Reliable French Speech Recognition Tool for an Automated Diagnosis of Learning Disabilities. SmartNets 2024: 1-6 - [c149]Xingfang Wu, Heng Li, Nobukazu Yoshioka, Hironori Washizaki, Foutse Khomh:
Refining GPT-3 Embeddings with a Siamese Structure for Technical Post Duplicate Detection. SANER 2024: 114-125 - [c148]Vahid Majdinasab, Michael Joshua Bishop, Shawn Rasheed, Arghavan Moradi Dakhel, Amjed Tahir, Foutse Khomh:
Assessing the Security of GitHub Copilot's Generated Code - A Targeted Replication Study. SANER 2024: 435-444 - [c147]Mina Taraghi, Gianolli Dorcelus, Armstrong Foundjem, Florian Tambon, Foutse Khomh:
Deep Learning Model Reuse in the HuggingFace Community: Challenges, Benefit and Trends. SANER 2024: 512-523 - [c146]Cyrine Zid, François Belias, Massimiliano Di Penta, Foutse Khomh, Giuliano Antoniol:
List Comprehension Versus for Loops Performance in Real Python Projects: Should we Care? SANER 2024: 592-601 - [i126]Mehil B. Shah, Mohammad Masudur Rahman, Foutse Khomh:
Towards Enhancing the Reproducibility of Deep Learning Bugs: An Empirical Study. CoRR abs/2401.03069 (2024) - [i125]Mina Taraghi, Gianolli Dorcelus, Armstrong Foundjem, Florian Tambon, Foutse Khomh:
Deep Learning Model Reuse in the HuggingFace Community: Challenges, Benefit and Trends. CoRR abs/2401.13177 (2024) - [i124]Léuson M. P. da Silva, Jordan Samhi, Foutse Khomh:
ChatGPT vs LLaMA: Impact, Reliability, and Challenges in Stack Overflow Discussions. CoRR abs/2402.08801 (2024) - [i123]Vahid Majdinasab, Amin Nikanjam, Foutse Khomh:
Trained Without My Consent: Detecting Code Inclusion In Language Models Trained on Code. CoRR abs/2402.09299 (2024) - [i122]Florian Tambon, Arghavan Moradi Dakhel, Amin Nikanjam, Foutse Khomh, Michel C. Desmarais, Giuliano Antoniol:
Bugs in Large Language Models Generated Code: An Empirical Study. CoRR abs/2403.08937 (2024) - [i121]Houssem Ben Braiek, Foutse Khomh:
Machine Learning Robustness: A Primer. CoRR abs/2404.00897 (2024) - [i120]Bertie Vidgen, Adarsh Agrawal, Ahmed M. Ahmed, Victor Akinwande, Namir Al-Nuaimi, Najla Alfaraj, Elie Alhajjar, Lora Aroyo, Trupti Bavalatti, Borhane Blili-Hamelin, Kurt D. Bollacker, Rishi Bomassani, Marisa Ferrara Boston, Siméon Campos, Kal Chakra, Canyu Chen, Cody Coleman, Zacharie Delpierre Coudert, Leon Derczynski, Debojyoti Dutta, Ian Eisenberg, James Ezick, Heather Frase, Brian Fuller, Ram Gandikota, Agasthya Gangavarapu, Ananya Gangavarapu, James Gealy, Rajat Ghosh, James Goel, Usman Gohar, Subhra S. Goswami, Scott A. Hale, Wiebke Hutiri, Joseph Marvin Imperial, Surgan Jandial, Nick Judd, Felix Juefei-Xu, Foutse Khomh, Bhavya Kailkhura, Hannah Rose Kirk, Kevin Klyman, Chris Knotz, Michael Kuchnik, Shachi H. Kumar, Chris Lengerich, Bo Li, Zeyi Liao, Eileen Peters Long, Victor Lu, Yifan Mai, Priyanka Mary Mammen, Kelvin N. Manyeki, Sean McGregor, Virendra Mehta, Shafee Mohammed, Emanuel Moss, Lama Nachman, Dinesh Jinenhally Naganna, Amin Nikanjam, Besmira Nushi, Luis Oala, Iftach Orr, Alicia Parrish, Cigdem Patlak, William Pietri, Forough Poursabzi-Sangdeh, Eleonora Presani, Fabrizio Puletti, Paul Röttger, Saurav Sahay, Tim Santos, Nino Scherrer, Alice Schoenauer Sebag, Patrick Schramowski, Abolfazl Shahbazi, Vin Sharma, Xudong Shen, Vamsi Sistla, Leonard Tang, Davide Testuggine, Vithursan Thangarasa, Elizabeth Anne Watkins, Rebecca Weiss, Chris Welty, Tyler Wilbers, Adina Williams, Carole-Jean Wu, Poonam Yadav, Xianjun Yang, Yi Zeng, Wenhui Zhang, Fedor Zhdanov, Jiacheng Zhu, Percy Liang, Peter Mattson, Joaquin Vanschoren:
Introducing v0.5 of the AI Safety Benchmark from MLCommons. CoRR abs/2404.12241 (2024) - [i119]Seif Abukhalaf, Mohammad Hamdaqa, Foutse Khomh:
PathOCL: Path-Based Prompt Augmentation for OCL Generation with GPT-4. CoRR abs/2405.12450 (2024) - [i118]Khouloud Oueslati, Gabriel Laberge, Maxime Lamothe, Foutse Khomh:
Mining Action Rules for Defect Reduction Planning. CoRR abs/2405.13740 (2024) - [i117]Sylvain Kouemo Ngassom, Arghavan Moradi Dakhel, Florian Tambon, Foutse Khomh:
Chain of Targeted Verification Questions to Improve the Reliability of Code Generated by LLMs. CoRR abs/2405.13932 (2024) - [i116]Mohamed Salah Bouafif, Chen Zheng, Ilham Ahmed Qasse, Ed Zulkoski, Mohammad Hamdaqa, Foutse Khomh:
A Context-Driven Approach for Co-Auditing Smart Contracts with The Support of GPT-4 code interpreter. CoRR abs/2406.18075 (2024) - [i115]Vahid Majdinasab, Amin Nikanjam, Foutse Khomh:
DeepCodeProbe: Towards Understanding What Models Trained on Code Learn. CoRR abs/2407.08890 (2024) - [i114]Florian Tambon, Amin Nikanjam, Foutse Khomh, Giuliano Antoniol:
Assessing Programming Task Difficulty for Efficient Evaluation of Large Language Models. CoRR abs/2407.21227 (2024) - [i113]Altaf Allah Abbassi, Houssem Ben Braiek, Foutse Khomh, Thomas Reid:
Trimming the Risk: Towards Reliable Continuous Training for Deep Learning Inspection Systems. CoRR abs/2409.09108 (2024) - [i112]Roozbeh Aghili, Heng Li, Foutse Khomh:
An Empirical Study of Sensitive Information in Logs. CoRR abs/2409.11313 (2024) - [i111]Roozbeh Aghili, Qiaolin Qin, Heng Li, Foutse Khomh:
Understanding Web Application Workloads and Their Applications: Systematic Literature Review and Characterization. CoRR abs/2409.12299 (2024) - [i110]Xingfang Wu, Heng Li, Foutse Khomh:
What Information Contributes to Log-based Anomaly Detection? Insights from a Configurable Transformer-Based Approach. CoRR abs/2409.20503 (2024) - [i109]Rached Bouchoucha, Ahmed Haj Yahmed, Darshan Patil, Janarthanan Rajendran, Amin Nikanjam, Sarath Chandar, Foutse Khomh:
Toward Debugging Deep Reinforcement Learning Programs with RLExplorer. CoRR abs/2410.04322 (2024) - [i108]Dmytro Humeniuk, Houssem Ben Braiek, Thomas Reid, Foutse Khomh:
In-Simulation Testing of Deep Learning Vision Models in Autonomous Robotic Manipulators. CoRR abs/2410.19277 (2024) - [i107]Mohammadhossein Malekpour, Nour Shaheen, Foutse Khomh, Amine Mhedhbi:
Towards Optimizing SQL Generation via LLM Routing. CoRR abs/2411.04319 (2024) - [i106]Doriane Olewicki, Léuson M. P. da Silva, Suhaib Mujahid, Arezou Amini, Benjamin Mah, Marco Castelluccio, Sarra Habchi, Foutse Khomh, Bram Adams:
Impact of LLM-based Review Comment Generation in Practice: A Mixed Open-/Closed-source User Study. CoRR abs/2411.07091 (2024) - [i105]Mohammad Mehdi Morovati, Amin Nikanjam, Foutse Khomh:
Fault Localization in Deep Learning-based Software: A System-level Approach. CoRR abs/2411.08172 (2024) - [i104]Mehil B. Shah, Mohammad Masudur Rahman, Foutse Khomh:
Towards Understanding the Impact of Data Bugs on Deep Learning Models in Software Engineering. CoRR abs/2411.12137 (2024) - [i103]Kaveh Shahedi, Heng Li, Maxime Lamothe, Foutse Khomh:
Tracing Optimization for Performance Modeling and Regression Detection. CoRR abs/2411.17548 (2024) - [i102]Forough Majidi, Foutse Khomh, Heng Li, Amin Nikanjam:
An Efficient Model Maintenance Approach for MLOps. CoRR abs/2412.04657 (2024) - [i101]Ruchira Manke, Mohammad Wardat, Foutse Khomh, Hridesh Rajan:
Leveraging Data Characteristics for Bug Localization in Deep Learning Programs. CoRR abs/2412.05775 (2024) - [i100]Paulina Stevia Nouwou Mindom, Léuson M. P. da Silva, Amin Nikanjam, Foutse Khomh:
Continuously Learning Bug Locations. CoRR abs/2412.11289 (2024) - 2023
- [j89]Hosna Hooshyar, Eduardo 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) - [j88]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) - [j87]Biruk Asmare Muse, Foutse Khomh, Giuliano Antoniol:
Refactoring practices in the context of data-intensive systems. Empir. Softw. Eng. 28(2): 46 (2023) - [j86]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) - [j85]Osama Ehsan, Foutse Khomh, Ying Zou, Dong Qiu:
Ranking code clones to support maintenance activities. Empir. Softw. Eng. 28(3): 70 (2023) - [j84]Paulina Stevia Nouwou Mindom, Amin Nikanjam, Foutse Khomh:
A comparison of reinforcement learning frameworks for software testing tasks. Empir. Softw. Eng. 28(5): 111 (2023) - [j83]Xingfang Wu, Heng Li, Foutse Khomh:
On the effectiveness of log representation for log-based anomaly detection. Empir. Softw. Eng. 28(6): 137 (2023) - [j82]Roozbeh Aghili, Heng Li, Foutse Khomh:
Studying the characteristics of AIOps projects on GitHub. Empir. Softw. Eng. 28(6): 143 (2023) - [j81]Florian Tambon, Foutse Khomh, Giuliano Antoniol:
A probabilistic framework for mutation testing in deep neural networks. Inf. Softw. Technol. 155: 107129 (2023) - [j80]Fatemeh Yousefifeshki, Heng Li, Foutse Khomh:
Studying the challenges of developing hardware description language programs. Inf. Softw. Technol. 159: 107196 (2023) - [j79]Arghavan Moradi Dakhel, Michel C. Desmarais, Foutse Khomh:
Dev2vec: Representing domain expertise of developers in an embedding space. Inf. Softw. Technol. 159: 107218 (2023) - [j78]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) - [j77]Bhagya Chembakottu, Heng Li, Foutse Khomh:
A large-scale exploratory study of android sports apps in the google play store. Inf. Softw. Technol. 164: 107321 (2023) - [j76]Gabriel Laberge, Yann Pequignot, Alexandre Mathieu, Foutse Khomh, Mario Marchand:
Partial Order in Chaos: Consensus on Feature Attributions in the Rashomon Set. J. Mach. Learn. Res. 24: 364:1-364:50 (2023) - [j75]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) - [j74]Dmytro Humeniuk, Foutse Khomh, Giuliano Antoniol:
AmbieGen: A search-based framework for autonomous systems testing. Sci. Comput. Program. 230: 102990 (2023) - [j73]Matteo Biagiola, Nicolás Cardozo, Donghwan Shin, Foutse Khomh, Andrea Stocco, Vincenzo Riccio:
Summary of the Fourth International Workshop on Deep Learning for Testing and Testing for Deep Learning (DeepTest 2023). ACM SIGSOFT Softw. Eng. Notes 48(4): 39-40 (2023) - [j72]Md. Saidur Rahman, Foutse Khomh, Alaleh Hamidi, Jinghui Cheng, Giuliano Antoniol, Hironori Washizaki:
Machine learning application development: practitioners' insights. Softw. Qual. J. 31(4): 1065-1119 (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) - [c145]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 - [c144]Solomon Berhe, Marc Maynard, Foutse Khomh:
Maintenance Cost of Software Ecosystem Updates. ANT/EDI40 2023: 608-615 - [c143]Weitao Pan, Hironori Washizaki, Nobukazu Yoshioka, Yoshiaki Fukazawa, Foutse Khomh, Yann-Gaël Guéhéneuc:
A Machine Learning Based Approach to Detect Machine Learning Design Patterns. APSEC 2023: 574-578 - [c142]Gabriel Laberge, Ulrich Aïvodji, Satoshi Hara, Mario Marchand, Foutse Khomh:
Fooling SHAP with Stealthily Biased Sampling. ICLR 2023 - [c141]Dmytro Humeniuk, Foutse Khomh, Giuliano Antoniol:
RIGAA at the SBFT 2023 Tool Competition - Cyber-Physical Systems Track. SBFT 2023: 49-50 - [c140]Ahmed Haj Yahmed, Altaf Allah Abbassi, Amin Nikanjam, Heng Li, Foutse Khomh:
Deploying Deep Reinforcement Learning Systems: A Taxonomy of Challenges. ICSME 2023: 26-38 - [c139]Sharon Chee Yin Ho, Vahid Majdinasab, Mohayeminul Islam, Diego Elias Costa, Emad Shihab, Foutse Khomh, Sarah Nadi, Muhammad Raza:
An Empirical Study on Bugs Inside PyTorch: A Replication Study. ICSME 2023: 220-231 - [c138]Florian Tambon, Vahid Majdinasab, Amin Nikanjam, Foutse Khomh, Giuliano Antoniol:
Mutation Testing of Deep Reinforcement Learning Based on Real Faults. ICST 2023: 188-198 - [c137]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 - [c136]Ahmed Haj Yahmed, Rached Bouchoucha, Houssem Ben Braiek, Foutse Khomh:
An Intentional Forgetting-Driven Self-Healing Method for Deep Reinforcement Learning Systems. ASE 2023: 1314-1325 - [c135]Seif Abukhalaf, Mohammad Hamdaqa, Foutse Khomh:
On Codex Prompt Engineering for OCL Generation: An Empirical Study. MSR 2023: 148-157 - [c134]Foutse Khomh:
Harnessing Predictive Modeling and Software Analytics in the Age of LLM-Powered Software Development (Invited Talk). PROMISE 2023: 1 - [p3]Foutse Khomh, Mohammad Masudur Rahman, Antoine Barbez:
Intelligent Software Maintenance. Optimising the Software Development Process with Artificial Intelligence 2023: 241-275 - [e10]Foutse Khomh, Preetha Chatterjee, Andreas Metzger:
Proceedings of the 3rd International Workshop on Software Engineering and AI for Data Quality in Cyber-Physical Systems/Internet of Things, SEA4DQ 2023, San Francisco, CA, USA, 4 December 2023. ACM 2023 [contents] - [i99]Dmytro Humeniuk, Foutse Khomh, Giuliano Antoniol:
AmbieGen: A Search-based Framework for Autonomous Systems Testing. CoRR abs/2301.01234 (2023) - [i98]Patrick Loic Foalem, Foutse Khomh, Heng Li:
Studying Logging Practice in Machine Learning-based Applications. CoRR abs/2301.04234 (2023) - [i97]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) - [i96]Seif Abukhalaf, Mohammad Hamdaqa, Foutse Khomh:
On Codex Prompt Engineering for OCL Generation: An Empirical Study. CoRR abs/2303.16244 (2023) - [i95]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) - [i94]Saud Hakem Al Harbi, Lionel Nganyewou Tidjon, Foutse Khomh:
Responsible Design Patterns for Machine Learning Pipelines. CoRR abs/2306.01788 (2023) - [i93]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) - [i92]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) - [i91]Mohammad Mehdi Morovati, Amin Nikanjam, Florian Tambon, Foutse Khomh, Zhen Ming Jiang:
Bug Characterization in Machine Learning-based Systems. CoRR abs/2307.14512 (2023) - [i90]Alexandre Verdet, Mohammad Hamdaqa, Léuson M. P. da Silva, Foutse Khomh:
Exploring Security Practices in Infrastructure as Code: An Empirical Study. CoRR abs/2308.03952 (2023) - [i89]Xingfang Wu, Heng Li, Foutse Khomh:
On the Effectiveness of Log Representation for Log-based Anomaly Detection. CoRR abs/2308.08736 (2023) - [i88]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) - [i87]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) - [i86]Dmytro Humeniuk, Foutse Khomh, Giuliano Antoniol:
Reinforcement Learning Informed Evolutionary Search for Autonomous Systems Testing. CoRR abs/2308.12762 (2023) - [i85]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) - [i84]Pierre-Olivier Côté, Amin Nikanjam, Nafisa Ahmed, Dmytro Humeniuk, Foutse Khomh:
Data Cleaning and Machine Learning: A Systematic Literature Review. CoRR abs/2310.01765 (2023) - [i83]Bhagya Chembakottu, Heng Li, Foutse Khomh:
A Large-Scale Exploratory Study of Android Sports Apps in the Google Play Store. CoRR abs/2310.07921 (2023) - [i82]Mohammad Mehdi Morovati, Florian Tambon, Mina Taraghi, Amin Nikanjam, Foutse Khomh:
Common Challenges of Deep Reinforcement Learning Applications Development: An Empirical Study. CoRR abs/2310.09575 (2023) - [i81]Moses Openja, Gabriel Laberge, Foutse Khomh:
Detection and Evaluation of bias-inducing Features in Machine learning. CoRR abs/2310.12805 (2023) - [i80]Florian Tambon, Foutse Khomh, Giuliano Antoniol:
GIST: Generated Inputs Sets Transferability in Deep Learning. CoRR abs/2311.00801 (2023) - [i79]Vahid Majdinasab, Michael Joshua Bishop, Shawn Rasheed, Arghavan Moradi Dakhel, Amjed Tahir, Foutse Khomh:
Assessing the Security of GitHub Copilot Generated Code - A Targeted Replication Study. CoRR abs/2311.11177 (2023) - [i78]Aaditya Bhatia, Foutse Khomh, Bram Adams, Ahmed E. Hassan:
An Empirical Study of Self-Admitted Technical Debt in Machine Learning Software. CoRR abs/2311.12019 (2023) - [i77]Moses Openja, Foutse Khomh, Armstrong Foundjem, Zhen Ming Jiang, Mouna Abidi, Ahmed E. Hassan:
Studying the Practices of Testing Machine Learning Software in the Wild. CoRR abs/2312.12604 (2023) - [i76]Xingfang Wu, Eric Laufer, Heng Li, Foutse Khomh, Santhosh Srinivasan, Jayden Luo:
Characterizing and Classifying Developer Forum Posts with their Intentions. CoRR abs/2312.14279 (2023) - [i75]Xingfang Wu, Heng Li, Nobukazu Yoshioka, Hironori Washizaki, Foutse Khomh:
Refining GPT-3 Embeddings with a Siamese Structure for Technical Post Duplicate Detection. CoRR abs/2312.15068 (2023) - [i74]Paulina Stevia Nouwou Mindom, Amin Nikanjam, Foutse Khomh:
Harnessing Pre-trained Generalist Agents for Software Engineering Tasks. CoRR abs/2312.15536 (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) - [c133]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 - [c132]Moses Openja, Forough Majidi, Foutse Khomh, Bhagya Chembakottu, Heng Li:
Studying the Practices of Deploying Machine Learning Projects on Docker. EASE 2022: 190-200 - [c131]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 - [c130]Forough Majidi, Moses Openja, Foutse Khomh, Heng Li:
An Empirical Study on the Usage of Automated Machine Learning Tools. ICSME 2022: 59-70 - [c129]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 - [c128]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 - [c127]Dmytro Humeniuk, Giuliano Antoniol, Foutse Khomh:
AmbieGen tool at the SBST 2022 Tool Competition. SBST@ICSE 2022: 43-46 - [c126]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 - [c125]Md. Saidur Rahman, Foutse Khomh, Emilio Rivera, Yann-Gaël Guéhéneuc, Bernd Lehnert:
Challenges in machine learning application development: an industrial experience report. SE4RAI@ICSE 2022: 21-28 - [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 - [d7]Vittoria Nardone, Biruk Asmare Muse, Mouna Abidi, Foutse Khomh, Massimiliano Di Penta:
Video Games Bad Smells: What they are and how Developers Perceive Them - Online dataset. Version 1. Zenodo, 2022 [all versions]
- [d6]Vittoria Nardone, Biruk Asmare Muse, Mouna Abidi, Foutse Khomh, Massimiliano Di Penta:
Video Games Bad Smells: What they are and how Developers Perceive Them - Online dataset. Version 2. Zenodo, 2022 [all versions] - [d5]Vittoria Nardone, Biruk Asmare Muse, Mouna Abidi, Foutse Khomh, Massimiliano Di Penta:
Video Games Bad Smells: What they are and how Developers Perceive Them - Online dataset. Version 3. Zenodo, 2022 [all versions] - [d4]Vittoria Nardone, Biruk Asmare Muse, Mouna Abidi, Foutse Khomh, Massimiliano Di Penta:
Video Games Bad Smells: What they are and how Developers Perceive Them - Online dataset. Version 4. Zenodo, 2022 [all versions] - [d3]Vittoria Nardone, Biruk Asmare Muse, Mouna Abidi, Foutse Khomh, Massimiliano Di Penta:
Video Game Bad Smells: What they are and how Developers Perceive Them - Online dataset. Version 5. Zenodo, 2022 [all versions] - [d2]José Raúl Romero, Inmaculada Medina-Bulo, Francisco Chicano, Liyan Song, Leandro L. Minku, Fitsum Meshesha Kifetew, Anna Perini, Angelo Susi, Antonio Garmendia, Dominik Bork, Martin Eisenberg, Thiago do Nascimento Ferreira, Marouane Kessentini, Manuel Wimmer, Tien N. Nguyen, José Antonio Parejo, Ana Belén Sánchez, Afonso Fontes, Gregory Gay, Francisco Gomes de Oliveira Neto, Robert Feldt, Michael Felderer, Eduard Paul Enoiu, Sahar Tahvili, Foutse Khomh, Mohammad Masudur Rahman, Antoine Barbez, Javier Ferrer, Pedro Delgado-Pérez, Aurora Ramírez, Breno Miranda:
Complementary material for the book "Optimising the Software Development Process with Artificial Intelligence". Zenodo, 2022 - [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]Amin Nikanjam, Foutse Khomh:
Design Smells in Deep Learning Programs: An Empirical Study. CoRR abs/2107.02279 (2021) - [i37]Florian Tambon, Giulio Antoniol, Foutse Khomh:
HOMRS: High Order Metamorphic Relations Selector for Deep Neural Networks. CoRR abs/2107.04863 (2021) - [i36]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. CoRR abs/2107.12045 (2021) - [i35]Ettore Merlo, Mira Marhaba, Foutse Khomh, Houssem Ben Braiek, Giuliano Antoniol:
Models of Computational Profiles to Study the Likelihood of DNN Metamorphic Test Cases. CoRR abs/2107.13491 (2021) - [i34]Hadhemi Jebnoun, Md. Saidur Rahman, Foutse Khomh, Biruk Asmare Muse:
Clones in Deep Learning Code: What, Where, and Why? CoRR abs/2107.13614 (2021) - [i33]Rodrigo F. Silva, Mohammad Masudur Rahman, Carlos Eduardo de Carvalho Dantas, Chanchal K. Roy, Foutse Khomh, Marcelo de Almeida Maia:
Improved Retrieval of Programming Solutions With Code Examples Using a Multi-featured Score. CoRR abs/2108.02702 (2021) - [i32]Mohammad Masudur Rahman, Foutse Khomh, Marco Castelluccio:
Why are Some Bugs Non-Reproducible? An Empirical Investigation using Data Fusion. CoRR abs/2108.05316 (2021) - [i31]Mohammad Masudur Rahman, Foutse Khomh, Shamima Yeasmin, Chanchal K. Roy:
The Forgotten Role of Search Queries in IR-based Bug Localization: An Empirical Study. CoRR abs/2108.05341 (2021) - [i30]Emilio Rivera-Landos, Foutse Khomh, Amin Nikanjam:
The challenge of reproducible ML: an empirical study on the impact of bugs. CoRR abs/2109.03991 (2021) - [i29]Gabriel Laberge, Yann Pequignot, Foutse Khomh, Mario Marchand, Alexandre Mathieu:
Partial order: Finding Consensus among Uncertain Feature Attributions. CoRR abs/2110.13369 (2021) - [i28]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. CoRR abs/2111.03196 (2021) - [i27]Paulina Stevia Nouwou Mindom, Amin Nikanjam, Foutse Khomh, John Mullins:
On Assessing The Safety of Reinforcement Learning algorithms Using Formal Methods. CoRR abs/2111.04865 (2021) - [i26]Iren Mazloomzadeh, Gias Udin, Foutse Khomh, Ashkan Sami:
Reputation Gaming in Stack Overflow. CoRR abs/2111.07101 (2021) - [i25]Florian Tambon, Amin Nikanjam, Le An, Foutse Khomh, Giuliano Antoniol:
Silent Bugs in Deep Learning Frameworks: An Empirical Study of Keras and TensorFlow. CoRR abs/2112.13314 (2021) - [i24]Md. Saidur Rahman, Foutse Khomh, Alaleh Hamidi, Jinghui Cheng, Giuliano Antoniol, Hironori Washizaki:
Machine Learning Application Development: Practitioners' Insights. CoRR abs/2112.15277 (2021) - 2020
- [j43]Bowen Xu, Le An, Ferdian Thung, Foutse Khomh, David Lo:
Why reinventing the wheels? An empirical study on library reuse and re-implementation. Empir. Softw. Eng. 25(1): 755-789 (2020) - [j42]Rodrigo Morales, Foutse Khomh, Giuliano Antoniol:
RePOR: Mimicking humans on refactoring tasks. Are we there yet? Empir. Softw. Eng. 25(4): 2960-2996 (2020) - [j41]Gias Uddin, Foutse Khomh, Chanchal K. Roy:
Mining API usage scenarios from stack overflow. Inf. Softw. Technol. 122: 106277 (2020) - [j40]Cristiano Politowski, Foutse Khomh, Simone Romano, Giuseppe Scanniello, Fábio Petrillo, Yann-Gaël Guéhéneuc, Abdou Maiga:
A large scale empirical study of the impact of Spaghetti Code and Blob anti-patterns on program comprehension. Inf. Softw. Technol. 122: 106278 (2020) - [j39]Antoine Barbez, Foutse Khomh, Yann-Gaël Guéhéneuc:
A machine-learning based ensemble method for anti-patterns detection. J. Syst. Softw. 161 (2020) - [j38]Houssem Ben Braiek, Foutse Khomh:
On testing machine learning programs. J. Syst. Softw. 164: 110542 (2020) - [j37]Bram Adams, Foutse Khomh:
The Diversity Crisis of Software Engineering for Artificial Intelligence. IEEE Softw. 37(4): 104-108 (2020) - [j36]Mbarka Soualhia, Foutse Khomh, Sofiène Tahar:
A Dynamic and Failure-Aware Task Scheduling Framework for Hadoop. IEEE Trans. Cloud Comput. 8(2): 553-569 (2020) - [c111]Solomon Berhe, Marc Maynard, Foutse Khomh:
Software Release Patterns When is it a good time to update a software component? ANT/EDI40 2020: 618-625 - [c110]Devansh Tiwari, Hironori Washizaki, Yoshiaki Fukazawa, Tomoyuki Fukuoka, Junji Tamaki, Nobuhiro Hosotani, Munetaka Kohama, Yann-Gaël Guéhéneuc, Foutse Khomh:
Commit - Defect and Architectural Metrics - based Quality Assessment of C Language. ENASE 2020: 579-586 - [c109]Ehsan Firouzi, Ashkan Sami, Foutse Khomh, Gias Uddin:
On the use of C# Unsafe Code Context: An Empirical Study of Stack Overflow. ESEM 2020: 39:1-39:6 - [c108]Mouna Abidi, Foutse Khomh:
Towards the Definition of Patterns and Code Smells for Multi-language Systems. EuroPLoP 2020: 37:1-37:13 - [c107]Cyrine Zid, Dmytro Humeniuk, Foutse Khomh, Giuliano Antoniol:
Double Cycle Hybrid Testing of Hybrid Distributed IoT System. ICSE (Workshops) 2020: 529-532 - [c106]Moses Openja, Bram Adams, Foutse Khomh:
Analysis of Modern Release Engineering Topics : - A Large-Scale Study using StackOverflow -. ICSME 2020: 104-114 - [c105]Mohammad Masudur Rahman, Foutse Khomh, Marco Castelluccio:
Why are Some Bugs Non-Reproducible? : -An Empirical Investigation using Data Fusion-. ICSME 2020: 605-616 - [c104]Hironori Washizaki, Hironori Takeuchi, Foutse Khomh, Naotake Natori, Takuo Doi, Satoshi Okuda:
Practitioners' insights on machine-learning software engineering design patterns: a preliminary study. ICSME 2020: 797-799 - [c103]Fabiano Pecorelli, Fabio Palomba, Foutse Khomh, Andrea De Lucia:
Developer-Driven Code Smell Prioritization. MSR 2020: 220-231 - [c102]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. MSR 2020: 327-338 - [c101]Hadhemi Jebnoun, Houssem Ben Braiek, Mohammad Masudur Rahman, Foutse Khomh:
The Scent of Deep Learning Code: An Empirical Study. MSR 2020: 420-430 - [c100]Mouna Abidi, Moses Openja, Foutse Khomh:
Multi-language Design Smells: A Backstage Perspective. MSR 2020: 615-618 - [e8]Foutse Khomh, Pasquale Salza, Gemma Catolino:
Proceedings of the 4th ACM SIGSOFT International Workshop on Machine Learning Techniques for Software Quality Evaluation, MaLTeSQuE@ESEC/SIGSOFT FSE 2020, Virtual Event, USA, November 13, 2020. ACM 2020, ISBN 978-1-4503-8124-6 [contents] - [e7]Kostas Kontogiannis, Foutse Khomh, Alexander Chatzigeorgiou, Marios-Eleftherios Fokaefs, Minghui Zhou:
27th IEEE International Conference on Software Analysis, Evolution and Reengineering, SANER 2020, London, ON, Canada, February 18-21, 2020. IEEE 2020, ISBN 978-1-7281-5143-4 [contents] - [d1]Cristiano Politowski, Foutse Khomh, Simone Romano, Giuseppe Scanniello, Fábio Petrillo, Yann-Gaël Guéhéneuc, Abdou Maiga:
A Large Scale Empirical Study of the Impact of Spaghetti Code and Blob Anti-patterns on Program Comprehension. Zenodo, 2020 - [i23]Cristiano Politowski, Foutse Khomh, Simone Romano, Giuseppe Scanniello, Fábio Petrillo, Yann-Gaël Guéhéneuc, Abdou Maiga:
A Large Scale Empirical Study of the Impact of Spaghetti Code and Blob Anti-patterns on Program Comprehension. CoRR abs/2009.02438 (2020) - [i22]Mouna Abidi, Md. Saidur Rahman, Moses Openja, Foutse Khomh:
Are Multi-language Design Smells Prevalent? An Empirical Study. CoRR abs/2010.14331 (2020)
2010 – 2019
- 2019
- [j35]Le An, Marco Castelluccio, Foutse Khomh:
An empirical study of DLL injection bugs in the Firefox ecosystem. Empir. Softw. Eng. 24(4): 1799-1822 (2019) - [j34]Marco Castelluccio, Le An, Foutse Khomh:
An empirical study of patch uplift in rapid release development pipelines. Empir. Softw. Eng. 24(5): 3008-3044 (2019) - [j33]Ikram El Asri, Noureddine Kerzazi, Gias Uddin, Foutse Khomh, Mohammed Abdou Janati Idrissi:
An empirical study of sentiments in code reviews. Inf. Softw. Technol. 114: 37-54 (2019) - [j32]Mohab Aly, Foutse Khomh, Mohammed Haoues, Alejandro Quintero, Soumaya Yacout:
Enforcing security in Internet of Things frameworks: A Systematic Literature Review. Internet Things 6 (2019) - [j31]Mohab Aly, Foutse Khomh, Yann-Gaël Guéhéneuc, Hironori Washizaki, Soumaya Yacout:
Is Fragmentation a Threat to the Success of the Internet of Things? IEEE Internet Things J. 6(1): 472-487 (2019) - [j30]Fábio Petrillo, Yann-Gaël Guéhéneuc, Marcelo Pimenta, Carla Maria Dal Sasso Freitas, Foutse Khomh:
Swarm debugging: The collective intelligence on interactive debugging. J. Syst. Softw. 153: 152-174 (2019) - [j29]David Johannes, Foutse Khomh, Giuliano Antoniol:
A large-scale empirical study of code smells in JavaScript projects. Softw. Qual. J. 27(3): 1271-1314 (2019) - [c99]Mouna Abidi, Manel Grichi, Foutse Khomh:
Behind the scenes: developers' perception of multi-language practices. CASCON 2019: 72-81 - [c98]Manel Grichi, Mouna Abidi, Yann-Gaël Guéhéneuc, Foutse Khomh:
State of practices of Java native interface. CASCON 2019: 274-283 - [c97]Mbarka Soualhia, Chunyan Fu, Foutse Khomh:
Infrastructure fault detection and prediction in edge cloud environments. SEC 2019: 222-235 - [c96]Mouna Abidi, Manel Grichi, Foutse Khomh, Yann-Gaël Guéhéneuc:
Code smells for multi-language systems. EuroPLoP 2019: 12:1-12:13 - [c95]Mouna Abidi, Foutse Khomh, Yann-Gaël Guéhéneuc:
Anti-patterns for multi-language systems. EuroPLoP 2019: 42:1-42:14 - [c94]Gias Uddin, Foutse Khomh, Chanchal K. Roy:
Towards crowd-sourced API documentation. ICSE (Companion Volume) 2019: 310-311 - [c93]Antoine Barbez, Foutse Khomh, Yann-Gaël Guéhéneuc:
Deep Learning Anti-Patterns from Code Metrics History. ICSME 2019: 114-124 - [c92]Houssem Ben Braiek, Foutse Khomh:
DeepEvolution: A Search-Based Testing Approach for Deep Neural Networks. ICSME 2019: 454-458 - [c91]Hironori Washizaki, Hiromu Uchida, Foutse Khomh, Yann-Gaël Guéhéneuc:
Studying Software Engineering Patterns for Designing Machine Learning Systems. IWESEP 2019: 49-54 - [c90]Houssem Ben Braiek, Foutse Khomh:
TFCheck : A TensorFlow Library for Detecting Training Issues in Neural Network Programs. QRS 2019: 426-433 - [c89]John Businge, Moses Openja, David Kavaler, Engineer Bainomugisha, Foutse Khomh, Vladimir Filkov:
Studying Android App Popularity by Cross-Linking GitHub and Google Play Store. SANER 2019: 287-297 - [p1]Yann-Gaël Guéhéneuc, Foutse Khomh:
Empirical Software Engineering. Handbook of Software Engineering 2019: 285-320 - [e6]Yann-Gaël Guéhéneuc, Foutse Khomh, Federica Sarro:
Proceedings of the 27th International Conference on Program Comprehension, ICPC 2019, Montreal, QC, Canada, May 25-31, 2019. IEEE / ACM 2019, ISBN 978-1-7281-1519-1 [contents] - [e5]Leandro L. Minku, Foutse Khomh, Jean Petric:
Proceedings of the Fifteenth International Conference on Predictive Models and Data Analytics in Software Engineering, PROMISE 2019, Recife, Brazil, September 18, 2019. ACM 2019, ISBN 978-1-4503-7233-6 [contents] - [i21]Fábio Petrillo, Yann-Gaël Guéhéneuc, Marcelo Pimenta, Carla Maria Dal Sasso Freitas, Foutse Khomh:
Swarm Debugging: the Collective Intelligence on Interactive Debugging. CoRR abs/1902.03520 (2019) - [i20]Antoine Barbez, Foutse Khomh, Yann-Gaël Guéhéneuc:
A Machine-learning Based Ensemble Method For Anti-patterns Detection. CoRR abs/1903.01899 (2019) - [i19]Md. Saidur Rahman, Emilio Rivera, Foutse Khomh, Yann-Gaël Guéhéneuc, Bernd Lehnert:
Machine Learning Software Engineering in Practice: An Industrial Case Study. CoRR abs/1906.07154 (2019) - [i18]Houssem Ben Braiek, Foutse Khomh:
TFCheck : A TensorFlow Library for Detecting Training Issues in Neural Network Programs. CoRR abs/1909.02562 (2019) - [i17]Houssem Ben Braiek, Foutse Khomh:
DeepEvolution: A Search-Based Testing Approach for Deep Neural Networks. CoRR abs/1909.02563 (2019) - [i16]Morteza Verdi, Ashkan Sami, Jafar Akhondali, Foutse Khomh, Gias Uddin, Alireza Karami Motlagh:
An Empirical Study of C++ Vulnerabilities in Crowd-Sourced Code Examples. CoRR abs/1910.01321 (2019) - [i15]Hironori Washizaki, Hiromu Uchida, Foutse Khomh, Yann-Gaël Guéhéneuc:
Studying Software Engineering Patterns for Designing Machine Learning Systems. CoRR abs/1910.04736 (2019) - [i14]Antoine Barbez, Foutse Khomh, Yann-Gaël Guéhéneuc:
Deep Learning Anti-patterns from Code Metrics History. CoRR abs/1910.07658 (2019) - [i13]Simon Msika, Alejandro Quintero, Foutse Khomh:
SIGMA : Strengthening IDS with GAN and Metaheuristics Attacks. CoRR abs/1912.09303 (2019) - [i12]Foutse Khomh, Fuyuki Ishikawa, Hiroshi Maruyama:
Software Engineering for Machine Learning Systems (SEMLS) (NII Shonan Meeting 156). NII Shonan Meet. Rep. 2019 (2019) - 2018
- [j28]Rodrigo Morales, Francisco Chicano, Foutse Khomh, Giuliano Antoniol:
Exact search-space size for the refactoring scheduling problem. Autom. Softw. Eng. 25(2): 195-200 (2018) - [j27]Zéphyrin Soh, Foutse Khomh, Yann-Gaël Guéhéneuc, Giuliano Antoniol:
Noise in Mylyn interaction traces and its impact on developers and recommendation systems. Empir. Softw. Eng. 23(2): 645-692 (2018) - [j26]Hironori Washizaki, Yann-Gaël Guéhéneuc, Foutse Khomh:
ProMeTA: a taxonomy for program metamodels in program reverse engineering. Empir. Softw. Eng. 23(4): 2323-2358 (2018) - [j25]Rubén Saborido, Rodrigo Morales, Foutse Khomh, Yann-Gaël Guéhéneuc, Giuliano Antoniol:
Getting the most from map data structures in Android. Empir. Softw. Eng. 23(5): 2829-2864 (2018) - [j24]Foutse Khomh, S. Amirhossein Abtahizadeh:
Understanding the impact of cloud patterns on performance and energy consumption. J. Syst. Softw. 141: 151-170 (2018) - [j23]Rodrigo Morales, Francisco Chicano, Foutse Khomh, Giuliano Antoniol:
Efficient refactoring scheduling based on partial order reduction. J. Syst. Softw. 145: 25-51 (2018) - [j22]Bram Adams, Stephany Bellomo, Christian Bird, Boris Debic, Foutse Khomh, Kim Moir, John ODuinn:
Release Engineering 3.0. IEEE Softw. 35(2): 22-25 (2018) - [j21]Foutse Khomh, Bram Adams, Jinghui Cheng, Marios Fokaefs, Giuliano Antoniol:
Software Engineering for Machine-Learning Applications: The Road Ahead. IEEE Softw. 35(5): 81-84 (2018) - [j20]Le An, Foutse Khomh, Yann-Gaël Guéhéneuc:
An empirical study of crash-inducing commits in Mozilla Firefox. Softw. Qual. J. 26(2): 553-584 (2018) - [j19]Liliane Barbour, Le An, Foutse Khomh, Ying Zou, Shaohua Wang:
An investigation of the fault-proneness of clone evolutionary patterns. Softw. Qual. J. 26(4): 1187-1222 (2018) - [j18]Rubén Saborido, Foutse Khomh, Abram Hindle, Enrique Alba:
An app performance optimization advisor for mobile device app marketplaces. Sustain. Comput. Informatics Syst. 19: 29-42 (2018) - [j17]Rodrigo Morales, Rubén Saborido, Foutse Khomh, Francisco Chicano, Giuliano Antoniol:
EARMO: An Energy-Aware Refactoring Approach for Mobile Apps. IEEE Trans. Software Eng. 44(12): 1176-1206 (2018) - [c88]Fuyuki Ishikawa, Foutse Khomh, Nobukazu Yoshioka, Giuliano Antoniol:
Report of iMLSE-18: the 1st International Workshop on Machine Learning Systems Engineering. WESPr-iMLSE@APSEC 2018: 3-4 - [c87]Le An, Foutse Khomh, Shane McIntosh, Marco Castelluccio:
Why Did This Reviewed Code Crash? An Empirical Study of Mozilla Firefox. APSEC 2018: 396-405 - [c86]Giuliano Antoniol, Kamel Ayari, Massimiliano Di Penta, Foutse Khomh, Yann-Gaël Guéhéneuc:
Is it a bug or an enhancement?: a text-based approach to classify change requests. CASCON 2018: 2-16 - [c85]Amine Barrak, Marc-André Laverdière, Foutse Khomh, Le An, Ettore Merlo:
Just-in-time detection of protection-impacting changes on WordPress and MediaWiki. CASCON 2018: 178-188 - [c84]Rodrigo Morales, Rubén Saborido, Foutse Khomh, Francisco Chicano, Giuliano Antoniol:
EARMO: an energy-aware refactoring approach for mobile apps. ICSE 2018: 59 - [c83]Aiko Yamashita, Fábio Petrillo, Foutse Khomh, Yann-Gaël Guéhéneuc:
Developer interaction traces backed by IDE screen recordings from think aloud sessions. MSR 2018: 50-53 - [c82]Houssem Ben Braiek, Foutse Khomh, Bram Adams:
The open-closed principle of modern machine learning frameworks. MSR 2018: 353-363 - [c81]Naoures Ghrairi, Segla Kpodjedo, Amine Barrak, Fábio Petrillo, Foutse Khomh:
The State of Practice on Virtual Reality (VR) Applications: An Exploratory Study on Github and Stack Overflow. QRS 2018: 356-366 - [c80]Mohab Aly, Foutse Khomh, Soumaya Yacout:
Kubernetes or OpenShift? Which Technology Best Suits Eclipse Hono IoT Deployments. SOCA 2018: 113-120 - [c79]Foutse Khomh, Yann-Gaël Guéhéneuc:
Design patterns impact on software quality: Where are the theories? SANER 2018: 15-25 - [c78]Sarah Fakhoury, Venera Arnaoudova, Cedric Noiseux, Foutse Khomh, Giuliano Antoniol:
Keep it simple: Is deep learning good for linguistic smell detection? SANER 2018: 602-611 - [e4]Foutse Khomh, Chanchal K. Roy, Janet Siegmund:
Proceedings of the 26th Conference on Program Comprehension, ICPC 2018, Gothenburg, Sweden, May 27-28, 2018. ACM 2018 [contents] - [i11]Rodrigo Morales, Foutse Khomh, Giuliano Antoniol:
Automated Refactoring: Can They Pass The Turing Test? CoRR abs/1808.04352 (2018) - [i10]Mohab Aly, Foutse Khomh, Yann-Gaël Guéhéneuc, Hironori Washizaki, Soumaya Yacout:
Is Fragmentation a Threat to the Success of the Internet of Things? CoRR abs/1808.07355 (2018) - [i9]Houssem Ben Braiek, Foutse Khomh:
On Testing Machine Learning Programs. CoRR abs/1812.02257 (2018) - 2017
- [j16]Rodrigo Morales, Zéphyrin Soh, Foutse Khomh, Giuliano Antoniol, Francisco Chicano:
On the use of developers' context for automatic refactoring of software anti-patterns. J. Syst. Softw. 128: 236-251 (2017) - [j15]Mbarka Soualhia, Foutse Khomh, Sofiène Tahar:
Task Scheduling in Big Data Platforms: A Systematic Literature Review. J. Syst. Softw. 134: 170-189 (2017) - [j14]Foutse Khomh, David Lo, Michael W. Godfrey:
Guest editor's introduction to the Special Issue on Source Code Analysis and Manipulation (SCAM 2015). J. Softw. Evol. Process. 29(12) (2017) - [j13]Latifa Guerrouj, Zeinab Azadeh Kermansaravi, Venera Arnaoudova, Benjamin C. M. Fung, Foutse Khomh, Giuliano Antoniol, Yann-Gaël Guéhéneuc:
Investigating the relation between lexical smells and change- and fault-proneness: an empirical study. Softw. Qual. J. 25(3): 641-670 (2017) - [c77]Fiorella Zampetti, Cedric Noiseux, Giuliano Antoniol, Foutse Khomh, Massimiliano Di Penta:
Recommending when Design Technical Debt Should be Self-Admitted. ICSME 2017: 216-226 - [c76]Marco Castelluccio, Le An, Foutse Khomh:
Is it Safe to Uplift this Patch?: An Empirical Study on Mozilla Firefox. ICSME 2017: 411-421 - [c75]Foundjem Armstrong, Foutse Khomh, Bram Adams:
Broadcast vs. Unicast Review Technology: Does It Matter? ICST 2017: 219-229 - [c74]Rubén Saborido, Foutse Khomh, Giuliano Antoniol, Yann-Gaël Guéhéneuc:
Comprehension of ads-supported and paid Android applications: are they different? ICPC 2017: 143-153 - [c73]Gias Uddin, Foutse Khomh:
Automatic summarization of API reviews. ASE 2017: 159-170 - [c72]Gias Uddin, Foutse Khomh:
Opiner: an opinion search and summarization engine for APIs. ASE 2017: 978-983 - [c71]Aiko Yamashita, S. Amirhossein Abtahizadeh, Foutse Khomh, Yann-Gaël Guéhéneuc:
Software evolution and quality data from controlled, multiple, industrial case studies. MSR 2017: 507-510 - [c70]John Businge, Simon Kawuma, Engineer Bainomugisha, Foutse Khomh, Evarist Nabaasa:
Code Authorship and Fault-proneness of Open-Source Android Applications: An Empirical Study. PROMISE 2017: 33-42 - [c69]Fábio Petrillo, Hyan Mandian, Aiko Yamashita, Foutse Khomh, Yann-Gaël Guéhéneuc:
How Do Developers Toggle Breakpoints? Observational Studies. QRS 2017: 285-295 - [c68]Le An, Ons Mlouki, Foutse Khomh, Giuliano Antoniol:
Stack Overflow: A code laundering platform? SANER 2017: 283-293 - [c67]Amir Saboury, Pooya Musavi, Foutse Khomh, Giulio Antoniol:
An empirical study of code smells in JavaScript projects. SANER 2017: 294-305 - [i8]Rubén Saborido, Foutse Khomh, Yann-Gaël Guéhéneuc, Giuliano Antoniol:
Comprehension of Ads-supported and Paid Android Applications: Are They Different? CoRR abs/1703.03017 (2017) - [i7]Le An, Ons Mlouki, Foutse Khomh, Giuliano Antoniol:
Stack Overflow: A Code Laundering Platform? CoRR abs/1703.03897 (2017) - [i6]Rubén Saborido, Foutse Khomh, Abram Hindle, Enrique Alba:
An App Performance Optimization Advisor for Mobile Device App Marketplaces. CoRR abs/1709.04916 (2017) - [i5]Marco Castelluccio, Le An, Foutse Khomh:
Is It Safe to Uplift This Patch? An Empirical Study on Mozilla Firefox. CoRR abs/1709.08852 (2017) - 2016
- [j12]Shaohua Wang, Foutse Khomh, Ying Zou:
Improving bug management using correlations in crash reports. Empir. Softw. Eng. 21(2): 337-367 (2016) - [j11]Fehmi Jaafar, Yann-Gaël Guéhéneuc, Sylvie Hamel, Foutse Khomh, Mohammad Zulkernine:
Evaluating the impact of design pattern and anti-pattern dependencies on changes and faults. Empir. Softw. Eng. 21(3): 896-931 (2016) - [j10]Wei Wu, Foutse Khomh, Bram Adams, Yann-Gaël Guéhéneuc, Giuliano Antoniol:
An exploratory study of api changes and usages based on apache and eclipse ecosystems. Empir. Softw. Eng. 21(6): 2366-2412 (2016) - [c66]Latifa Guerrouj, Olga Baysal, David Lo, Foutse Khomh:
Software analytics: challenges and opportunities. ICSE (Companion Volume) 2016: 902-903 - [c65]Hironori Washizaki, Yann-Gaël Guéhéneuc, Foutse Khomh:
A Taxonomy for Program Metamodels in Program Reverse Engineering. ICSME 2016: 44-55 - [c64]Béchir Bani, Foutse Khomh, Yann-Gaël Guéhéneuc:
A Study of the Energy Consumption of Databases and Cloud Patterns. ICSOC 2016: 606-614 - [c63]Pooya Musavi, Bram Adams, Foutse Khomh:
Experience Report: An Empirical Study of API Failures in OpenStack Cloud Environments. ISSRE 2016: 424-434 - [c62]Fábio Petrillo, Zéphyrin Soh, Foutse Khomh, Marcelo Soares Pimenta, Carla Maria Dal Sasso Freitas, Yann-Gaël Guéhéneuc:
Understanding interactive debugging with Swarm Debug Infrastructure. ICPC 2016: 1-4 - [c61]Fábio Petrillo, Zéphyrin Soh, Foutse Khomh, Marcelo Pimenta, Carla M. D. S. Freitas, Yann-Gaël Guéhéneuc:
Towards Understanding Interactive Debugging. QRS 2016: 152-163 - [c60]Rodrigo Morales, Aminata Sabane, Pooya Musavi, Foutse Khomh, Francisco Chicano, Giuliano Antoniol:
Finding the Best Compromise Between Design Quality and Testing Effort During Refactoring. SANER 2016: 24-35 - [c59]Bilal Karasneh, Michel R. V. Chaudron, Foutse Khomh, Yann-Gaël Guéhéneuc:
Studying the Relation between Anti-Patterns in Design Models and in Source Code. SANER 2016: 36-45 - [c58]Ons Mlouki, Foutse Khomh, Giuliano Antoniol:
On the Detection of Licenses Violations in the Android Ecosystem. SANER 2016: 382-392 - [c57]Zéphyrin Soh, Aiko Yamashita, Foutse Khomh, Yann-Gaël Guéhéneuc:
Do Code Smells Impact the Effort of Different Maintenance Programming Activities? SANER 2016: 393-402 - [c56]Rubén Saborido, Giovanni Beltrame, Foutse Khomh, Enrique Alba, Giuliano Antoniol:
Optimizing User Experience in Choosing Android Applications. SANER 2016: 438-448 - [i4]Rodrigo Morales, Rubén Saborido, Foutse Khomh, Francisco Chicano, Giuliano Antoniol:
Anti-patterns and the energy efficiency of Android applications. CoRR abs/1610.05711 (2016) - 2015
- [j9]Foutse Khomh, Bram Adams, Tejinder Dhaliwal, Ying Zou:
Understanding the impact of rapid releases on software quality - The case of firefox. Empir. Softw. Eng. 20(2): 336-373 (2015) - [j8]Mika V. Mäntylä, Bram Adams, Foutse Khomh, Emelie Engström, Kai Petersen:
On rapid releases and software testing: a case study and a semi-systematic literature review. Empir. Softw. Eng. 20(5): 1384-1425 (2015) - [j7]Bipin Upadhyaya, Ying Zou, Foutse Khomh:
An approach to extract RESTful services from web applications. Int. J. Bus. Process. Integr. Manag. 7(3): 213-227 (2015) - [j6]Bram Adams, Stephany Bellomo, Christian Bird, Tamara Marshall-Keim, Foutse Khomh, Kim Moir:
The Practice and Future of Release Engineering: A Roundtable with Three Release Engineers. IEEE Softw. 32(2): 42-49 (2015) - [c55]Zéphyrin Soh, Thomas Drioul, Pierre-Antoine Rappe, Foutse Khomh, Yann-Gaël Guéhéneuc, Naji Habra:
Noises in Interaction Traces Data and Their Impact on Previous Research Studies. ESEM 2015: 1-10 - [c54]Mbarka Soualhia, Foutse Khomh, Sofiène Tahar:
Predicting Scheduling Failures in the Cloud: A Case Study with Google Clusters and Hadoop on Amazon EMR. HPCC/CSS/ICESS 2015: 58-65 - [c53]Bram Adams, Stephany Bellomo, Christian Bird, Foutse Khomh, Kim Moir:
3rd International Workshop on Release Engineering (RELENG 2015). ICSE (2) 2015: 995-996 - [c52]S. Amirhossein Abtahizadeh, Foutse Khomh, Yann-Gaël Guéhéneuc:
How green are cloud patterns? IPCCC 2015: 1-8 - [c51]Mbarka Soualhia, Foutse Khomh, Sofiène Tahar:
ATLAS: An AdapTive faiLure-Aware Scheduler for Hadoop. IPCCC 2015: 1-8 - [c50]Le An, Foutse Khomh:
An Empirical Study of Crash-inducing Commits in Mozilla Firefox. PROMISE 2015: 5:1-5:10 - [c49]Le An, Foutse Khomh:
An Empirical Study of Highly Impactful Bugs in Mozilla Projects. QRS 2015: 262-271 - [c48]Le An, Foutse Khomh:
Challenges and Issues of Mining Crash Reports. SWAN@SANER 2015: 5-8 - [c47]Rodrigo Morales, Shane McIntosh, Foutse Khomh:
Do code review practices impact design quality? A case study of the Qt, VTK, and ITK projects. SANER 2015: 171-180 - [e3]Bram Adams, Stephany Bellomo, Christian Bird, Foutse Khomh, Kim Moir:
3rd IEEE/ACM International Workshop on Release Engineering, RELENG 2015, Florence, Italy, May 19, 2015. IEEE Computer Society 2015, ISBN 978-1-4673-7070-7 [contents] - [e2]Michael W. Godfrey, David Lo, Foutse Khomh:
15th IEEE International Working Conference on Source Code Analysis and Manipulation, SCAM 2015, Bremen, Germany, September 27-28, 2015. IEEE Computer Society 2015, ISBN 978-1-4673-7529-0 [contents] - [i3]Mbarka Soualhia, Foutse Khomh, Sofiène Tahar:
Predicting Scheduling Failures in the Cloud. CoRR abs/1507.03562 (2015) - [i2]Mbarka Soualhia, Foutse Khomh, Sofiène Tahar:
ATLAS: An Adaptive Failure-aware Scheduler for Hadoop. CoRR abs/1511.01446 (2015) - [i1]Rubén Saborido, Venera Arnaoudova, Giovanni Beltrame, Foutse Khomh, Giuliano Antoniol:
On the impact of sampling frequency on software energy measurements. PeerJ Prepr. 3: e1219 (2015) - 2014
- [j5]Feng Zhang, Foutse Khomh, Ying Zou, Ahmed E. Hassan:
An empirical study of the effect of file editing patterns on software quality. J. Softw. Evol. Process. 26(11): 996-1029 (2014) - [c46]Geoffrey Hecht, Benjamin Jose-Scheidt, Clement De Figueiredo, Naouel Moha, Foutse Khomh:
An Empirical Study of the Impact of Cloud Patterns on Quality of Service (QoS). CloudCom 2014: 278-283 - [c45]Shuai Xie, Foutse Khomh, Ying Zou, Iman Keivanloo:
An empirical study on the fault-proneness of clone migration in clone genealogies. CSMR-WCRE 2014: 94-103 - [c44]Mini Shridhar, Bram Adams, Foutse Khomh:
A qualitative analysis of software build system changes and build ownership styles. ESEM 2014: 29:1-29:10 - [c43]Yujuan Jiang, Bram Adams, Foutse Khomh, Daniel M. Germán:
Tracing back the history of commits in low-tech reviewing environments: a case study of the Linux kernel. ESEM 2014: 51:1-51:10 - [c42]Noureddine Kerzazi, Foutse Khomh:
Factors impacting rapid releases: an industrial case study. ESEM 2014: 61:1-61:8 - [c41]Noureddine Kerzazi, Foutse Khomh, Bram Adams:
Why Do Automated Builds Break? An Empirical Study. ICSME 2014: 41-50 - [c40]Fehmi Jaafar, Foutse Khomh, Yann-Gaël Guéhéneuc, Mohammad Zulkernine:
Anti-pattern Mutations and Fault-proneness. QSIC 2014: 246-255 - [c39]Le An, Foutse Khomh, Bram Adams:
Supplementary Bug Fixes vs. Re-opened Bugs. SCAM 2014: 205-214 - [c38]Francis Palma, Le An, Foutse Khomh, Naouel Moha, Yann-Gaël Guéhéneuc:
Investigating the Change-Proneness of Service Patterns and Antipatterns. SOCA 2014: 1-8 - [c37]Foutse Khomh:
On improving the dependability of cloud applications with fault-tolerance. WICSA Companion 2014: 2:1-2:3 - 2013
- [j4]Fehmi Jaafar, Yann-Gaël Guéhéneuc, Sylvie Hamel, Foutse Khomh:
Analysing Anti-patterns Static Relationships with Design Patterns. Electron. Commun. Eur. Assoc. Softw. Sci. Technol. 59 (2013) - [j3]Liliane Barbour, Foutse Khomh, Ying Zou:
An empirical study of faults in late propagation clone genealogies. J. Softw. Evol. Process. 25(11): 1139-1165 (2013) - [c36]Bram Adams, Christian Bird, Foutse Khomh, Kim Moir:
1st international workshop on release engineering (RELENG 2013). ICSE 2013: 1545-1546 - [c35]Mika Mäntylä, Foutse Khomh, Bram Adams, Emelie Engström, Kai Petersen:
On Rapid Releases and Software Testing. ICSM 2013: 20-29 - [c34]Seyyed Ehsan Salamati Taba, Foutse Khomh, Ying Zou, Ahmed E. Hassan, Meiyappan Nagappan:
Predicting Bugs Using Antipatterns. ICSM 2013: 270-279 - [c33]Feng Zhang, Audris Mockus, Ying Zou, Foutse Khomh, Ahmed E. Hassan:
How Does Context Affect the Distribution of Software Maintainability Metrics? ICSM 2013: 350-359 - [c32]Shuai Xie, Foutse Khomh, Ying Zou:
An empirical study of the fault-proneness of clone mutation and clone migration. MSR 2013: 149-158 - [c31]Shaohua Wang, Foutse Khomh, Ying Zou:
Improving bug localization using correlations in crash reports. MSR 2013: 247-256 - [c30]Zéphyrin Soh, Foutse Khomh, Yann-Gaël Guéhéneuc, Giuliano Antoniol:
Towards understanding how developers spend their effort during maintenance activities. WCRE 2013: 152-161 - [c29]Fehmi Jaafar, Yann-Gaël Guéhéneuc, Sylvie Hamel, Foutse Khomh:
Mining the relationship between anti-patterns dependencies and fault-proneness. WCRE 2013: 351-360 - [c28]Zéphyrin Soh, Foutse Khomh, Yann-Gaël Guéhéneuc, Giuliano Antoniol, Bram Adams:
On the effect of program exploration on maintenance tasks. WCRE 2013: 391-400 - [e1]Bram Adams, Christian Bird, Foutse Khomh, Kim Moir:
Proceedings of the 1st International Workshop on Release Engineering, RELENG 2013, San Francisco, California, USA, May 20, 2013. IEEE Computer Society 2013, ISBN 978-1-4673-6441-6 [contents] - 2012
- [j2]Foutse Khomh, Massimiliano Di Penta, Yann-Gaël Guéhéneuc, Giuliano Antoniol:
An exploratory study of the impact of antipatterns on class change- and fault-proneness. Empir. Softw. Eng. 17(3): 243-275 (2012) - [c27]Tejinder Dhaliwal, Foutse Khomh, Ying Zou, Ahmed E. Hassan:
Recovering commit dependencies for selective code integration in software product lines. ICSM 2012: 202-211 - [c26]Foutse Khomh, Hao Yuan, Ying Zou:
Adapting Linux for mobile platforms: An empirical study of Android. ICSM 2012: 629-632 - [c25]Foutse Khomh, Tejinder Dhaliwal, Ying Zou, Bram Adams:
Do faster releases improve software quality? An empirical case study of Mozilla Firefox. MSR 2012: 179-188 - [c24]Bipin Upadhyaya, Foutse Khomh, Ying Zou:
Extracting RESTful services from Web applications. SOCA 2012: 1-4 - [c23]Bipin Upadhyaya, Foutse Khomh, Ying Zou, Alex Lau, Joanna Ng:
A concept analysis approach for guiding users in service discovery. SOCA 2012: 1-8 - [c22]Feng Zhang, Foutse Khomh, Ying Zou, Ahmed E. Hassan:
An Empirical Study on Factors Impacting Bug Fixing Time. WCRE 2012: 225-234 - [c21]Thierry Lavoie, Foutse Khomh, Ettore Merlo, Ying Zou:
Inferring Repository File Structure Modifications Using Nearest-Neighbor Clone Detection. WCRE 2012: 325-334 - [c20]Daniele Romano, Paulius Raila, Martin Pinzger, Foutse Khomh:
Analyzing the Impact of Antipatterns on Change-Proneness Using Fine-Grained Source Code Changes. WCRE 2012: 437-446 - [c19]Feng Zhang, Foutse Khomh, Ying Zou, Ahmed E. Hassan:
An Empirical Study of the Effect of File Editing Patterns on Software Quality. WCRE 2012: 456-465 - 2011
- [j1]Foutse Khomh, Stéphane Vaucher, Yann-Gaël Guéhéneuc, Houari A. Sahraoui:
BDTEX: A GQM-based Bayesian approach for the detection of antipatterns. J. Syst. Softw. 84(4): 559-572 (2011) - [c18]Marwen Abbes, Foutse Khomh, Yann-Gaël Guéhéneuc, Giuliano Antoniol:
An Empirical Study of the Impact of Two Antipatterns, Blob and Spaghetti Code, on Program Comprehension. CSMR 2011: 181-190 - [c17]Foutse Khomh, Brian Chan, Ying Zou, Anand Sinha, Dave Dietz:
Predicting post-release defects using pre-release field testing results. ICSM 2011: 253-262 - [c16]Liliane Barbour, Foutse Khomh, Ying Zou:
Late propagation in software clones. ICSM 2011: 273-282 - [c15]Tejinder Dhaliwal, Foutse Khomh, Ying Zou:
Classifying field crash reports for fixing bugs: A case study of Mozilla Firefox. ICSM 2011: 333-342 - [c14]Hua Xiao, Bipin Upadhyaya, Foutse Khomh, Ying Zou, Joanna Ng, Alex Lau:
An Automatic Approach for Extracting Process Knowledge from the Web. ICWS 2011: 315-322 - [c13]Xulin Zhao, Foutse Khomh, Ying Zou:
Improving the Modifiability of the Architecture of Business Applications. QSIC 2011: 176-185 - [c12]Foutse Khomh, Brian Chan, Ying Zou, Ahmed E. Hassan:
An Entropy Evaluation Approach for Triaging Field Crashes: A Case Study of Mozilla Firefox. WCRE 2011: 261-270 - 2010
- [c11]Rocco Oliveto, Foutse Khomh, Giuliano Antoniol, Yann-Gaël Guéhéneuc:
Numerical Signatures of Antipatterns: An Approach Based on B-Splines. CSMR 2010: 248-251 - [c10]Nicolas Haderer, Foutse Khomh, Giuliano Antoniol:
SQUANER: A framework for monitoring the quality of software systems. ICSM 2010: 1-4 - [c9]Salima Hassaine, Foutse Khomh, Yann-Gaël Guéhéneuc, Sylvie Hamel:
IDS: An Immune-Inspired Approach for the Detection of Software Design Smells. QUATIC 2010: 343-348
2000 – 2009
- 2009
- [c8]Foutse Khomh, Yann-Gaël Guéhéneuc, Giuliano Antoniol:
Playing roles in design patterns: An empirical descriptive and analytic study. ICSM 2009: 83-92 - [c7]Foutse Khomh, Stéphane Vaucher, Yann-Gaël Guéhéneuc, Houari A. Sahraoui:
A Bayesian Approach for the Detection of Code and Design Smells. QSIC 2009: 305-314 - [c6]Foutse Khomh, Massimiliano Di Penta, Yann-Gaël Guéhéneuc:
An Exploratory Study of the Impact of Code Smells on Software Change-proneness. WCRE 2009: 75-84 - [c5]Stéphane Vaucher, Foutse Khomh, Naouel Moha, Yann-Gaël Guéhéneuc:
Tracking Design Smells: Lessons from a Study of God Classes. WCRE 2009: 145-154 - [c4]Foutse Khomh:
SQUAD: Software Quality Understanding through the Analysis of Design. WCRE 2009: 303-306 - 2008
- [c3]Giuliano Antoniol, Kamel Ayari, Massimiliano Di Penta, Foutse Khomh, Yann-Gaël Guéhéneuc:
Is it a bug or an enhancement?: a text-based approach to classify change requests. CASCON 2008: 23 - [c2]Foutse Khomh, Yann-Gaël Guéhéneuc:
Do Design Patterns Impact Software Quality Positively? CSMR 2008: 274-278 - [c1]Naouel Moha, Foutse Khomh, Yann-Gaël Guéhéneuc, Laurence Duchien, Anne-Françoise Le Meur:
Génération automatique d'algorithmes de détection des défauts de conception. LMO 2008: 93-106
Coauthor Index
Giuliano Antoniol
aka: Giulio Antoniol
aka: Giulio Antoniol
[j114] [j104] [j98] [j91] [j90] [c146] [i122] [i114] [j87] [j81] [j74] [j72] [c141] [c138] [i99] [i97] [i86] [i80] [j66] [j61] [j59] [c133] [c127] [c122] [i73] [i72] [i71] [i70] [i56] [i55] [c116] [c115] [c114] [c113] [e9] [i41] [i37] [i36] [i35] [i25] [i24] [j42] [c107] [c102] [j29] [j28] [j27] [j25] [j23] [j21] [j17] [c88] [c86] [c84] [c78] [i11] [j16] [j13] [c77] [c74] [c68] [c67] [i8] [i7] [j10] [c60] [c58] [c56] [i4] [i1] [c30] [c28] [j2] [c18] [c11] [c10] [c8] [c3]
[c143] [j65] [j56] [c125] [j54] [j52] [i40] [i28] [j40] [j39] [c110] [d1] [i23] [j31] [j30] [c98] [c96] [c95] [c93] [c91] [p1] [e6] [i21] [i20] [i19] [i15] [i14] [j27] [j26] [j25] [j20] [c86] [c83] [c79] [i10] [j13] [c74] [c71] [c69] [i8] [j11] [j10] [c65] [c64] [c62] [c61] [c59] [c57] [c55] [c52] [c40] [c38] [j4] [c30] [c29] [c28] [j2] [j1] [c18] [c11] [c9] [c8] [c7] [c6] [c5] [c3] [c2] [c1]
[j115] [j114] [j112] [j111] [i128] [j105] [j104] [j103] [j100] [j97] [j95] [c155] [i123] [i122] [i120] [i115] [i114] [i109] [i105] [i102] [i100] [j86] [j84] [j75] [c140] [c138] [i97] [i93] [i91] [i88] [i85] [i84] [i82] [i74] [j67] [j66] [j57] [c131] [c129] [i62] [i61] [i60] [i54] [i53] [c120] [c118] [c117] [i45] [i39] [i38] [i36] [i30] [i27] [i25]
Chanchal Kumar Roy
aka: Chanchal K. Roy
aka: Chanchal K. Roy
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