Foutse Khomh

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Membre Académique Associé
Foutse Khomh
Professeur titulaire, École Polytechnique de Montréal
Foutse Khomh

Foutse Khomh est professeur titulaire au département de génie informatique et logiciel de l’École Polytechnique de Montréal. Il est aussi titulaire de la Chaire de recherche FRQ-IVADO en assurance qualité des logiciels d’apprentissage automatique. Il a obtenu un doctorat en Informatique de l’Université de Montréal en 2011, avec le prix d’excellence. Il est récipiendaire du prix CS-Can/Info-Can jeunes chercheurs exceptionnels en informatique (Outstanding Young Computer Science Researcher Prize en anglais), pour l’année 2019. Ses intérêts de recherche incluent la maintenance et l’évolution des logiciels, l’ingénierie des systèmes intégrant l’apprentissage automatique, l’ingénierie infonuagique, et l’intelligence artificielle sûre et robuste. Ses travaux de recherches ont reçu 3 prix pour des articles jugées les plus influents sur une décennie (10-Year Most Influential Paper Awards) et 6 prix de meilleurs articles. Il est membre du comité de programme de plusieurs conférences internationales et arbitre pour plusieurs journaux majeurs, notamment FSE, EMSE, TSC, TSE et TOSEM. Il est président du programme pour les événements satellites à SANER 2015, co-président du comité de programme des conférences SCAM 2015, ICSME 2018, PROMISE 2019, et ICPC 2019, general chair des conférences ICPC 2018, SCAM 2020, et SANER 2020. Il est membre du comité de pilotage (steering committee) des conférences SANER (président), MSR, PROMISE, ICPC (président) et ICSME (vice-président). Il a initié et co-organisé le Software Engineering for Machine Learning Applications (SEMLA) international symposium et la série d’ateliers RELENG (Release Engineering). Il est membre du comité de rédaction de plusieurs revues internationales.

Publications

2021-11

An empirical study of IoT topics in IoT developer discussions on Stack Overflow
Gias Uddin, Fatima Sabir, Yann-Gaël Guéhéneuc, Omar Alam and Foutse Khomh
Empirical Software Engineering
(2021-11-01)
link.springer.com
The forgotten role of search queries in IR-based bug localization: an empirical study
Mohammad Masudur Rahman, Foutse Khomh, Shamima Yeasmin and Chanchal K. Roy
Improved retrieval of programming solutions with code examples using a multi-featured score
Rodrigo F. Silva, M. Masudur Rahman, Carlos Eduardo de Carvalho Dantas, Chanchal K. Roy, Foutse Khomh and Marcelo de Almeida Maia

2021-09

The challenge of reproducible ML: an empirical study on the impact of bugs
Emilio Rivera-Landos, Foutse Khomh and Amin Nikanjam
arXiv: Software Engineering
(2021-09-09)
arxiv.orgPDF
Failure Analysis of Hadoop Schedulers using an Integration of Model Checking and Simulation
Mbarka Soualhia, Foutse Khomh and Sofiene Tahar
Electronic Proceedings in Theoretical Computer Science
(2021-09-06)
dx.doi.org[LATEST on arXiv preprint arXiv:2109.04196 (2021-09-07)]

2021-07

Clones in Deep Learning Code: What, Where, and Why?
Hadhemi Jebnoun, Saidur Rahman, Foutse Khomh and Biruk Asmare Muse
arXiv preprint arXiv:2107.13614
(2021-07-28)
128.84.4.18PDF
Models of Computational Profiles to Study the Likelihood of DNN Metamorphic Test Cases
Ettore Merlo, Mira Marhaba, Foutse Khomh, Houssem Ben Braiek and Giuliano Antoniol
arXiv preprint arXiv:2107.13491
(2021-07-28)
dblp.uni-trier.dePDF
How to Certify Machine Learning Based Safety-critical Systems? A Systematic Literature Review
Florian Tambon, Gabriel Laberge, Le An, Amin Nikanjam, Paulina Stevia Nouwou Mindom, Yann Pequignot, Foutse Khomh, Giulio Antoniol, Ettore Merlo and François Laviolette
arXiv preprint arXiv:2107.12045
(2021-07-26)
dblp.uni-trier.dePDF
HOMRS: High Order Metamorphic Relations Selector for Deep Neural Networks.
Florian Tambon, Giulio Antoniol and Foutse Khomh
arXiv preprint arXiv:2107.04863
(2021-07-10)
dblp.uni-trier.dePDF
Design Smells in Deep Learning Programs: An Empirical Study.
Amin Nikanjam and Foutse Khomh
arXiv preprint arXiv:2107.02279
(2021-07-05)
dblp.uni-trier.dePDF
Why do builds fail?—A conceptual replication study
Amine Barrak, Ellis E. Eghan, Bram Adams and Foutse Khomh
Journal of Systems and Software
(2021-07-01)
www.sciencedirect.com

2021-06

Assessing Developer Expertise from the Statistical Distribution of Programming Syntax Patterns
Arghavan Moradi Dakhel, Michel C. Desmarais and Foutse Khomh
EASE 2021
(2021-06-21)
doi.org
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
Mohab Aly, Foutse Khomh and Soumaya Yacout
IOT 2021
(2021-06-01)
www.sciencedirect.com

2021-05

Automatic Fault Detection for Deep Learning Programs Using Graph Transformations.
Amin Nikanjam, Houssem Ben Braiek, Mohammad Mehdi Morovati and Foutse Khomh
arXiv preprint arXiv:2105.08095
(2021-05-17)
dblp.uni-trier.dePDF
SWAT tool at the SBST 2021 Tool Competition
Dmytro Humeniuk, Giuliano Antoniol and Foutse Khomh
2021 IEEE/ACM 14th International Workshop on Search-Based Software Testing (SBST)
(2021-05-01)
dblp.uni-trier.de
Data Driven Testing of Cyber Physical Systems
Dmytro Humeniuk, Giuliano Antoniol and Foutse Khomh
2021 IEEE/ACM 14th International Workshop on Search-Based Software Testing (SBST)
(2021-05-01)
doi.org[Also on arXiv preprint arXiv:2102.11491 (2021-02-23)]

2021-04

Automatic API Usage Scenario Documentation from Technical Q&A Sites
Gias Uddin, Foutse Khomh and Chanchal K. Roy
ACM Transactions on Software Engineering and Methodology
(2021-04-23)
dl.acm.org[Also on arXiv preprint arXiv:2102.08502 (2021-02-16)]
Understanding How and Why Developers Seek and Analyze API-Related Opinions
Gias Uddin, Olga Baysal, Latifa Guerrouj and Foutse Khomh
IEEE Transactions on Software Engineering
(2021-04-01)
espace2.etsmtl.caPDF[Also on arXiv preprint arXiv:2102.08495 (2021-02-16)]

2021-03

Investigating Design Anti-pattern and Design Pattern Mutations and Their Change- and Fault-proneness
Zeinab, Kermansaravi, Saidur Rahman, Foutse Khomh, Fehmi Jaafar and Yann-Gael Gueheneuc
arXiv preprint arXiv:2104.00058
(2021-03-31)
ui.adsabs.harvard.eduPDF
Summarizing Relevant Parts from Technical Videos
Mahmood Vahedi, Mohammad Masudur Rahman, Foutse Khomh, Gias Uddin and Giuliano Antoniol
SANER 2021
(2021-03-01)
dblp.uni-trier.de
Automatic Mining of Opinions Expressed About APIs in Stack Overflow
Gias Uddin and Foutse Khomh
IEEE Transactions on Software Engineering
(2021-03-01)
doi.org

2021-02

Mining API Usage Scenarios from Stack Overflow
Gias Uddin, Foutse Khomh and Chanchal K Roy
arXiv preprint arXiv:2102.08874
(2021-02-17)
ui.adsabs.harvard.eduPDF
Are Multi-Language Design Smells Fault-Prone? An Empirical Study
Mouna Abidi, Saidur Rahman, Moses Openja and Foutse Khomh
ACM Transactions on Software Engineering and Methodology
(2021-02-11)
dl.acm.org[Also on arXiv: Software Engineering (2020-10-27)]

2021-01

Investigating design anti-pattern and design pattern mutations and their change- and fault-proneness
Zeinab Azadeh Kermansaravi, Saidur Rahman, Foutse Khomh, Fehmi Jaafar and Yann-Gaël Guéhéneuc
Empirical Software Engineering
(2021-01-16)
link.springer.com
Is Late Propagation a Harmful Code Clone Evolutionary Pattern? An Empirical Study.
Osama Ehsan, Liliane Barbour, Foutse Khomh and Ying Zou
Code Clone Analysis
(2021-01-01)
dblp.uni-trier.de
Faults in Deep Reinforcement Learning Programs: A Taxonomy and A Detection Approach.
Amin Nikanjam, Mohammad Mehdi Morovati, Foutse Khomh and Houssem Ben Braiek
arXiv: Software Engineering
(2021-01-01)
ui.adsabs.harvard.eduPDF

2020-10

Are Multi-language Design Smells Prevalent? An Empirical Study.
Mouna Abidi, Md. Saidur Rahman, Moses Openja and Foutse Khomh
arXiv preprint arXiv:2010.14331
(2020-10-27)
dblp.uni-trier.dePDF
On the use of C# Unsafe Code Context: An Empirical Study of Stack Overflow
Ehsan Firouzi, Ashkan Sami, Foutse Khomh and Gias Uddin
ESEM 2020
(2020-10-05)
dl.acm.org

2020-09

An Empirical Study of C++ Vulnerabilities in Crowd-Sourced Code Examples
Morteza Verdi, Ashkan Sami, Jafar Akhondali, Foutse Khomh, Gias Uddin and Alireza Karami Motlagh
IEEE Transactions on Software Engineering
(2020-09-11)
ieeexplore.ieee.org
Why are Some Bugs Non-Reproducible? : –An Empirical Investigation using Data Fusion–
Mohammad Masudur Rahman, Foutse Khomh and Marco Castelluccio
Analysis of Modern Release Engineering Topics : – A Large-Scale Study using StackOverflow –
Moses Openja, Bram Adams and Foutse Khomh
ICSM 2020
(2020-09-01)
doi.org
Practitioners’ insights on machine-learning software engineering design patterns: a preliminary study
Hironori Washizaki, Hironori Takeuchi, Foutse Khomh, Naotake Natori, Takuo Doi and Satoshi Okuda
ICSM 2020
(2020-09-01)
doi.org

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