In the rapidly evolving landscape of software development, Large Language Models (LLM) have emerged as powerful tools that can significantly impact the way software code is written, reviewed, and optimized, making them invaluable resources for programmers. They offer developers the ability to leverage pre-trained knowledge and tap into vast code repositories, enabling faster development cycles and reducing the time spent on repetitive or mundane coding tasks. However, while these models offer substantial benefits, their adoption also presents multiple challenges. For example, they might generate code snippets that are syntactically correct but functionally flawed, requiring human review and validation. Moreover, the ethical considerations surrounding these models, such as biases in the training data, should be carefully addressed to ensure fair and inclusive software development practices. This talk will provide an overview and reflection on some of these challenges, present some preliminary solutions, and discuss opportunities for predictive models and data analytics.

Foutse Khomh is a Full Professor, a Canada CIFAR AI Chair, an FRQ-IVADO Research Chair, and an NSERC Arthur B. McDonald Fellow at Polytechnique Montréal, where he heads the SWAT Lab (http://swat.polymtl.ca/). He received a Ph.D. in Software Engineering from the University of Montreal in 2011. His research interests include software maintenance and evolution, cloud engineering, machine learning systems engineering, empirical software engineering, software analytics, and dependable and trustworthy AI/ML. He has published over 200 conferences and journal papers. His work has received four ten-year Most Influential Paper (MIP) Awards, and six Best/Distinguished Paper Awards. He has served on the program committees of several international conferences including ICSE, FSE, ICSM(E), SANER, MSR, ICPC, SCAM, ESEM and has reviewed for top international journals such as SQJ, JSS, EMSE, TSE, and TOSEM. He is program chair for Satellite Events at SANER 2015, program co-chair of SCAM 2015, ICSME 2018, PROMISE 2019, ICPC 2019, and SSBSE 2024, and general chair of ICPC 2018, SCAM 2020, and general co-chair of SANER 2020. He initiated and co-organized the Software Engineering for Machine Learning Applications (SEMLA) symposium. He is one of the organizers of the RELENG workshop series (http://releng.polymtl.ca) and Associate Editor for IEEE Software, EMSE, and JSEP.