The REALISE Lab had an amazing experience at the CREATE SE4AI retreat in Kingston this July 2024. The CREATE SE4AI is a training initiative focused on the development, deployment, and servicing of artificial intelligence-based software systems. The retreat provided us with a wonderful opportunity to connect with researchers and professors from the program, sharing our research ideas and experiences in person. We spent a day and night at the scenic Delta Inn hotel surrounded by beautiful landscapes. The retreat was highlighted by engaging presentations from students, including Rachna from our lab, who shared her work on her recently published paper at MSR 2024. The evening was capped off with a delightful dinner and a charming walk through the streets of Kingston, a town full of natural beauty and perfect for relaxation.

Following the retreat, we participated in the first day of the Canadian Software Engineering Research (CSER) conference. This event brought together renowned researchers in the field of software engineering. We gained new insights and perspectives from the talks, particularly those from young professors, which were both inspiring and informative. Prof. Costa's presentation on Dependency Management offered valuable insights into a critical area of our work. The conference provided us with valuable opportunities to network, learn, and collaborate with fellow researchers. The CREATE SE4AI retreat and CSER conference were memorable and enriching experiences for the REALISE Lab. They offered us the chance to connect with the broader research community, learn from leading experts, and showcase our work.

Finding performance regressions usually require the execution of long and costly performance test suites. This is because performance tests often have to test the system end-to-end. Could we reduce the testing costs by testing locally (e.g., module, a service, method) and using a model to predict the impact of local changes no the system as a whole?

Our new paper proposes exactly this! The paper entitled "Early Detection of Performance Regressions by Bridging Local Performance Data and Architectural Models" has been accepted at 47th IEEE/ACM International Conference on Software Engineering (ICSE 2025).

We are currently finalizing the camera-ready version of the paper, and we will share the preprint soon. Stay tuned for more updates!

Are you interested in training Chatbots for Software Engineering tasks? Our paper "A Transformer-based Approach for Augmenting Software Engineering Chatbots Datasets" has been accepted at 18th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM 2024).

• In this paper, we propose an approach to augment Chatbot training datasets tailored for Sofdrware Engineering tasks.

Zakaria has presented his work in progress entitled "Choosing the Right Bias Mitigation Strategy: Insights from a Comprehensive Benchmark." In this work, we conduct an experimental assessment of bias mitigation methods over 21 scenarios, considering different machine learning models and datasets.

Our goal is to set a large benchmarking framework to help practitioners choose the right bias mitigation strategy for their specific use case. The poster was presented at the 2024th edition of the Software Engineering for Machine Learning Applications (SEMLA).

I am thrilled to announce that FRQNT has funded our research program “Harnessing Software Ecosystems to Support Library Maintainers”, as part of the Support for New Academics program.

This is a 2-year program, designed to support maintainers in improving the reliability and quality of open- source software libraries by leveraging their dependent ecosystem. This project’s goal is to provide solutions that help maintainers

1. understand how dependents use their library to plan their library evolution and
2. harness the tests of the dependent ecosystem to improve the quality of their library project.

Rachna presented her work on "The role of library versions in Developer-ChatGPT conversations", a MSR Data Mining Challenge study that investigated whether developers refer to library versions when asking ChatGPT for code recommendations. Spoiler alert: they do not, at least not as often as we expected. And when they use library versions in their conversation, they use it in the hopes of receiving tailored code recommendations or to troubleshoot issues with their code.

For her outstanding presentation, Rachna was awarded the best student presentation award at the 2024th edition of the Mining Software Repositories (MSR) conference. Way to go, Rachna!

Check out the slides here: presentation-slides

On a sunny Monday, we went to Jean-drapeau Parc to see a once in a lifetime events : we went to see the total solar eclispe. As a lab, we decided to stop racing against time to solve and conquer problems in order to experience the sight of the full eclipse.