SEMLA

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CREATE SE4AI

A training program on the development, deployment and servicing of artificial intelligenece-based software systems

SEMLA 2022 is coming

October 29th - 30th, 2022

The Software Engineering for Machine Learning Applications (SEMLA) international symposium aims at bringing together leading researchers and practitioners in software engineering and machine learning to reflect on and discuss the challenges and implications of engineering complex data-intensive software systems.

HR powered by AI

January 27, 2021

By Amanda Arciero, Airudi and Foutse Khomh, Polytechnique Montreal

AI and Digital Systems

February 16th - 19th, 2021

Discover the technologies and initiatives to concretize AI and Digital systems of tomorrow with Arnaud Van de Voorde (CAE), Foutse Khomh (Polytechnique Montreal), Caroline Gorski (R2 Data Labs), and (Jean-Paul Isson SITA).

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Reuse of code as an example: an article raises vulnerability issues in commercial applications

An article by Verdi et al. reveals the introduction of vulnerabilities in commercial applications, through the reuse of snippets of C++ code provided as examples on the Stack Overflow question and answer site. The study has raised awareness within the programming community.

How to Certify Machine Learning Based Safety-critical Systems? A Systematic Literature Review

Tambon et al. reviewed the literature on the requirements of certifying transportation systems with machine learning components, the existing standards for these systems, the current state-of-the-art techniques and practices towards the certification goal, and the limitations of these techniques.

On the Co-evolution of ML Pipelines and Source Code - Empirical Study of DVC Projects

Barrak et al. studied the technology used to version machine learning models and data sets in terms of the amount of effort required to keep models and data in sync with the source code and test suite of a software system.

An Exploratory Study on Machine Learning Model Stores

Xiu et al. analyze the machine learning model store mechanism used to distribute machine learning models to prospective users. The paper compares these novel stores to the better-known mobile app stores.

DEEL

Dependable, Certifiable, Explainable Artificial Intelligence for Critical Systems

The DEEL Project involves academic and industrial partners in the development of dependable, robust, explainable and certifiable artificial intelligence technological bricks applied to critical systems.