Guided Metamorphic Transformations for Testing the Robustness of Trained Code2Vec Models

Machine learning models are increasingly being used within software engineering for their predictions. Research shows that these models’ performance is increasing with new research. This thesis focuses on models for method name prediction, for which the goal is to have a model that can accurately predict method names. With this thesis, we could...

Enriching Machine Learning Model Metadata: Collecting performance metadata through automatic evaluation

As the sharing of machine learning (ML) models has increased in popularity, more so-called model zoos are created. These repositories facilitate the sharing of models and their metadata, and other people to find and re-use an existing model. However, the metadata provided for models is insufficient, with little focus on practical aspects of a...

Developing a level-1B qualifiable CNN for in-situ ultrasonic damage classification of aerospace composite structures: An in-depth evaluation on the end-to-end process of developing a data-driven tool

This paper examines the end-to-end development process for a Convolution Neural Network (CNN) based damage classification tool for ultrasonic inspection of aerospace-grade composite structures. The recent advent of Artificial Intelligence (AI) and Machine Learning (ML) has piqued the interest of the aerospace industry since it has the potential...