Harnessing Predictive Modeling and Software Analytics in the Age of LLM-Powered Software Development (Invited Talk)
Foutse Khomh · 2023
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.