Four faculty. Three research labs. One mission: advancing the science of AI-driven software development at William & Mary.
Combined metrics across all four AI-for-SE faculty members at William & Mary.
Four complementary research programs, united by a focus on intelligent software development.
Complementary research programs spanning the full stack of intelligent software development.
Code generation, semantic clone detection, program repair, and neural models of source code.
Automated bug-report analysis, refactoring recommendations, and program comprehension tools.
LLM-based code documentation, energy-efficient model training, and sustainable AI for SE.
Supply-chain vulnerability analysis, privacy compliance at scale, and GenAI security auditing.
Research outcomes adopted by major technology companies and open-source communities.
Xiao's security and privacy tools have been adopted by Google, Meta, Twitter/X, WeChat, and Opera to protect billions of users.
Poshyvanyk's DL-for-SE techniques have influenced industry-wide approaches to code intelligence, clone detection, and program repair.
Mastropaolo's work on LLM-based code documentation and generation informs next-generation developer workflows.
Chaparro's automated bug-report analysis and quality tools improve how development teams diagnose and resolve defects.