3 papers
cs.SE2026
Dissecting Software Graphs: Structural Insights for Driver-Guided Fuzzing
Baihong Chen, Hua Ming, Weifeng Pan +3
Many software systems expose multiple execution modes through command-line options, subcommands, and configuration flags. For such programs, fuzzing depends on both mutated inputs…
cs.SE2026
Quality and Security Signals in AI-Generated Python Refactoring Pull Requests
Mohamed Almukhtar, Anwar Ghammam, Hua Ming
As AI agents increasingly contribute to code development and maintenance, there is still limited empirical evidence on the quality and risk characteristics of their changes in real…
cs.SE2025
From Code Changes to Quality Gains: An Empirical Study in Python ML Systems with PyQu
Mohamed Almukhtar, Anwar Ghammam, Marouane Kessentini +1
In an era shaped by Generative Artificial Intelligence for code generation and the rising adoption of Python-based Machine Learning systems (MLS), software quality has emerged as a…