4 citations · 14 across the 15 of their papers we have counts for
4 papers · 1 filter
CauSec: Unboxing the Causal Drivers of Static Vulnerability Analysis Performance
Akram Khan, Md Akram Khan, Daniel Rodriguez-Cardenas +3
Static Application Security Testing (SAST) tools are widely used in both industry and academia. Such tools often make design choices that sacrifice detection to achieve higher perf…
ECLAIR: A Causally-Grounded AI Framework for Scientific Discovery in Empirical Software Engineering
Alejandro Velasco, Daniel Rodriguez-Cardenas, Dipin Khati +2
The scientific method has long guided empirical research in Software Engineering (SE), but the complexity of modern software systems often hinders its systematic application. This…
On Automated and Explainable Provenance of AI-Generated Code
Alejandro Velasco, Nathan Wintersgill, Trevor Stalnaker +2
Generative AI for code generation has transformed software development, but it has also introduced a critical transparency problem: the origins of AI-generated code are opaque to t…
How Do Semantically Equivalent Code Transformations Impact Membership Inference on LLMs for Code?
Hua Yang, Alejandro Velasco, Thanh Le-Cong +3
The success of large language models for code relies on vast amounts of code data, including public open-source repositories, such as GitHub, and private, confidential code from co…