Author

Alejandro Velasco

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Preprint Aug 2026

On Automated and Explainable Provenance of AI-Generated Code

It is argued that the next generation of CodeGenAI tools must be built on a foundation of explainable provenance: automated, post-hoc traceability that links generated code back to the prompt components, training data instances, global data features, and internal model components that caused its generation.

Alejandro Velasco, Nathan Wintersgill, Trevor Stalnaker et al. · 2 citations

#small language model Aug 2026

ECLAIR: A Causally-Grounded AI Framework for Scientific Discovery in Empirical Software Engineering

This study presents the first causally grounded structured methodology for embedding LLMs within the scientific method in SE, designed around the epistemological demands of empirical SE research, establishing a basis for rigorous AI-assisted research.

Alejandro Velasco, Daniel Rodríguez-Cárdenas, Dipin Khati et al. · IEEE/ACM International Confe... · 0 citations