Publications×3

R is a dynamically typed, vector-oriented language widely used for data analysis. Its vector semantics, including automatic type coercion, recycling, and flexible selection, are pervasive, non-trivial, and deeply intertwined with the semantics of virtually every R operation. We present a parametric abstract domain for R vectors, defined over μR, a core calculus designed to capture the important vector operations in R. An abstract vector simultaneously captures the possible lengths of the vector, the values of its elements, and its potential attributes. We define abstract operators for all μR operations, equip the domain with a widening operator to ensure termination, and implement it on top of flowR, a static analysis framework for R, evaluating it on a suite of 61 handcrafted programs covering six categories of vector operations.

A parametric abstract domain for R vectors, defined over μR, a core calculus designed to capture the most representative vector manipulation operations in R. An abstract vector simultaneously captures the possible lengths of the vector, the values of its elements, and its potential attributes. The domain is parametric in the element abstract domain, is equipped with a widening operator to ensure termination of fixpoint computation, and is implemented on top of flowR, a static analysis framework for R. Supervised by Prof. Vincenzo Arceri, with Florian Sihler as advisor (Erasmus+ exchange at Ulm University).

Experimental evaluation of the ability to automatically detect programming errors in source code generated by Large Language Models, using static analysis techniques. Supervised by Prof. Enea Zaffanella and Prof. Vincenzo Arceri. Grade: 110/110 cum laude.