Search Results for author: Matteo Paltenghi

Found 2 papers, 1 papers with code

Fuzz4All: Universal Fuzzing with Large Language Models

1 code implementation9 Aug 2023 Chunqiu Steven Xia, Matteo Paltenghi, Jia Le Tian, Michael Pradel, Lingming Zhang

Moreover, the inputs generated by existing fuzzers are often limited to specific features of the input language, and thus can hardly reveal bugs related to other or new features.

Extracting Meaningful Attention on Source Code: An Empirical Study of Developer and Neural Model Code Exploration

no code implementations11 Oct 2022 Matteo Paltenghi, Rahul Pandita, Austin Z. Henley, Albert Ziegler

The high effectiveness of neural models of code, such as OpenAI Codex and AlphaCode, suggests coding capabilities of models that are at least comparable to those of humans.

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