1 code implementation • 22 Sep 2021 • Steve Kommrusch, Martin Monperrus, Louis-Noël Pouchet
We propose a neural network architecture based on a transformer model to generate proofs of equivalence between program pairs.
no code implementations • 1 Jun 2021 • Steve Kommrusch, Théo Barollet, Louis-Noël Pouchet
We target the problem of provably computing the equivalence between two complex expression trees.
no code implementations • 17 Feb 2020 • Steve Kommrusch, Théo Barollet, Louis-Noël Pouchet
In this work we target the problem of provably computing the equivalence between two programs represented as dataflow graphs.
2 code implementations • 24 Dec 2018 • Zimin Chen, Steve Kommrusch, Michele Tufano, Louis-Noël Pouchet, Denys Poshyvanyk, Martin Monperrus
This paper presents a novel end-to-end approach to program repair based on sequence-to-sequence learning.
1 code implementation • 19 Nov 2018 • Steve Kommrusch, Louis-Noël Pouchet
One of the challenges of using machine learning techniques with medical data is the frequent dearth of source image data on which to train.