Search Results for author: Thomas Reps

Found 6 papers, 3 papers with code

Coarse-Tuning Models of Code with Reinforcement Learning Feedback

no code implementations25 May 2023 Abhinav Jain, Chima Adiole, Swarat Chaudhuri, Thomas Reps, Chris Jermaine

Our experiments show that RLCF raises the odds that an LLM-generated program compiles, is executable, and produces the right output on tests, often allowing LLMs to match the performance of 2x-8x larger LLMs.

Program Synthesis reinforcement-learning

Shipwright: A Human-in-the-Loop System for Dockerfile Repair

1 code implementation3 Mar 2021 Jordan Henkel, Denini Silva, Leopoldo Teixeira, Marcelo d'Amorim, Thomas Reps

Furthermore, in a "time-travel" analysis of broken Dockerfiles that were later fixed, we found that SHIPWRIGHT proposed repairs that were equivalent to human-authored patches in 22. 77% of the cases we studied.

Language Modelling Software Engineering

TOFU: Target-Oriented FUzzer

no code implementations29 Apr 2020 Zi Wang, Ben Liblit, Thomas Reps

TOFU is also input-structure aware (i. e., the search makes use of a specification of a superset of the program's allowed inputs).

Software Engineering

Semantic Robustness of Models of Source Code

1 code implementation7 Feb 2020 Goutham Ramakrishnan, Jordan Henkel, Zi Wang, Aws Albarghouthi, Somesh Jha, Thomas Reps

Deep neural networks are vulnerable to adversarial examples - small input perturbations that result in incorrect predictions.

Enabling Open-World Specification Mining via Unsupervised Learning

no code implementations27 Apr 2019 Jordan Henkel, Shuvendu K. Lahiri, Ben Liblit, Thomas Reps

Using this dataset, we show that interesting clusters can be recovered, in a fully automatic way, by leveraging unsupervised learning in the form of word embeddings.

Word Embeddings

Code Vectors: Understanding Programs Through Embedded Abstracted Symbolic Traces

1 code implementation18 Mar 2018 Jordan Henkel, Shuvendu K. Lahiri, Ben Liblit, Thomas Reps

With the rise of machine learning, there is a great deal of interest in treating programs as data to be fed to learning algorithms.

Software Engineering

Cannot find the paper you are looking for? You can Submit a new open access paper.