39 citations · 157 across the 32 of their papers we have counts for
6 papers · 1 filter
VarCLR: Variable Semantic Representation Pre-training via Contrastive Learning
Qibin Chen, Jeremy Lacomis, Edward J. Schwartz +3
Variable names are critical for conveying intended program behavior. Machine learning-based program analysis methods use variable name representations for a wide range of tasks, su…
Learning to Superoptimize Real-world Programs
Alex Shypula, Pengcheng Yin, Jeremy Lacomis +3
Program optimization is the process of modifying software to execute more efficiently. Superoptimizers attempt to find the optimal program by employing significantly more expensive…
Augmenting Decompiler Output with Learned Variable Names and Types
Qibin Chen, Jeremy Lacomis, Edward J. Schwartz +3
A common tool used by security professionals for reverse-engineering binaries found in the wild is the decompiler. A decompiler attempts to reverse compilation, transforming a bina…
GzScenic: Automatic Scene Generation for Gazebo Simulator
Afsoon Afzal, Claire Le Goues, Christopher S. Timperley
Testing robotic and cyberphysical systems in simulation require specifications of the simulated environments (i.e., scenes). The Scenic domain-specific language provides a high-lev…
An Empirical Study of OSS-Fuzz Bugs
Zhen Yu Ding, Claire Le Goues
Continuous fuzzing is an increasingly popular technique for automated quality and security assurance. Google maintains OSS-Fuzz: a continuous fuzzing service for open source softwa…
SOAR: A Synthesis Approach for Data Science API Refactoring
Ansong Ni, Daniel Ramos, Aidan Yang +4
With the growth of the open-source data science community, both the number of data science libraries and the number of versions for the same library are increasing rapidly. To matc…