519 citations · 4.1k across the 233 of their papers we have counts for
8 papers · 1 filter
Learning Performance-Improving Code Edits
Alexander Shypula, Aman Madaan, Yimeng Zeng +7
With the decline of Moore's law, optimizing program performance has become a major focus of software research. However, high-level optimizations such as API and algorithm changes r…
CodeBERTScore: Evaluating Code Generation with Pretrained Models of Code
Shuyan Zhou, Uri Alon, Sumit Agarwal +1
Since the rise of neural natural-language-to-code models (NL->Code) that can generate long expressions and statements rather than a single next-token, one of the major problems has…
Execution-Based Evaluation for Open-Domain Code Generation
Zhiruo Wang, Shuyan Zhou, Daniel Fried +1
To extend the scope of coding queries to more realistic settings, we propose ODEX, the first Open-Domain EXecution-based natural language (NL) to Python code generation dataset. OD…
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…
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…
In-IDE Code Generation from Natural Language: Promise and Challenges
Frank F. Xu, Bogdan Vasilescu, Graham Neubig
A great part of software development involves conceptualizing or communicating the underlying procedures and logic that needs to be expressed in programs. One major difficulty of p…
DIRE: A Neural Approach to Decompiled Identifier Naming
Jeremy Lacomis, Pengcheng Yin, Edward J. Schwartz +4
The decompiler is one of the most common tools for examining binaries without corresponding source code. It transforms binaries into high-level code, reversing the compilation proc…
Learning to Generate Corrective Patches using Neural Machine Translation
Hideaki Hata, Emad Shihab, Graham Neubig
Bug fixing is generally a manually-intensive task. However, recent work has proposed the idea of automated program repair, which aims to repair (at least a subset of) bugs in diffe…