110 citations · 121 across the 9 of their papers we have counts for
9 papers
FastContext: Training Efficient Repository Explorer for Coding Agents
Shaoqiu Zhang, Maoquan Wang, Yuling Shi +12
Large Language Model (LLM) coding agents have achieved strong results on software engineering tasks, yet repository exploration remains a major bottleneck: locating relevant code c…
SemRep: Generative Code Representation Learning with Code Transformations
Weichen Li, Jiamin Song, Bogdan Alexandru Stoica +4
Code transformation is a foundational capability in the software development process, where its effectiveness relies on constructing a high-quality code representation to character…
DevBench: A Realistic, Developer-Informed Benchmark for Code Generation Models
Adarsh Kumarappan, Pareesa Ameneh Golnari, Wen Wen +5
DevBench is a telemetry-driven benchmark designed to evaluate Large Language Models (LLMs) on realistic code completion tasks. It includes 1,800 evaluation instances across six pro…
Code-Aware Prompting: A study of Coverage Guided Test Generation in Regression Setting using LLM
Gabriel Ryan, Siddhartha Jain, Mingyue Shang +4
Testing plays a pivotal role in ensuring software quality, yet conventional Search Based Software Testing (SBST) methods often struggle with complex software units, achieving subop…
TOGA: A Neural Method for Test Oracle Generation
Elizabeth Dinella, Gabriel Ryan, Todd Mytkowicz +1
Testing is widely recognized as an important stage of the software development lifecycle. Effective software testing can provide benefits such as bug finding, preventing regression…
Learning Nonlinear Loop Invariants with Gated Continuous Logic Networks (Extended Version)
Jianan Yao, Gabriel Ryan, Justin Wong +2
Verifying real-world programs often requires inferring loop invariants with nonlinear constraints. This is especially true in programs that perform many numerical operations, such…