34 citations · 89 across the 8 of their papers we have counts for
8 papers
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…
Exploring Continual Learning for Code Generation Models
Prateek Yadav, Qing Sun, Hantian Ding +9
Large-scale code generation models such as Codex and CodeT5 have achieved impressive performance. However, libraries are upgraded or deprecated very frequently and re-training larg…
A Static Evaluation of Code Completion by Large Language Models
Hantian Ding, Varun Kumar, Yuchen Tian +9
Large language models trained on code have shown great potential to increase productivity of software developers. Several execution-based benchmarks have been proposed to evaluate…
Greener yet Powerful: Taming Large Code Generation Models with Quantization
Xiaokai Wei, Sujan Gonugondla, Wasi Ahmad +13
ML-powered code generation aims to assist developers to write code in a more productive manner, by intelligently generating code blocks based on natural language prompts. Recently,…
ReCode: Robustness Evaluation of Code Generation Models
Shiqi Wang, Zheng Li, Haifeng Qian +11
Code generation models have achieved impressive performance. However, they tend to be brittle as slight edits to a prompt could lead to very different generations; these robustness…
CoCoMIC: Code Completion By Jointly Modeling In-file and Cross-file Context
Yangruibo Ding, Zijian Wang, Wasi Uddin Ahmad +5
While pre-trained language models (LM) for code have achieved great success in code completion, they generate code conditioned only on the contents within the file, i.e., in-file c…
Multi-lingual Evaluation of Code Generation Models
Ben Athiwaratkun, Sanjay Krishna Gouda, Zijian Wang +22
We present new benchmarks on evaluation code generation models: MBXP and Multilingual HumanEval, and MathQA-X. These datasets cover over 10 programming languages and are generated…
A Study of Real-World Data Races in Golang
Milind Chabbi, Murali Krishna Ramanathan
The concurrent programming literature is rich with tools and techniques for data race detection. Less, however, has been known about real-world, industry-scale deployment, experien…