30 citations · 78 across the 23 of their papers we have counts for
6 papers · 1 filter
A Systematic Study of Time Limit Exceeded Errors in Online Programming Assignments
Jialu Zhang, Jialiang Gu, Wangmeiyu Zhang +5
Online programming platforms such as Codeforces and LeetCode attract millions of users seeking to learn to program or refine their skills for industry interviews. A major challenge…
Abstain and Validate: A Dual-LLM Policy for Reducing Noise in Agentic Program Repair
José Cambronero, Michele Tufano, Sherry Shi +7
Agentic Automated Program Repair (APR) is increasingly tackling complex, repository-level bugs in industry, but ultimately these patches still need to be reviewed by a human before…
Towards Verified Code Reasoning by LLMs
Meghana Sistla, Gogul Balakrishnan, Pat Rondon +3
While LLM-based agents are able to tackle a wide variety of code reasoning questions, the answers are not always correct. This prevents the agent from being useful in situations wh…
Tabularis Formatus: Predictive Formatting for Tables
Mukul Singh, José Cambronero, Sumit Gulwani +2
Spreadsheet manipulation software are widely used for data management and analysis of tabular data, yet the creation of conditional formatting (CF) rules remains a complex task req…
Agentic Bug Reproduction for Effective Automated Program Repair at Google
Runxiang Cheng, Michele Tufano, Jürgen Cito +5
Bug reports often lack sufficient detail for developers to reproduce and fix the underlying defects. Bug Reproduction Tests (BRTs), tests that fail when the bug is present and pass…
Evaluating Agent-based Program Repair at Google
Pat Rondon, Renyao Wei, José Cambronero +5
Agent-based program repair offers to automatically resolve complex bugs end-to-end by combining the planning, tool use, and code generation abilities of modern LLMs. Recent work ha…