collaborators

6 papers

cs.SE2026

Grounding AI Agents in Contracts: An Empirical Evaluation of Spec-Driven Test Generation

Michele Tufano, James McClure, José Cambronero +7

LLM-based agents are increasingly used for coding tasks, where they have outperformed many classical approaches and scaled to repository-level tasks, such as test generation. Howev…

cs.SE2026

TRIM: Reducing AI-Generated CodeSlop via Agent Trajectory Minimization

Alex Mathai, Shobini Iyer, Aleksandr Nogikh +4

Coding agents are increasingly used to accelerate code generation in many downstream tasks, such as fixing bugs, building applications, and prototyping. However, despite their valu…

cs.SE2026

Outrunning LLM Cutoffs: A Live Kernel Crash Resolution Benchmark for All

Chenxi Huang, Alex Mathai, Feiyang Yu +7

Repairing system crashes discovered by kernel fuzzers like Syzkaller is a critical yet underexplored challenge in software engineering. While recent works have introduced Large Lan…

cs.SE2026

Customizing an LLM for Enterprise Software Engineering

Aditya Kini, Satish Chandra, Milad Hashemi +15

Enterprise software development is a continuous evolutionary process, characterized by incremental additions, architectural revisions, production deployments and rigorous maintenan…

cs.SE2026

Dynamic Cogeneration of Bug Reproduction Test in Agentic Program Repair

Runxiang Cheng, Michele Tufano, José Cambronero +7

Bug Reproduction Tests (BRTs) have been used in many Automated Program Repair (APR) systems, primarily for validating fixes and aiding fix generation. In practice, when developers…

cs.SE2025

Towards a Human-in-the-Loop Framework for Reliable Patch Evaluation Using an LLM-as-a-Judge

Sherry Shi, Renyao Wei, Michele Tufano +4

Reliable evaluation is crucial for advancing Automated Program Repair (APR), but prevailing benchmarks rely on execution-based evaluation methods (unit test pass@k), which fail to…