collaborators

5 papers

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

kAgent: An execution-guided crash resolution agent for the Linux kernel

Alex Mathai, Chenxi Huang, Suwei Ma +7

Fuzzing frameworks like syzkaller have uncovered thousands of Linux kernel crashes, many of which are critical and security-sensitive. However, the ability to rapidly repair these…

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

RubberDuckBench: A Benchmark for AI Coding Assistants

Ferida Mohammed, Fatma Ayad, Petros Maniatis +2

Programmers are turning to AI coding assistants to answer questions about their code. Benchmarks are needed to soundly evaluate these systems and understand their performance. To e…