activity
20242026
collaborators

6 papers

cs.SE2026

SpecFirst: Behavioral Specification Elicitation as a First-Class Step in Agent-Based Program Synthesis from Scratch

Yihao Chen, Shi Chang, Feng Lin +4

LLM-based agents excel at software engineering tasks where an existing codebase provides context, but constructing a program from scratch remains fundamentally harder. Recent bench…

cs.SE2026

MindForge: Teaching Small Language Models Whole-Life-Cycle Software Engineering via Source-Free Program Synthesis

Yihao Chen, Shi Chang, Khaled Chawa +4

Coding agents have made substantial progress on software engineering tasks that modify existing codebases, including bug fixing and feature implementation. However, constructing a…

cs.LG2026

Chimera: Latency- and Performance-Aware Multi-agent Serving for Heterogeneous LLMs

Kangqi Ni, Wenyue Hua, Xiaoxiang Shi +3

Multi-agent applications often execute complex tasks as multi-stage workflows, where each stage is an LLM call whose output becomes part of context for subsequent steps. Existing L…

cs.SE2025

Adaptive Request Scheduling for CodeLLM Serving with SLA Guarantees

Shi Chang, Boyuan Chen, Kishanthan Thangarajah +2

Code Large Language Models (CodeLLMs) are increasingly integrated into modern software development workflows, yet efficiently serving them in resource-constrained, self-hosted envi…

cs.SE2025

Context-Aware CodeLLM Eviction for AI-assisted Coding

Kishanthan Thangarajah, Boyuan Chen, Shi Chang +1

AI-assisted coding tools powered by Code Large Language Models (CodeLLMs) are increasingly integrated into modern software development workflows. To address concerns around privacy…

cs.SE2024

Software Performance Engineering for Foundation Model-Powered Software

Haoxiang Zhang, Shi Chang, Arthur Leung +4

The rise of Foundation Models (FMs) like Large Language Models (LLMs) is revolutionizing software development. Despite the impressive prototypes, transforming FMware into productio…