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20222026
most citedA Cross-Company Ethnographic Study on Software Teams for DevOps and Microservices: Organization, Benefits, and Issues

12 citations · 12 across the 8 of their papers we have counts for

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Showing cs.SEShow all

9 papers · 1 filter

cs.SE2026

Fail-Fast, Restart-Smart: Early Failure Prediction and Restart for SWE Agentic Tasks

Chenyu Wang, Yunbo Lyu, Junda He +4

Software engineering (SWE) agents resolve repository-level issues through long trajectories that grow increasingly expensive as context accumulates. Failed runs tend to be longer a…

cs.SE2026

MultiFixer: A Coordinator-Proposer Based Multi-Agent Framework For Fixing Multi-Hunk Bugs

Haichuan Hu, Chunrong Fang, Ye Shang +5

Automated Program Repair (APR) has benefited greatly from Large Language Models (LLMs), but existing LLM-based APR methods still struggle with multi-hunk bugs that require coordina…

cs.SE2026

What Characterizes Pairwise Modular Smells?

Chenxing Zhong, Daniel Feitosa, Paris Avgeriou +3

Enhancing the modular structure of existing systems has attracted substantial research interest, primarily through (1) software modularization and (2) identifying design issues (e.…

cs.SE2026

An Execution-Verified Multi-Language Benchmark for Code Semantic Reasoning

Yikun Li, Jinfeng Jiang, Ting Zhang +7

Evaluating whether large language models (LLMs) can recover execution-relevant program structure, rather than only produce code that passes tests, remains an open problem. Existing…

cs.SE2026

APISENSOR: Robust Discovery of Web API from Runtime Traffic Logs

Yanjing Yang, Chenxing Zhong, Ke Han +5

Large Language Model (LLM)-based agents increasingly rely on APIs to operate complex web applications, but rapid evolution often leads to incomplete or inconsistent API documentati…

cs.SE2025

A Grey Literature Review of AI-Native Applications

Lingli Cao, Shanshan Li, Ying Fan +2

Background: The rapid advancement of large language models (LLMs) has given rise to AI-native applications, a new paradigm in software engineering that fundamentally redefines how…