papers

Publications (25)

cs.SE2025

Screencast-Based Analysis of User-Perceived GUI Responsiveness

Wei Liu, Linqiang Guo, Yi Wen Heng +4

GUI responsiveness is critical for a positive user experience in mobile applications. Even brief delays in visual feedback can frustrate users and lead to negative reviews. However…

cs.CL2024

Studying and Recommending Information Highlighting in Stack Overflow Answers

Shahla Shaan Ahmed, Shaowei Wang, Yuan Tian +3

Context: Navigating the knowledge of Stack Overflow (SO) remains challenging. To make the posts vivid to users, SO allows users to write and edit posts with Markdown or HTML so tha…

cs.SE2026

Probe to Generate: Program Variant-Guided Test Augmentation for Repository-Level Repair Benchmarks

Chenglin Li, Yisen Xu, Zehao Wang +3

Test-based benchmarks such as SWE-bench have become a standard basis for evaluating automated issue resolution agents, deeming a patch correct if it passes a provided regression te…

cs.SE2026

Bug Report Specification Refinement with Trajectory Guidance for Automated Program Repair

S M Farah Al Fahim, Md Nakhla Rafi, Md Ahasanuzzaman +5

Bug reports serve as task specifications for repository-level automated program repair (APR) agents, but they often describe only the observed failure and omit repair-relevant info…

cs.SE2026

Turning Interaction History into Execution State: A Runtime Layer for Long-Horizon Coding Agents

Zehao Wang, Yisen Xu, Chenglin Li +5

Long-horizon coding agents accumulate hundreds of actions and observations in their trajectories, yet nothing in this record indicates which observations still describe the reposit…

cs.SE2026

Retrieval-Oriented Code Representations in Agentic Bug Localization

Genevieve Caumartin, Tse-Hsun, Chen +1

The paper evaluates how different code representations, including LLM-generated textual summaries, affect the effectiveness and cost of file-level bug localization, finding that ro…

#bug localization#code representation#information retrieval#large language models
cs.SE2025

MANTRA: Enhancing Automated Method-Level Refactoring with Contextual RAG and Multi-Agent LLM Collaboration

Yisen Xu, Feng Lin, Jinqiu Yang +3

Maintaining and scaling software systems relies heavily on effective code refactoring, yet this process remains labor-intensive, requiring developers to carefully analyze existing…

cs.AI2026

StepReflect: Structured UI Transition Reflection for Mobile GUI Agents

Linqiang Guo, Wei Liu, Li Gu +3

Autonomous mobile GUI agents require accurate action reflection for reliable long-horizon execution. Existing approaches rely on open-ended multimodal reasoning after each action,…

cs.SE2025

Studying the Impact of Early Test Termination Due to Assertion Failure on Code Coverage and Spectrum-based Fault Localization

Md. Ashraf Uddin, Shaowei Wang, An Ran Chen +3

An assertion is commonly used to validate the expected programs behavior (e.g., if the returned value of a method equals an expected value) in software testing. Although it is a re…

cs.SE2024

PopSweeper: Automatically Detecting and Resolving App-Blocking Pop-Ups to Assist Automated Mobile GUI Testing

Linqiang Guo, Wei Liu, Yi Wen Heng +3

Graphical User Interfaces (GUIs) are the primary means by which users interact with mobile applications, making them crucial to both app functionality and user experience. However,…

cs.SE2024

Discovery of Timeline and Crowd Reaction of Software Vulnerability Disclosures

Yi Wen Heng, Zeyang Ma, Haoxiang Zhang +3

Reusing third-party libraries increases productivity and saves time and costs for developers. However, the downside is the presence of vulnerabilities in those libraries, which can…

cs.SE2021

Studying Duplicate Logging Statements and Their Relationships with Code Clones

Zhenhao Li, Tse-Hsun, Chen +2

In this paper, we focus on studying duplicate logging statements, which are logging statements that have the same static text message. We manually studied over 4K duplicate logging…

cs.SE2026

Towards Structured, State-Aware, and Execution-Grounded Reasoning for Software Engineering Agents

Tse-Hsun, Chen

Software Engineering (SE) agents have shown promising abilities in supporting various SE tasks. Current SE agents remain fundamentally reactive, making decisions mainly based on co…

cs.SE2026

CI-Repair-Bench: A Repository-Aware Benchmark for Automated Patch Validation via CI Workflows

Rabeya Khatun Muna, Md Nakhla Rafi, Tse-Hsun +1

Continuous Integration (CI) enforces repository-level correctness through multi-stage workflows and is central to modern software development, yet diagnosing and repairing CI failu…

cs.SE2025

Crash Report Enhancement with Large Language Models: An Empirical Study

S M Farah Al Fahim, Md Nakhla Rafi, Zeyang Ma +3

Crash reports are central to software maintenance, yet many lack the diagnostic detail developers need to debug efficiently. We examine whether large language models can enhance cr…

cs.SE2024

Studying and Benchmarking Large Language Models For Log Level Suggestion

Yi Wen Heng, Zeyang Ma, Zhenhao Li +3

Large Language Models (LLMs) have become a focal point of research across various domains, including software engineering, where their capabilities are increasingly leveraged. Rece…

cs.SE2026

From Historical Patches to Repair Plans: Outcome-Conditioned Reasoning for Repository-Level Program Repair

Chenglin Li, Yisen Xu, Zehao Wang +3

Repository-level automated program repair (APR) requires long-horizon reasoning over interdependent decisions. However, most LLM-based approaches reconstruct repair reasoning indep…

cs.SE2025

RobuNFR: Evaluating the Robustness of Large Language Models on Non-Functional Requirements Aware Code Generation

Feng Lin, Dong Jae Kim, Zhenhao Li +3

When using LLMs to address Non-Functional Requirements (NFRs), developers may behave differently (e.g., expressing the same NFR in different words). Robust LLMs should output consi…

cs.SE2019

An Empirical Study of Obsolete Answers on Stack Overflow

Haoxiang Zhang, Shaowei Wang, Tse-Hsun +3

Stack Overflow accumulates an enormous amount of software engineering knowledge. However, as time passes, certain knowledge in answers may become obsolete. Such obsolete answers, i…

cs.SE2026

SWE-Refactor: A Repository-Level Benchmark for Real-World LLM-Based Code Refactoring

Yisen Xu, Jinqiu Yang, Tse-Hsun +1

Large Language Models (LLMs) have recently attracted wide interest for tackling software engineering tasks. In contrast to code generation, refactoring demands precise, semantics-p…

cs.SE2025

MobileUPReg: Identifying User-Perceived Performance Regressions in Mobile OS Versions

Wei Liu, Yi Wen Heng, Feng Lin +3

Mobile operating systems (OS) are frequently updated, but such updates can unintentionally degrade user experience by introducing performance regressions. Existing detection techni…

cs.SE2026

Independent Patch Verification for Coding Agents with a Bidirectional Reconstruct-and-Verify Framework

Chenglin Li, Yisen Xu, Zehao Wang +3

Autonomous coding agents powered by large language models can now generate code patches directly from bug reports, but a fundamental gap remains: once a patch is produced, no mecha…

cs.AI2025

Agent-SAMA: State-Aware Mobile Assistant

Linqiang Guo, Wei Liu, Yi Wen Heng +3

Mobile Graphical User Interface (GUI) agents aim to autonomously complete tasks within or across apps based on user instructions. While recent Multimodal Large Language Models (MLL…

cs.SE2026

Rethinking Code Performance Benchmarks for LLMs

Nhat Minh Le, Yisen Xu, Zhijie Wang +2

Many function-level performance benchmarks have been proposed to evaluate whether large language models (LLMs) can generate efficient programs. However, results on these benchmarks…

cs.SE2025

SBEST: Spectrum-Based Fault Localization Without Fault-Triggering Tests

Md Nakhla Rafi, Lorena Barreto Simedo Pacheco, An Ran Chen +3

Fault localization is a critical step in software maintenance. Yet, many existing techniques, such as Spectrum-Based Fault Localization (SBFL), rely heavily on the availability of…