31 citations
- University of Minnesota, DuluthUS3 papers
- Mahidol UniversityTH2 papers
- Pennsylvania State UniversityUS2 papers
- Astronomical Institute of the Slovak Academy of SciencesSK1 paper
- Centre National de la Recherche ScientifiqueFR1 paper
- Concordia UniversityCA1 paper
- Georgia Southern UniversityUS1 paper
- Hodges UniversityUS1 paper
- Huawei Technologies (Canada)CA1 paper
- John Regan Associates (United Kingdom)GB1 paper
- Laboratoire de Physique Théorique et Modèles StatistiquesFR1 paper
- Michigan Technological UniversityUS1 paper
6 papers · 2 filters
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…
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…
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…
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…
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…
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…