9 papers
Understanding Agent-Reactive Bugs at the Model-Harness Boundary: An Empirical Study of LLM Agent Issue Reports
Jingyi Chen, Songqiang Chen, Hengcheng Zhu +3
LLM agents span command-line interfaces (e.g., Codex) and agent frameworks (e.g., LangChain), integrating backend LLMs with harness code that parses model outputs, controls agent l…
Programming-by-Example for Batch-Editing Collision Meshes in 3D Software
Gengyang Xu, Dongwei Xiao, Hengcheng Zhu +4
As 3D software proliferates, software artifacts now extend beyond code and 2D user interfaces to include 3D assets. Among these assets, collision meshes are critical as they define…
Characterizing Tests in IoT Software: Practices, Challenges and Opportunities
Rufeng Chen, Hengcheng Zhu, Wuqi Zhang +2
The Internet of Things (IoT) is experiencing rapid growth. Smart devices are emerging in smart homes and industrial applications, performing mission-critical tasks. Bugs in IoT sof…
Improving LLM-Driven Test Generation by Learning from Mocking Information
Jamie Lee, Flynn Teh, Hengcheng Zhu +3
Large Language Models (LLMs) have recently shown strong potential for automated unit test generation. This has motivated us to investigate whether developer-defined test doubles (c…
MR-Coupler: Automated Metamorphic Test Generation via Functional Coupling Analysis
Congying Xu, Hengcheng Zhu, Songqiang Chen +3
Metamorphic testing (MT) is a widely recognized technique for alleviating the oracle problem in software testing. However, its adoption is hindered by the difficulty of constructin…
MR-Adopt: Automatic Deduction of Input Transformation Function for Metamorphic Testing
Congying Xu, Songqiang Chen, Jiarong Wu +4
While a recent study reveals that many developer-written test cases can encode a reusable Metamorphic Relation (MR), over 70% of them directly hard-code the source input and follow…