5 papers · 1 filter
Bridging Behavior and Implementation: Automated Java Glue Code Generation for Behavior-Driven Development
Xinyu Shi, Zhou Yang, An Ran Chen
Behavior-Driven Development (BDD) helps technical and non-technical stakeholders share a common understanding of software requirements through natural-language scenarios. Glue code…
Can Large Language Models Reason About Complex Execution Paths? An Empirical Study on Python
Wenhan Wang, Kaibo Liu, Zeyu Sun +4
Execution path reasoning is a key step towards program semantics understanding. It is crucial for generating test cases that cover certain branches/paths, or detecting bugs that ar…
TESTEVAL: Benchmarking Large Language Models for Test Case Generation
Wenhan Wang, Chenyuan Yang, Zhijie Wang +6
Testing plays a crucial role in the software development cycle, enabling the detection of bugs, vulnerabilities, and other undesirable behaviors. To perform software testing, teste…
Fine-grained Testing for Autonomous Driving Software: a Study on Autoware with LLM-driven Unit Testing
Wenhan Wang, Xuan Xie, Yuheng Huang +3
Testing autonomous driving systems (ADS) is critical to ensuring their reliability and safety. Existing ADS testing works focuses on designing scenarios to evaluate system-level be…
Python Symbolic Execution with LLM-powered Code Generation
Wenhan Wang, Kaibo Liu, An Ran Chen +4
Symbolic execution is a key technology in software testing, which generates test cases by collecting symbolic path constraints and then solving constraints with SMT solvers. Symbol…