10 papers
DiffTestGen: Change-Directed LLM-Based Testing for Exposing Behavioral Differences
Huimin Hu, Cristian Cadar, Michael Pradel
As software evolves over time, it is important to ensure that any behavioral changes occur as intended by developers. A promising approach for this goal is to generate tests that e…
RippleGUItester: Change-Aware Exploratory Testing
Yanqi Su, Michael Pradel, Chunyang Chen
Software systems evolve continuously through frequent code changes, yet such changes often introduce unintended bugs despite extensive testing and code review. Existing testing app…
AgentStepper: Interactive Debugging of Software Development Agents
Robert Hutter, Michael Pradel
Software development agents powered by large language models (LLMs) have shown great promise in automating tasks like environment setup, issue solving, and program repair. Unfortun…
PatchGuru: Patch Oracle Inference from Natural Language Artifacts
Thanh Le-Cong, Bach Le, Toby Murray +2
As software systems evolve, patches may unintentionally alter program behavior. Validating patches against their intended semantics is difficult due to incomplete regression tests…
CodeMapper: A Language-Agnostic Approach to Mapping Code Regions Across Commits
Huimin Hu, Michael Pradel
During software evolution, developers commonly face the problem of mapping a specific code region from one commit to another. For example, they may want to determine how the condit…
Testora: Using Natural Language Intent to Detect Behavioral Regressions
Michael Pradel
As software is evolving, code changes can introduce regression bugs or affect the behavior in other unintended ways. Traditional regression test generation is impractical for detec…