10 papers
Tangent: An Empirical Study of Testing Practices for LLM-Based Agent Applications
Rangeet Pan, Tyler Stennett, Divya Sankar +5
Agents built on large language models (LLMs) are increasingly used to build applications that perform complex, multi-step tasks involving reasoning, tool use, and interaction with…
Sakura: An Approach for Generating Complex Tests from Natural Language Test Descriptions
Tyler Stennett, Rangeet Pan, Bridget McGinn +2
Research on automating software testing has spanned several decades. Most existing approaches generate unit tests for individual methods, validate isolated API endpoints, or target…
SAINT: Service-level Integration Test Generation with Program Analysis and LLM-based Agents
Rangeet Pan, Raju Pavuluri, Ruikai Huang +4
Enterprise applications are typically tested at multiple levels, with service-level testing playing an important role in validating application functionality. Existing service-leve…
Hamster: A Large-Scale Study and Characterization of Developer-Written Tests
Rangeet Pan, Tyler Stennett, Raju Pavuluri +3
Automated test generation (ATG), which aims to reduce the cost of manual test suite development, has been investigated for decades and has produced countless techniques based on a…
Usage, Effects and Requirements for AI Coding Assistants in the Enterprise: An Empirical Study
Maja Vukovic, Rangeet Pan, Tin Kam Ho +3
The rise of large language models (LLMs) has accelerated the development of automated techniques and tools for supporting various software engineering tasks, e.g., program understa…
Advancing Automated In-Isolation Validation in Repository-Level Code Translation
Kaiyao Ke, Ali Reza Ibrahimzada, Rangeet Pan +2
Repository-level code translation aims to migrate entire repositories across programming languages while preserving functionality automatically. Despite advancements in repository-…