5 papers
Prompt-Based REST API Test Amplification in Industry: An Experience Report
Tolgahan Bardakci, Andreas Faes, Mutlu Beyazit +1
Large Language Models (LLMs) are increasingly used to support software testing tasks, yet there is little evidence of their effectiveness for REST API testing in industrial setting…
Agentic LLMs for REST API Test Amplification: A Comparative Study Across Cloud Applications
Jarne Besjes, Robbe Nooyens, Tolgahan Bardakci +2
Representational State Transfer (REST) APIs are a cornerstone of modern cloud native systems. Ensuring their reliability demands automated test suites that exercise diverse and bou…
Test Amplification for REST APIs via Single and Multi-Agent LLM Systems
Robbe Nooyens, Tolgahan Bardakci, Mutlu Beyazit +1
REST APIs (Representational State Transfer Application Programming Interfaces) play a vital role in modern cloud-native applications. As these APIs grow in complexity and scale, en…
Test Amplification for REST APIs Using "Out-of-the-box" Large Language Models
Tolgahan Bardakci, Serge Demeyer, Mutlu Beyazit
REST APIs (Representational State Transfer Application Programming Interfaces) are an indispensable building block in today's cloud-native applications, so testing them is critical…
Cross-System Categorization of Abnormal Traces in Microservice-Based Systems via Meta-Learning
Yuqing Wang, Mika V. Mäntylä, Serge Demeyer +3
Microservice-based systems (MSS) may fail with various fault types. While existing AIOps methods excel at detecting abnormal traces and locating the responsible service(s), human e…