A. von Mayrhauser

Papers

Total Citations

126

H-Index

About

Anneliese von Mayrhauser is a pioneering figure in software engineering, best known for her groundbreaking work in automated test generation and domain-based testing. Her research fundamentally bridges artificial intelligence and software testing, introducing innovative methods that treat test case generation as an AI planning problem—a concept that has garnered over 62 citations and remains influential in the field. She developed Domain Based Testing (DBT), a systematic approach that leverages domain analysis and modeling to increase test case reuse, significantly improving efficiency in command-based systems. Her contributions extend to practical automation, as demonstrated in her work on automated testing for robot tape libraries, where she integrated syntactic and semantic information at multiple levels to drive test data generation. Von Mayrhauser also advanced goal-oriented testing by using AI planners to generate test cases from high-level objectives, extending UML models for system-level verification. With a citation impact spanning hundreds of references, her research has shaped modern software testing practices, making complex systems more reliable and testable. Her work remains essential reading for researchers and practitioners seeking intelligent, reusable testing strategies.