3 citations · 11 across the 12 of their papers we have counts for
8 papers · 1 filter
Summary of the 4th International Workshop on Requirements Engineering and Testing (RET 2017)
Markus Borg, Elizabeth Bjarnason, Michael Unterkalmsteiner +3
The RET (Requirements Engineering and Testing) workshop series provides a meeting point for researchers and practitioners from the two separate fields of Requirements Engineering (…
Summary of the 3rd International Workshop on Requirements Engineering and Testing
Michael Unterkalmsteiner, Gregory Gay, Michael Felderer +3
The RET (Requirements Engineering and Testing) workshop series provides a meeting point for researchers and practitioners from the two separate fields of Requirements Engineering (…
Requirements Engineering for Automotive Perception Systems: an Interview Study
Khan Mohammad Habibullah, Hans-Martin Heyn, Gregory Gay +6
Background: Driving automation systems (DAS), including autonomous driving and advanced driver assistance, are an important safety-critical domain. DAS often incorporate perception…
The Integration of Machine Learning into Automated Test Generation: A Systematic Mapping Study
Afonso Fontes, Gregory Gay
Context: Machine learning (ML) may enable effective automated test generation. Objective: We characterize emerging research, examining testing practices, researcher goals, ML techn…
Non-Functional Requirements for Machine Learning: An Exploration of System Scope and Interest
Khan Mohammad Habibullah, Gregory Gay, Jennifer Horkoff
Systems that rely on Machine Learning (ML systems) have differing demands on system quality compared to traditional systems. Such quality demands, known as non-functional requireme…
Automated Support for Unit Test Generation: A Tutorial Book Chapter
Afonso Fontes, Gregory Gay, Francisco Gomes de Oliveira Neto +1
Unit testing is a stage of testing where the smallest segment of code that can be tested in isolation from the rest of the system - often a class - is tested. Unit tests are typica…
Using Machine Learning to Generate Test Oracles: A Systematic Literature Review
Afonso Fontes, Gregory Gay
Machine learning may enable the automated generation of test oracles. We have characterized emerging research in this area through a systematic literature review examining oracle t…
Learning How to Search: Generating Effective Test Cases Through Adaptive Fitness Function Selection
Hussein Almulla, Gregory Gay
Search-based test generation is guided by feedback from one or more fitness functions - scoring functions that judge solution optimality. Choosing informative fitness functions is…