The increasing complexity, criticality and pervasiveness of software results in new challenges for testing. Model Based Testing (MBT) continues to be an important research area, where new approaches, methods and tools make MBT techniques (for automatic test case generation) more deployable and useful for industry than ever. Following the success of previous editions, the goal of the A-MOST workshop is to bring researchers and practitioners together to discuss state of the art, practice and future prospects in MBT. Topics and sub-topics (not exhaustive):
The models used in MBT
Models for component, integration and system testing
Test models for systems of systems, non-deterministic systems, real-time embedded systems, and hybrid (continuous/discrete) systems
Models for non-functional aspects (e.g., security, safety, reliability)
Environment and usage models
Formal, semi-formal, and restricted-natural-language models
The processes, techniques, and tools that support MBT
Algorithms for automatic test case generation from models
Coverage criteria to guide and assess test case generation
Application of model checking techniques for test case generation
Application of machine learning techniques to automatically derive, augment and evolve test models
Model-based mutation testing
Generation of testing-infrastructures from models
Combinatorial approaches for model-based statistical testing
Integrated model-based approaches for simulation, testing, and run-time monitoring
Traceability in MBT
Test model evolution during the software lifecycle
Integration of MBT in agile and DevOps contexts
Evaluation (evaluation of software using MBT and evaluation of MBT)
Performance measures in MBT
Cost of testing and economic impact of MBT
Empirical validation, experiences, and case studies using MBT