14th Workshop on Advances in Model Based Testing (A-MOST) @ICST 2018, Västerås, Sweden

The increasing complexity and need for assurance of software-based systems pose new challenges for testing. Model Based Testing (MBT) is an important research area, where new approaches, methods and tools make MBT techniques more useful and applicable in industry, contributing to improve the effectiveness and efficiency of the test process. Models and different abstractions can ease comprehension of a complex system and allow the systematization and automation of test generation. A-MOST 2018 will bring together researchers and practitioners interested in the topic of Model Based Testing. Using models for designing and testing software is currently one of the most salient industrial trends with significant impact on the development and testing processes. Model-based tools and methods have been successfully applied and continue to converge into comprehensive approaches to software and system engineering. The area encompasses models derived from object-oriented software engineering, formal methods, and other mathematical and engineering disciplines.

The execution of software using test cases or sequences derived in a manual or automatic manner from models is an encouraging scientific and industrial trend to cope with growing software system complexity and criticality. Modeling requires substantial investment, and practical and scalable MBT solutions can help leverage this investment. The testing models may have been adapted from system design models or might have been devised specifically to support MBT. Naturally, the greatest benefits are often obtained when test generation is automated, but many practitioners report that the modeling process itself is of value, often highlighting requirements issues. The use of industrial scale software demands the model-based construction of software and systems as compositions of independent and reusable components and services. In this engineering paradigm, complex system functionality arises out of the composition of many component services. For these systems, model based testing may significantly improve component acceptance and move component integration testing towards a canonical validation and certification of complete systems. Automation of software development and software testing on the basis of executable models and simulation promises significant reductions in fault-removal cost and development time. As a consequence of automating MBT, changes in requirements analysis, development and testing processes are needed that demand combined efforts from research and industry towards a broadly accepted solution. A-MOST 2018 will focus on three main areas: the models used in MBT; the processes, techniques, and tools that support MBT; and evaluation. Here, evaluation includes the evaluation of software using MBT and the evaluation of MBT. These areas can be further broken down into the following topics.


  • Models for component, integration and system testing
  • Product-line models
  • (Hybrid) embedded system models
  • Systems-of-systems models
  • Architectural models
  • Models for orchestration and choreography of services
  • Executable models, simulation and model transformations
  • Environment and use models
  • Non-functional models
  • Models for variant-rich and highly configurable systems


  • Model-based test generation algorithms
  • Application of model checking techniques to MBT
  • Symbolic execution-based techniques
  • Tracing from requirements models to test models
  • Performance and predictability of MBT
  • Test model evolution during the software life-cycle
  • Risk-based approaches for MBT
  • Generation of testing infrastructures from models
  • Combinatorial approaches for MBT
  • Statistical testing
  • Non-functional MBT


  • Estimating dependability (e.g., security, safety, reliability) using MBT
  • Coverage metrics and measurements for structural and (non-) functional models
  • Cost of testing, economic impact of MBT
  • Empirical validation, experiences, case studies using MBT