SmartTS: A Component-Based and Model-Driven Approach to Software Testing in Robotic Software Ecosystem

Validating the behaviour of commercial off-the-shelf components and of interactions between them is a complex, and often a manual task. Treated like any other software product, a software component for a robot system is often tested only by the component developer. Test sets and results are often not available to the system builder, who may need to verify functional and non-functional claims made by the component. Availability of test records is key in establishing compliance and thus selection of the most suitable components for system composition. To provide empirically verifiable test records consistent with a component’s claims would greatly improve the overall safety and dependability of robotic software systems in open-ended environments. Addi-tionally, a test and validation suite for a system built from the model package of that system empirically codifies its behavioural claims. In this paper, we present the “SmartTS methodology”: A component-based and model-driven approach to generate model-bound test-suites for software components and systems. SmartTS methodology and tooling are not restricted to the robotics domain. The core contribution of SmartTS is support for test and validation suites derived from the model packages of components and systems. The test-suites in SmartTS are tightly bound to an application domain’s data and service models as defined in the RobMoSys (EU H2020 project) compliant SmartMDSD toolchain. SmartTS does not break component encapsulation for system builders while providing them complete access to the way that component is tested and simulated.

@article{Nagrath2021,
  title     = {SmartTS: A Component-Based and Model-Driven Approach to Software Testing in Robotic Software Ecosystem},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {12},
  number    = {7},
  year      = {2021},
  publisher = {The Science and Information Organization},
  author    = {Vineet Nagrath and Christian Schlegel},
  doi       = {10.14569/IJACSA.2021.0120702},
  url       = {https://doi.org/10.14569/IJACSA.2021.0120702}
}