Realization of distributed system models using code generation extensions

Abstract

Development of distributed software systems is complex due to the distribution of resources, which complicates validation of system-wide functionality. Such systems include various facets like functionality and distribution, each of which must be validated and integrated in the final software solution. Model-based techniques advocate various abstraction approaches to cope with such challenges. To enhance model-based development, this paper proposes (1) guidelines for development of distributed systems, where the different facets are introduced gradually through systematic modeling extensions, (2) code generation capabilities supporting technology specific realizations, and (3) demonstration of the applicability of our approach using an industrial case study involving the development of a harvest planning system, where the communication infrastructure paradigm changed late in the project. When developing this system, we spent most time validating system-wide functionality. The model extensions allowed an easier change of the underlying communication paradigm and code generation supported realization of the different system representations.

Enabling continuous integration in a formal methods setting

“…The extentions we developed were used in a large case study, to support an industrial project with a major agricultural company 1 : development of a harvest planning system [8,9,18,28], which is now being turned into a commercial product. This system enables farmers to optimise harvest operations using predictions made using simulation.…”

The Harvest Coach Architecture: Embedding Deviation-Tolerance in a Harvest Logistic Solution

“…In [7,10], the reader may find details about the process of unit testing the prototypes developed. One paper uses the harvest logistics prototype as a case study and test to the improvements of the VDM testing support, the other uses it as an example of distributed system modeling.…”

“…The VDM++ model supports both off-line simulation and real-time guidance of harvest operations, so it is rather complex, but in here we report on the core functionality needed to understand the deviation listings only. For a thorough description of the model, the many previous publications should suffice [4][5][6][7]. The model is object oriented, and its class diagram is shown in Figure 8.…”

“…which deploys an initial harvest plan tuned for a best case scenario in terms of the field conditions. The execution level was previously developed as reported in [4][5][6][7], and, before our additions, implemented a stepwise loop reading the values for the several vehicle parameters (e.g., GPS position, bin level) in the field and issuing the routes to be shown to the operators in thin clients to be carried in cabins of the vehicles.…”

Code generation for distributed embedded systems with VDM-RT

“…Hence these contributions present how the code generator is extended in order to support generating code for DESs, when following the guidelines presented above. In general, the division between functionality and distribution in VDM-RT enables to have systematic code generation extensions [20]. Generating the functionality corresponds to emitting code from the normal classes of a VDM-RT model, as indicated in Figure 4.…”