Model Based Development with the Skeleton Design Method

Whitsitt, Sean; Sprinkle, Jonathan

doi:10.1109/ecbs.2013.16

Cited by 3 publications

(2 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…JausML is built using the skeleton design method (an extension of the more common template design method) [11]. Building the code generator for the ROS to JAUS bridges to be compatible with the skeleton design method will make integrating the final results with JausML a trivial matter.…”

Section: Jausmlmentioning

confidence: 99%

Generating a ROS/JAUS bridge for an autonomous ground vehicle

Morley

Warren

Rabb

et al. 2013

Proceedings of the 2013 ACM Workshop on Domain-Specific Modeling

Self Cite

View full text Add to dashboard Cite

Robotic systems have benefitted from standardized middleware that can componentize the development of new capabilities for a robot. The popularity of these robotic middleware systems has resulted in sizable libraries of components that are now available to roboticists. However, many robotic systems (such as autonomous vehicles) must adhere to externally defined standards that do not contain a large repository of components. Due to the real-time and safety concerns that accompany the domain of unmanned systems, it is not trivial to interface these middleware systems. However, previous attempts to do so have succeeded at the cost of ad hoc design and implementation. This paper describes a domain-specific approach to the synthesis of a bridge between the popular Robotic Operating System (ROS) and the Joint Architecture for Unmanned Systems (JAUS). The domain-specific nature of the approach permits the bridge to be limited in scope by the application's specific messages (and their attribute mappings between JAUS/ROS), resulting in smaller code size and overhead than would be incurred by a generic solution. Our approach is validated by tests performed on an unmanned vehicle with and without the JAUS/ROS bridge.

show abstract

Section: Jausmlmentioning

confidence: 99%

Generating a ROS/JAUS bridge for an autonomous ground vehicle

Morley

Warren

Rabb

et al. 2013

Proceedings of the 2013 ACM Workshop on Domain-Specific Modeling

Self Cite

View full text Add to dashboard Cite

show abstract

“…The transformations that the language creates based on expert blocks are generated using the skeleton design method [15]. First, a skeleton was made for each component of the transformation.…”

Section: Transformationsmentioning

confidence: 99%

Generating Model Transformations for Mending Dynamic Constraint Violations in Cyber Physical Systems

Whitsitt

Sprinkle

Lysecky

2014

Proceedings of the 14th Workshop on Domain-Specific Modeling

Self Cite

View full text Add to dashboard Cite

Cyber physical systems (CPSs) by definition involve design constraints addressing the computation and communication necessary to control physical systems. These systems have been modeled using domain specific modeling languages, but some limitations exist in the continued application of such a modeling approach to more complex, or safety-critical, systems. Specifically, it is well known how to formulate constraints in a domain-specific modeling language in order to prevent users from building invalid structures, but existing constraint-based techniques do not take into consideration design requirements that may require analysis in the physical domain (i.e. dynamic constraints). Those analysis results, when interpreted by a domain expert, can inform changes to the model: unfortunately, this "by hand" process does not scale. This paper presents an approach to automate the process of evolving models based on dynamic constraints that are not structurally enforceable into the modeling of CPSs. This new methodology-called dynamic constraint feedback (DCF)-is described herein and demonstrated with specific examples derived from the domain of data adaptable reconfigurable embedded systems (DARES). In DCF, expert blocks are integrated with a modeling language to perform dynamic constraint analysis on system models. The results from these analyses are then used to generate model transformations that can be applied to the source models.

show abstract