Evolution of software in automated production systems

Since ontology-driven software development (ODSD) is an integration of ontology technologies and model-driven software development (MDSD), it is necessary to identify and analyse technologies applied in MDSD. We define basic concepts, such as model-driven engineering, metamodelling, model transformation and technological space, and describe the state-of-the-art implementations of these concepts.

Model-Driven Software Development

This abstract summarizes the paper accepted at the Journal of Systems and Software with the same title [1]. 
Automated production systems form the backbone of the world’s industrial production. They are highly specialized technical systems, which are comprised of mechanical, electrical and electronic parts and software, all closely interwoven. Software is the defining factor to realize modern trends in manufacturing as defined by mass customization, small lot sizes, high variability of product types, and a changing product portfolio during the lifecycle of an automated production system. However, the software can control the production system only via electrical and mechanical means, which have their individual life cycles and undergo evolution. Hence, the evolution of automated production systems always requires addressing cross-disciplinary evolution challenges.
We provide an interdisciplinary survey on the challenges, the state-of-the-art as well as research directions with respect to the evolution of software in automated production systems. In the first part, we discuss the specifics of the development process as well as the different types of evolutions during the system’s life-cycle. In the second part, we survey the challenges due to evolution covering the different development phases (requirements, design, implementation, validation & verification) and several important cross-cutting aspects (variability management, model-driven engineering, and traceability), and review existing potential approaches. Finally, we outline future research directions for the discussed challenges.

Evolution of software in automated production systems: Challenges and Research Directions

https://uoc.edu/webs/rclariso/_resources/documents/jss10.pdf

Verification and validation of declarative model-to-model transformations through invariants

Bidirectional transformations (bx) support principled consistency maintenance between data sources. Each data source corresponds to one perspective on a composite system, manifested by operations to ‘get’ and ‘set’ a view of the whole from that particular perspective. Bx are important in a wide range of settings, including databases, interactive applications, and model-driven development. We show that bx are naturally modelled in terms of mutable state; in particular, the ‘set’ operations are stateful functions. This leads naturally to considering bx that exploit other computational effects too, such as I/O, nondeterminism, and failure, all largely ignored in the bx literature to date. We present a semantic foundation for symmetric bidirectional transformations with effects. We build on the mature theory of monadic encapsulation of effects in functional programming, develop the equational theory and important combinators for effectful bx, and provide a prototype implementation in Haskell along with several illustrative examples.

/pdf/notions-of-bidirectional-computation-and-entangled-state-453r5miwwl.pdf

Wim Bast

Papers

MOF QVT final adopted specification: meta object facility (MOF) 2.0 query/view/transformation specification.