Incremental Consistency Checking in Delta-oriented UML-Models for Automation Systems

Automation systems exist in many variants and may evolve over time in order to deal with different environment contexts or to fulfill changing customer requirements. This induces an increased complexity during design-time as well as tedious maintenance efforts. We already proposed a multi-perspective modeling approach to improve the development of such systems. It operates on different levels of abstraction by using well-known UML-models with activity, composite structure and state chart models. Each perspective was enriched with delta modeling to manage variability and evolution. As an extension, we now focus on the development of an efficient consistency checking method at several levels to ensure valid variants of the automation system. Consistency checking must be provided for each perspective in isolation, in-between the perspectives as well as after the application of a delta.Comment: In Proceedings FMSPLE 2016, arXiv:1603.0857

Adaptive inferential sensors based on evolving fuzzy models

A new technique to the design and use of inferential sensors in the process industry is proposed in this paper, which is based on the recently introduced concept of evolving fuzzy models (EFMs). They address the challenge that the modern process industry faces today, namely, to develop such adaptive and self-calibrating online inferential sensors that reduce the maintenance costs while keeping the high precision and interpretability/transparency. The proposed new methodology makes possible inferential sensors to recalibrate automatically, which reduces significantly the life-cycle efforts for their maintenance. This is achieved by the adaptive and flexible open-structure EFM used. The novelty of this paper lies in the following: (1) the overall concept of inferential sensors with evolving and self-developing structure from the data streams; (2) the new methodology for online automatic selection of input variables that are most relevant for the prediction; (3) the technique to detect automatically a shift in the data pattern using the age of the clusters (and fuzzy rules); (4) the online standardization technique used by the learning procedure of the evolving model; and (5) the application of this innovative approach to several real-life industrial processes from the chemical industry (evolving inferential sensors, namely, eSensors, were used for predicting the chemical properties of different products in The Dow Chemical Company, Freeport, TX). It should be noted, however, that the methodology and conclusions of this paper are valid for the broader area of chemical and process industries in general. The results demonstrate that well-interpretable and with-simple-structure inferential sensors can automatically be designed from the data stream in real time, which predict various process variables of interest. The proposed approach can be used as a basis for the development of a new generation of adaptive and evolving inferential sensors that can a- ddress the challenges of the modern advanced process industry

Towards Product Lining Model-Driven Development Code Generators

A code generator systematically transforms compact models to detailed code. Today, code generation is regarded as an integral part of model-driven development (MDD). Despite its relevance, the development of code generators is an inherently complex task and common methodologies and architectures are lacking. Additionally, reuse and extension of existing code generators only exist on individual parts. A systematic development and reuse based on a code generator product line is still in its infancy. Thus, the aim of this paper is to identify the mechanism necessary for a code generator product line by (a) analyzing the common product line development approach and (b) mapping those to a code generator specific infrastructure. As a first step towards realizing a code generator product line infrastructure, we present a component-based implementation approach based on ideas of variability-aware module systems and point out further research challenges.Comment: 6 pages, 1 figure, Proceedings of the 3rd International Conference on Model-Driven Engineering and Software Development, pp. 539-545, Angers, France, SciTePress, 201

Open Source Innovation, Patent Injunctions, and the Public Interest

This Article explores the difficulties that high technology markets pose for patent law and, in particular, for patent injunctions. It then outlines the ways in which “open source innovation” is unusually vulnerable to patent injunctions. It argues that courts can recognize this vulnerability, and respond to the particular competitive and innovative benefits of open source innovation, by flexibly applying the Supreme Court’s ruling in eBay v. MercExchange. Having dealt with the lamentable failure of the International Trade Commission to exercise a similar flexibility in its own patent jurisprudence, despite statutory and constitutional provisions that counsel otherwise, the Article concludes with some recommendations for reform