Assuring property conformance of code generators via model checking

Automatic code generation is an essential cornerstone of today’s model-driven approaches to software engineering. Thus a key requirement for the success of this technique is the reliability and correctness of code generators. This article describes how we employ standard model checking-based verification to check that code generator models developed within our code generation framework Genesys conform to (temporal) properties. Genesys is a graphical framework for the high-level construction of code generators on the basis of an extensible library of well-defined building blocks along the lines of the Extreme Model-Driven Development paradigm. We will illustrate our verification approach by examining complex constraints for code generators, which even span entire model hierarchies. We also show how this leads to a knowledge base of rules for code generators, which we constantly extend by e.g. combining constraints to bigger constraints, or by deriving common patterns from structurally similar constraints. In our experience, the development of code generators with Genesys boils down to re-instantiating patterns or slightly modifying the graphical process model, activities which are strongly supported by verification facilities presented in this article.     

Robust stability and instability of biochemical networks with parametric uncertainty

Parameter perturbations in dynamical models of biochemical networks affect the qualitative dynamical behaviour observed in the model. Since this qualitative behaviour is in many cases the key model output used to explain biological function, the robustness analysis of the model’s behaviour with respect to parametric uncertainty is a crucial step in systems biology research. In this paper, we develop a new method for robustness analysis of the dynamical behaviour. As a first step, we provide a characterization of non-robust perturbations as a system of polynomial equalities and inequalities. In the second step, we apply the Positivstellensatz and Handelman representation of polynomials to check for the non-existence of solutions to this system, which can be relaxed to solving a linear program. Thereby, a solution to the linear program yields a robustness certificate for the considered dynamical behaviour. With these robustness certificates, we propose an algorithm to compute a lower robustness bound corresponding to a level of parametric uncertainty up to which no local bifurcations can occur. The applicability of the proposed method to biochemical network models is illustrated by analysing the robustness of oscillations in a model of the NF-κB signalling pathway. The results may be used to define a level of confidence in the observed model behaviour under parametric uncertainty, making them valuable for evaluating dynamical models of biological networks.     

Schedulability analysis for Controller Area Network (CAN) with FIFO queues priority queues and gateways

Controller Area Network (CAN) is widely used in automotive applications. Existing schedulability analysis for CAN is based on the assumption that the highest priority message ready for transmission at each node on the network will be entered into arbitration on the bus. However, in practice, some CAN device drivers implement FIFO rather than priority-based queues invalidating this assumption. In this paper, we introduce response time analysis and optimal priority assignment policies for CAN messages in networks where some nodes use FIFO queues while other nodes use priority queues. We show, via a case study and experimental evaluation, the detrimental impact that FIFO queues have on the real-time performance of CAN. Further, we show that in gateway applications, if it is not possible to implement a priority queue, then it is preferable to use multiple FIFO queues each allocated a small number of messages with similar transmission deadlines.     

Validation of data fusion as a method for forecasting the regeneration workload for complex capital goods

The regeneration of complex capital goods is afflicted with a high degree of uncertainty. Neither the extent of the damage to the goods nor the resulting maintenance workload is known in advance, and that poses challenges for capacity planning. Data fusion in the form of Bayesian networks is used to prepare forecasts in order to estimate the workload in maintenance processes. The objective is to optimize the planability of the capacities required.     

Improved Thermal Insulation for Contemporary Automotive Roof Structures Based on a Computational Fluid Dynamics Heat Flux Approach

Significant losses in the maximum range of electric vehicles and stricter emission norms have drawn attention to further development endeavors in the optimization of passenger compartment conditioning. This need for revision in climatization concepts stems from the focus on defusing the trade-off between thermal comfort and operating distance. Thermal insulation of the drive cabin offers a promising solution. Within this framework, this paper outlines an approach to systematically analyze prevalent heat transfer phenomena within enclosing body surfaces. The conventional roof structure comprising a functionally integrated air gap was chosen as one such representative part. Detailed analysis at this component level presents itself as rather challenging and has therefore contemporarily not been investigated in depth. Computational fluid dynamics simulations are hence employed to analyze the existing complex conjugate heat transfer scenario. As a first step, thermal characterization of the simulation methodology was validated by conducting hot box measurements. Further detailed investigation using these numerical models provided an insight into the understanding of existing heat transfer modes. The obtained results contributed toward efficiently deriving concrete insulation concepts, overcoming restrictions placed by time -and cost-intensive testing procedures.     

Model-based testing as a service

The quality of Web services is an important factor for businesses that advertise or sell their services in the Internet. Failures can directly lead to fewer costumers or security problems. However, the testing of complex Web services that are organized in service-oriented architectures is a difficult and complex problem. Model-based testing (MBT) is one solution to deal with the complexity of the testing. With MBT, testers do not define the tests directly, but rather specify the structure and behavior of the System Under Test using models. Then, a test strategy is used to derive test cases automatically from the models. However, MBT yields a large amount of tests for complex systems which require lots of resources for their execution, thereby limiting its potential. Within this article, we discuss how cloud computing can be used to provide the required resources for scaling up test campaigns with large amounts of test cases derived using MBT.

     

Einsatz von Proteinen als Bindemittel für Holzwerkstoffe

Even after three decades of intensive investigations, biogenic binders based on natural polyphenols (lignin, tannin), polysaccharides (starch), proteins and natural resins/waxes do show very little presence and are miles away from being profitably used. Investigations presented herein deal with how to use both natural proteins and protein-hybridised binders for the production of wood-based panels. As a result it can be seen that with the sole use of native proteins the requirements of a modern wood-based panel technology, especially in terms of economic production cannot yet be met. However, a part-substitution of synthetic binder components by proteins is about to meet the demands of availability, production speed and required panel properties of today’s production.     

Biotechnological synthesis of long‐chain dicarboxylic acids as building blocks for polymers

An important field in sustainable industrial chemistry is the development of new applications for fats and oils. One of the promising applications is the use of fatty acid derivatives, e.g. dicarboxylic acid (DCA), as polymer building blocks. In contrast to conventional plastics, bioplastics are polymers derived from renewable biomass sources. In addition to their contribution to the conservation of fossil resources and reduction in CO₂ emissions by waste incineration, many bioplastics are biodegradable. The majority of industrial DCA production for polyamide (PA) and polyester (PE) synthesis is still done via chemical synthesis. While short‐chain DCA can be synthesized in high yields, costs of long‐chain DCA production rise significantly due to the generation of various by‐products and are connected mostly to a costly purification. Thus biotechnology provides novel biochemical approaches for long‐chain DCA synthesis that can provide an eco‐efficient process alternative. In the present article, strategies for the development of high‐level production strains for long‐chain DCA are illustrated. Basic strategies for strain development, in order to achieve an effective enrichment of DCA, require the knowledge of the respective biochemical pathways. These are discussed in detail. Furthermore an overview of fermentation strategies and characteristics of corresponding polymers is given.     

模块化机器的安全白皮书

SmartFactory~(KL)工作组1 "智能基础设施"专门处理模块化工业4.0生产设施的安全问题。其旨在提供一种工厂结构,通过模块化等手段确保其灵活性和可变性。本安型模块具有常规的功能安全性。但是,模块间依然存在依赖关系。在支持未知模块的模块化系统中,还需要一个新的安全体系结构。去年,该概念被整合到了工业4.0生产设施中,以实例证明该概念可在当今技术的基础上得以实施。在安全和机器通信的实施中,仅采用了一条单线共存。机器和机器模块可以在运行期间插入生产线或从生产线移除,而不会影响工厂的其它部分。必要的安全相关参数将根据此处导入的安全配置文件自动进行协商、配置和发布。要求如下文所述。