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Fischer T.,Research Center for Information Technology | Kollner C.,Vector Informatik GmbH | Hardle M.,Research Center for Information Technology | Muller-Glaser K.D.,Karlsruhe Institute of Technology
Proceedings - IEEE International Symposium on Rapid System Prototyping, RSP | Year: 2014

Managing different variants and configurations of complex embedded systems consisting of multiple exchangeable hardware modules is a difficult task. This is in particular true when selecting a certain variant and configuration affects several aspects of development, deployment and operation. In this paper, we describe our approach for product line development of a highly flexible, modular embedded system, which can be assembled in many different ways. Each composition can be perceived as a prototype, because it requires a specific FPGA firmware, and offers different parameters changeable at runtime. A key component of our solution is a model-based description of possible variations. It enables automatic generation of source code as well as configuration files. Through this it is possible to provide new variants and configurations very fast and the response time to customer requests is improved. We outline how the model can be well-integrated with technologies and tools used for development, deployment and operation of the overall system. This involves run-time parametrization of the system and configuration of secondary tools using standard office documents, but the focus lies on the link between model and FPGA implementation (VHDL). We propose a powerful but still easy to understand template-based approach for this purpose. © 2014 IEEE.


Elberzhager F.,Fraunhofer Institute for Experimental Software Engineering | Munch J.,University of Helsinki | Assmann D.,Vector Informatik GmbH
Information and Software Technology | Year: 2014

Context Quality assurance effort, especially testing effort, is frequently a major cost factor during software development. Consequently, one major goal is often to reduce testing effort. One promising way to improve the effectiveness and efficiency of software quality assurance is the use of data from early defect detection activities to provide a software testing focus. Studies indicate that using a combination of early defect data and other product data to focus testing activities outperforms the use of other product data only. One of the key challenges is that the use of data from early defect detection activities (such as inspections) to focus testing requires a thorough understanding of the relationships between these early defect detection activities and testing. An aggravating factor is that these relationships are highly context-specific and need to be evaluated for concrete environments. Objective The underlying goal of this paper is to help companies get a better understanding of these relationships for their own environment, and to provide them with a methodology for finding relationships in their own environments. Method This article compares three different strategies for evaluating assumed relationships between inspections and testing. We compare a confidence counter, different quality classes, and the F-measure including precision and recall. Results One result of this case-study-based comparison is that evaluations based on the aggregated F-measures are more suitable for industry environments than evaluations based on a confidence counter. Moreover, they provide more detailed insights about the validity of the relationships. Conclusion We have confirmed that inspection results are suitable data for controlling testing activities. Evaluated knowledge about relationships between inspections and testing can be used in the integrated inspection and testing approach In2Test to focus testing activities. Product data can be used in addition. However, the assumptions have to be evaluated in each new context. © 2014 Elsevier B.V. All rights reserved.


Elberzhager F.,Fraunhofer Institute for Experimental Software Engineering | Kremer S.,Fraunhofer Institute for Experimental Software Engineering | Munch J.,University of Helsinki | Assmann D.,Vector Informatik GmbH
Proceedings - 38th EUROMICRO Conference on Software Engineering and Advanced Applications, SEAA 2012 | Year: 2012

Product metrics, such as size or complexity, are often used to identify defect-prone parts or to focus quality assurance activities. In contrast, quality information that is available early, such as information provided by inspections, is usually not used. Currently, only little experience is documented in the literature on whether data from early defect detection activities can support the identification of defect prone parts later in the development process. This article compares selected product and inspection metrics commonly used to predict defect-prone parts. Based on initial experience from two case studies performed in different environments, the suitability of different metrics for predicting defect-prone parts is illustrated. These studies revealed that inspection defect data seems to be a suitable predictor, and a combination of certain inspection and product metrics led to the best prioritizations in our contexts. © 2012 IEEE.


Loffler T.,Vector Informatik GmbH
19th Intelligent Transport Systems World Congress, ITS 2012 | Year: 2012

Automotive OEMs (Original equipment manufacturers) and suppliers are already conducting Car2x production projects. It is indeed true that mature automotive development processes exist today for validating innovations in the pre-production phase within the boundaries of a single vehicle. However, system validation of an ITS (Intelligent Transport System) vehicle station can only be performed in the context of its interactions with other traffic participants in the relevant environment. This article describes how the proven method of network simulation can be extended to Car2x scenarios.


Brehmer A.,Vector Informatik GmbH | Lotoczky R.,Vector CANtech Inc
AIAA/IEEE Digital Avionics Systems Conference - Proceedings | Year: 2014

CAN increasing use in aerospace applications ARINC 825 - standardized CAN for airborne use ARINC 812A - standardized CAN for galley insert (GAIN) equipment CANOpen has found application in aerospace systems Satellite sensors (ESA) Integration of COTS components CAN-FD 'next-gen' CAN solution for high data rate applications Lower overhead Higher data throughput © 2014 IEEE.

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