An experimental Study using ACSL and Frama-C to formulate and verify Low-Level Requirements from a DO-178C compliant Avionics Project

Safety critical avionics software is a natural application area for formal verification. This is reflected in the formal method's inclusion into the certification guideline DO-178C and its formal methods supplement DO-333. Airbus and Dassault-Aviation, for example, have conducted studies in using formal verification. A large German national research project, Verisoft XT, also examined the application of formal methods in the avionics domain. However, formal methods are not yet mainstream, and it is questionable if formal verification, especially formal deduction, can be integrated into the software development processes of a resource constrained small or medium enterprise (SME). ESG, a Munich based medium sized company, has conducted a small experimental study on the application of formal verification on a small portion of a real avionics project. The low level specification of a software function was formalized with ACSL, and the corresponding source code was partially verified using Frama-C and the WP plugin, with Alt-Ergo as automated prover. We established a couple of criteria which a method should meet to be fit for purpose for industrial use in SME, and evaluated these criteria with the experience gathered by using ACSL with Frama-C on a real world example. The paper reports on the results of this study but also highlights some issues regarding the method in general which, in our view, will typically arise when using the method in the domain of embedded real-time programming.Comment: In Proceedings F-IDE 2015, arXiv:1508.0338

Smart container monitoring using custom-made WSN technology : from business case to prototype

This paper reports on the development of a prototype solution for tracking and monitoring shipping containers. Deploying wireless sensor networks (WSNs) in an operational environment remains a challenging task. We strongly believe that standardized methodologies and tools could enhance future WSN deployments and enable rapid prototype development. Therefore, we choose to use a step-by-step approach where each step gives us more insight in the problem at hand while shielding some of the complexity of the final solution. We observed that environment emulation is of the utmost importance, especially for harsh wireless conditions inside a container stacking. This lead us to extend our test lab with wireless link emulation capabilities. It is also essential to assess feasibility of concepts and design choices after every stage during prototype development. This enabled us to create innovative WSN solutions, including a multi-MAC framework and a robust gateway selection algorithm

A gentle transition from Java programming to Web Services using XML-RPC

Exposing students to leading edge vocational areas of relevance such as Web Services can be difficult. We show a lightweight approach by embedding a key component of Web Services within a Level 3 BSc module in Distributed Computing. We present a ready to use collection of lecture slides and student activities based on XML-RPC. In addition we show that this material addresses the central topics in the context of web services as identified by Draganova (2003)

FPGA-based module for SURF extraction

We present a complete hardware and software solution of an FPGA-based computer vision embedded module capable of carrying out SURF image features extraction algorithm. Aside from image analysis, the module embeds a Linux distribution that allows to run programs specifically tailored for particular applications. The module is based on a Virtex-5 FXT FPGA which features powerful configurable logic and an embedded PowerPC processor. We describe the module hardware as well as the custom FPGA image processing cores that implement the algorithm's most computationally expensive process, the interest point detection. The module's overall performance is evaluated and compared to CPU and GPU based solutions. Results show that the embedded module achieves comparable disctinctiveness to the SURF software implementation running in a standard CPU while being faster and consuming significantly less power and space. Thus, it allows to use the SURF algorithm in applications with power and spatial constraints, such as autonomous navigation of small mobile robots

Considerations about Continuous Experimentation for Resource-Constrained Platforms in Self-Driving Vehicles

Autonomous vehicles are slowly becoming reality thanks to the efforts of many academic and industrial organizations. Due to the complexity of the software powering these systems and the dynamicity of the development processes, an architectural solution capable of supporting long-term evolution and maintenance is required. Continuous Experimentation (CE) is an already increasingly adopted practice in software-intensive web-based software systems to steadily improve them over time. CE allows organizations to steer the development efforts by basing decisions on data collected about the system in its field of application. Despite the advantages of Continuous Experimentation, this practice is only rarely adopted in cyber-physical systems and in the automotive domain. Reasons for this include the strict safety constraints and the computational capabilities needed from the target systems. In this work, a concept for using Continuous Experimentation for resource-constrained platforms like a self-driving vehicle is outlined.Comment: Copyright 2017 Springer. Paper submitted and accepted at the 11th European Conference on Software Architecture. 8 pages, 1 figure. Published in Lecture Notes in Computer Science vol 10475 (Springer), https://link.springer.com/chapter/10.1007/978-3-319-65831-5_

The NASA SBIR product catalog

The purpose of this catalog is to assist small business firms in making the community aware of products emerging from their efforts in the Small Business Innovation Research (SBIR) program. It contains descriptions of some products that have advanced into Phase 3 and others that are identified as prospective products. Both lists of products in this catalog are based on information supplied by NASA SBIR contractors in responding to an invitation to be represented in this document. Generally, all products suggested by the small firms were included in order to meet the goals of information exchange for SBIR results. Of the 444 SBIR contractors NASA queried, 137 provided information on 219 products. The catalog presents the product information in the technology areas listed in the table of contents. Within each area, the products are listed in alphabetical order by product name and are given identifying numbers. Also included is an alphabetical listing of the companies that have products described. This listing cross-references the product list and provides information on the business activity of each firm. In addition, there are three indexes: one a list of firms by states, one that lists the products according to NASA Centers that managed the SBIR projects, and one that lists the products by the relevant Technical Topics utilized in NASA's annual program solicitation under which each SBIR project was selected

VANET Applications: Hot Use Cases

Current challenges of car manufacturers are to make roads safe, to achieve free flowing traffic with few congestions, and to reduce pollution by an effective fuel use. To reach these goals, many improvements are performed in-car, but more and more approaches rely on connected cars with communication capabilities between cars, with an infrastructure, or with IoT devices. Monitoring and coordinating vehicles allow then to compute intelligent ways of transportation. Connected cars have introduced a new way of thinking cars - not only as a mean for a driver to go from A to B, but as smart cars - a user extension like the smartphone today. In this report, we introduce concepts and specific vocabulary in order to classify current innovations or ideas on the emerging topic of smart car. We present a graphical categorization showing this evolution in function of the societal evolution. Different perspectives are adopted: a vehicle-centric view, a vehicle-network view, and a user-centric view; described by simple and complex use-cases and illustrated by a list of emerging and current projects from the academic and industrial worlds. We identified an empty space in innovation between the user and his car: paradoxically even if they are both in interaction, they are separated through different application uses. Future challenge is to interlace social concerns of the user within an intelligent and efficient driving

Ensuring Cyber-Security in Smart Railway Surveillance with SHIELD

Modern railways feature increasingly complex embedded computing systems for surveillance, that are moving towards fully wireless smart-sensors. Those systems are aimed at monitoring system status from a physical-security viewpoint, in order to detect intrusions and other environmental anomalies. However, the same systems used for physical-security surveillance are vulnerable to cyber-security threats, since they feature distributed hardware and software architectures often interconnected by ‘open networks’, like wireless channels and the Internet. In this paper, we show how the integrated approach to Security, Privacy and Dependability (SPD) in embedded systems provided by the SHIELD framework (developed within the EU funded pSHIELD and nSHIELD research projects) can be applied to railway surveillance systems in order to measure and improve their SPD level. SHIELD implements a layered architecture (node, network, middleware and overlay) and orchestrates SPD mechanisms based on ontology models, appropriate metrics and composability. The results of prototypical application to a real-world demonstrator show the effectiveness of SHIELD and justify its practical applicability in industrial settings

SANTO: Social Aerial NavigaTion in Outdoors

In recent years, the advances in remote connectivity, miniaturization of electronic components and computing power has led to the integration of these technologies in daily devices like cars or aerial vehicles. From these, a consumer-grade option that has gained popularity are the drones or unmanned aerial vehicles, namely quadrotors. Although until recently they have not been used for commercial applications, their inherent potential for a number of tasks where small and intelligent devices are needed is huge. However, although the integrated hardware has advanced exponentially, the refinement of software used for these applications has not beet yet exploited enough. Recently, this shift is visible in the improvement of common tasks in the field of robotics, such as object tracking or autonomous navigation. Moreover, these challenges can become bigger when taking into account the dynamic nature of the real world, where the insight about the current environment is constantly changing. These settings are considered in the improvement of robot-human interaction, where the potential use of these devices is clear, and algorithms are being developed to improve this situation. By the use of the latest advances in artificial intelligence, the human brain behavior is simulated by the so-called neural networks, in such a way that computing system performs as similar as possible as the human behavior. To this end, the system does learn by error which, in an akin way to the human learning, requires a set of previous experiences quite considerable, in order for the algorithm to retain the manners. Applying these technologies to robot-human interaction do narrow the gap. Even so, from a bird's eye, a noticeable time slot used for the application of these technologies is required for the curation of a high-quality dataset, in order to ensure that the learning process is optimal and no wrong actions are retained. Therefore, it is essential to have a development platform in place to ensure these principles are enforced throughout the whole process of creation and optimization of the algorithm. In this work, multiple already-existing handicaps found in pipelines of this computational gauge are exposed, approaching each of them in a independent and simple manner, in such a way that the solutions proposed can be leveraged by the maximum number of workflows. On one side, this project concentrates on reducing the number of bugs introduced by flawed data, as to help the researchers to focus on developing more sophisticated models. On the other side, the shortage of integrated development systems for this kind of pipelines is envisaged, and with special care those using simulated or controlled environments, with the goal of easing the continuous iteration of these pipelines.Thanks to the increasing popularity of drones, the research and development of autonomous capibilities has become easier. However, due to the challenge of integrating multiple technologies, the available software stack to engage this task is restricted. In this thesis, we accent the divergencies among unmanned-aerial-vehicle simulators and propose a platform to allow faster and in-depth prototyping of machine learning algorithms for this drones