Abstract
Automotive Safety Integrity Levels (ASILs) are used in the new automotive functional safety standard, ISO 26262, as a key part of managing safety requirements throughout a top-down design process. The ASIL decomposition concept, outlined in the standard, allows the safety requirements to be divided between multiple components of the system whilst still meeting the ASILs initially allocated to system-level hazards. Existing exhaustive automatic decomposition techniques drastically reduce the effort of performing such tasks manually. However, the combinatorial nature of the problem leaves such exhaustive techniques with a scalability issue. To overcome this problem, we have developed a new technique that uses a penalty-based genetic algorithm to efficiently explore the search space and identify optimum assignments of ASILs to the system components. The technique has been applied to a hybrid braking system to evaluate its effectiveness. © 2013 Springer-Verlag.

Abstract
Recently, tuple-stores have become pivotal structures in many information systems. Their ability to handle large datasets makes them important in an era with unprecedented amounts of data being produced and exchanged. However, these tuple-stores typically rely on structured peer-to-peer protocols which assume moderately stable environments. Such assumption does not always hold for very large scale systems sized in the scale of thousands of machines. In this paper we present a novel approach to the design of a tuple-store. Our approach follows a stratified design based on an unstructured substrate. We focus on this substrate and how the use of epidemic protocols allow reaching high dependability and scalability.

Abstract
The design of an Autonomous Underwater Vehicle (AUV) is governed by a complex tradeoff between mission performance and required payload sensors, and taking into account possible constraints in fabrication, assembly and operational logistics. On a commercial level, the technology is relatively mature, with several companies offering off-the-shelf AUV solutions in a wide range of sizes and performance levels, for a wide variety of operational scenarios. However, to ensure proper performance in specific applications, such broad-range systems require factory customization, with the consequent impact in time and cost. This paper describes a program for the development of underwater vehicles based on modular building blocks. In this case, modularity encompasses both physical parts and also software and control systems. These modules can be rearranged, replaced or individually redesigned to yield a great variety of AUV configurations in a relatively short time. The paper describes the development of MARES, a small hovering AUV, and also TriMARES, a custom 3-body hybrid AUV/ROV, built from the same modules in little over 6 months.

Abstract
Developing applications for resource-constrained embedded systems is a challenging task specially when applications must adapt to changes in their operating conditions or environment. To ensure an appropriate response at all times, it is highly desirable to develop applications that can dynamically adapt their behavior at run-time. In this paper we introduce an architecture that allows the specification of adaptable behavior through an external, high-level and platform-independent domain-specific language (DSL). The DSL is used here to define adaptation rules that change the run-time behavior of the application depending on various operational factors, such as time constraints. We illustrate the use of the DSL in an application to mobile robot navigation using smartphones, where experimental results highlight the benefits of specifying the adaptable behavior in a flexible and external way to the main application logic. © André C. Santos, João M. P. Cardoso, Pedro C. Diniz and Diogo R. Ferreira.

Abstract
In Computer Science stepwise refinement of algebraic specifications is a well-known formal methodology for rigorous program development. This paper illustrates how techniques from Algebraic Logic, in particular that of interpretation, understood as a multifunction that preserves and reflects logical consequence, capture a number of relevant transformations in the context of software design, reuse, and adaptation, difficult to deal with in classical approaches. Examples include data encapsulation and the decomposition of operations into atomic transactions. But if interpretations open such a new research avenue in program refinement, (conceptual) tools are needed to reason about them. In this line, the paper's main contribution is a study of the correspondence between logical interpretations and morphisms of a particular kind of coalgebras. This opens way to the use of coalgebraic constructions, such as simulation and bisimulation, in the study of interpretations between (abstract) logics.

Abstract
We characterize the minimum number of measurements needed to drive to zero the minimum mean squared error (MMSE) of Gaussian mixture model (GMM) input signals in the low-noise regime. The result also hints at almost phasetransition optimal recovery procedures based on a classification and reconstruction approach.