Abstract
Device miniaturization is pointing towards tolerating imperfect hardware provided it is "good enough". Software design theories will have to face the impact of such a trend sooner or later. A school of thought in software design is relational: it expresses specifications as relations and derives programs from specifications using relational algebra. This paper proposes that linear algebra be adopted as an evolution of relational algebra able to cope with the quantification of the impact of imperfect hardware on (otherwise) reliable software. The approach is illustrated by developing a monadic calculus for component oriented software construction with a probabilistic dimension quantifying (by linear algebra) the propagation of imperfect behaviour from lower to upper layers of software systems. © 2014 Springer International Publishing.

Abstract
Deduplication of primary storage volumes in a cloud computing environment is increasingly desirable, as the resulting space savings contribute to the cost effectiveness of a large scale multi-tenant infrastructure. However, traditional archival and backup deduplication systems impose prohibitive overhead for latency-sensitive applications deployed at these infrastructures while, current primary deduplication systems rely on special cluster filesystems, centralized components, or restrictive workload assumptions. We present DEDIS, a fully-distributed and dependable system that performs exact and cluster-wide background deduplication of primary storage. DEDIS does not depend on data locality and works on top of any unsophisticated storage backend, centralized or distributed, that exports a basic shared block device interface. The evaluation of an open-source prototype shows that DEDIS scales out and adds negligible overhead

Abstract
Important challenges in interoperability, reliability, and scalability need to be addressed before the Smart Grid vision can be fulfilled. The sheer scale of the electric grid and the criticality of the communication among its subsystems for proper management, demands a scalable and reliable communication framework able to work in an heterogeneous and dynamic environment. Moreover, the need to provide full interoperability between diverse current and future energy and non-energy systems, along with seamless discovery and configuration of a large variety of networked devices, ranging from the resource constrained sensing devices to servers in data centers, requires an implementation-agnostic Service Oriented Architecture. In this position paper we propose that this challenge can be addressed with a generic framework that reconciles the reliability and scalability of Peer-to-Peer systems, with the industrial standard interoperability of Web Services. We illustrate the flexibility of the proposed framework by showing how it can be used in two specific scenarios.

Abstract
The automatic elimination of duplicate data in a storage system, commonly known as deduplication, is increasingly accepted as an effective technique to reduce storage costs. Thus, it has been applied to different storage types, including archives and backups, primary storage, within solid-state drives, and even to random access memory. Although the general approach to deduplication is shared by all storage types, each poses specific challenges and leads to different trade-offs and solutions. This diversity is often misunderstood, thus underestimating the relevance of new research and development. The first contribution of this article is a classification of deduplication systems according to six criteria that correspond to key design decisions: granularity, locality, timing, indexing, technique, and scope. This classification identifies and describes the different approaches used for each of them. As a second contribution, we describe which combinations of these design decisions have been proposed and found more useful for challenges in each storage type. Finally, outstanding research challenges and unexplored design points are identified and discussed.

Abstract

Abstract
As a complex artefact, software has to meet requirements formulated and verified at different levels of abstraction. A basic distinction is drawn between behavioural (dynamic) and data (static) aspects. From an educational point of view, although disguised under a number of different designations, both issues are usually present, but kept separated, in typical Computer Science undergraduate curricula. It is often argued that they tackle orthogonal problems through essentially different methods. This paper explores an alternative path in which students progress from equational to hybrid specifications in a uniform setting, integrating paradigms, combining data and behaviour, and dealing appropriately with systems evolution and reconfiguration.