Persistent Contextual Values as Inter-Process Layers

Mobile applications today often fail to be context aware when they also need to be customizable and efficient at run-time. Context-oriented programming allows programmers to develop applications that are more context aware. Its central construct, the so-called layer, however, is not customizable. We propose to use novel persistent contextual values for mobile development. Persistent contextual values automatically adapt their value to the context. Furthermore they provide access without overhead. Key-value configuration files contain the specification of contextual values and the persisted contextual values themselves. By modifying the configuration files, the contextual values can easily be customized for every context. From the specification, we generate code to simplify development. Our implementation, called Elektra, permits development in several languages including C++ and Java. In a benchmark we compare layer activations between threads and between applications. In a case study involving a web-server on a mobile embedded device the performance overhead is minimal, even with many context switches.Comment: 8 pages Mobile! 16, October 31, 2016, Amsterdam, Netherland

On the Prediction of Smart Contracts\u2019 Behaviours

Smart contracts are pieces of software stored on the blockchain that control the transfer of assets between parties under certain conditions. In this paper we analyze the bahaviour of smart contracts and the interaction with external actors in order to maximize objective functions. We define a core language of programs with a minimal set of smart contract primitives and we describe the whole system as a parallel composition of smart contracts and users. We therefore express the system behaviour as a first logic formula in Presburger arithmetics and study the maximum profit for each actor by solving arithmetic constraints

VMC: A Tool for Product Variability Analysis

Abstract. We present VMC, a tool for the modeling and analysis of variability in product lines. It accepts a product family specified as a modal transition system, possibly with additional variability constraints, after which it can automatically generate all the family’s valid products, visualize the family/products as modal/labeled transition systems, and efficiently model check properties expressed in an action- and state-based branching-time temporal logic over products and families alike.

Dementia-related genetic variants in an Italian population of early-onset Alzheimer’s disease

Early-onset Alzheimer’s disease (EOAD) is the most common form of early-onset dementia. Although three major genes have been identified as causative, the genetic contribution to the disease remains unsolved in many patients. Recent studies have identified pathogenic variants in genes representing a risk factor for developing Alzheimer’s disease (AD) and in causative genes for other degenerative dementias as responsible for EOAD. To study them further, we investigated a panel of candidate genes in 102 Italian EOAD patients, 45.10% of whom had a positive family history and 21.74% with a strong family history of dementia. We found that 10.78% of patients carried pathogenic or likely pathogenic variants, including a novel variant, in PSEN1, PSEN2, or APP, and 7.84% showed homozygosity for the ε4 APOE allele. Additionally, 7.84% of patients had a moderate risk allele in PSEN1, PSEN2, or TREM2 genes. Besides, we observed that 12.75% of our patients carried only a variant in genes associated with other neurodegenerative diseases. The combination of these variants contributes to explain 46% of cases with a definite familiarity and 32% of sporadic forms. Our results confirm the importance of extensive genetic screening in EOAD for clinical purposes, to select patients for future treatments and to contribute to the definition of overlapping pathogenic mechanisms between AD and other forms of dementia