Harnessing a Refinement Theory to Compute Loop Functions

AbstractWe consider a while loop on some space S and we are interested in deriving the function that this loop defines between its initial states and its final states (when it terminates). Such a capability is useful in a wide range of applications, including reverse engineering, software maintenance, program comprehension, and program verification. In the absence of a general theoretical solution to the problem of deriving the function of a loop, we explore engineering solutions. In this paper we use a relational refinement calculus to approach this complex problem in a systematic manner. Our approach has many drawbacks, some surmountable and some not (being inherent to the approach); nevertheless, it offers a way to automatically derive the function of loops or an approximation thereof, under some conditions

Modélisation et validation formelle des règles d'exploitation ferroviaires

Le système européen de surveillance du trafic ferroviaire (en anglais, European Rail Traffic Management System, ERTMS) est un système complexe de contrôle/commande et de signalisation ferroviaire mettant en ½uvre des règles européennes d'exploitation ferroviaires. Cet article propose une étude de cas basée sur deux scénarios extraits de ces règles, un scénario nominal d'autorisation de mouvement et un scénario exceptionnel de franchissement d'un arrêt. En effet, on trouve dans ces scénarios des aspects fonctionnels et de sécurité. Ces aspects nécessitent, d'une part, une modélisation fonctionnelle enrichie par des modèles décrivant la politique de sécurité et les autorisations données aux agents agissant sur le système, et d'autre part, une validation formelle. Pour ce faire, nous avons utilisé la plate-forme B4MSecure, fondée sur l'approche IDM (Ingénierie Dirigée par les Modèles), produisant à partir des modèles UML des spécifications formelles B. L'objectif de ces spécifications résultantes est de valider ces scénarios à l'aide d'outils d'animation et de preuve de spécifications B afin de garantir une analyse rigoureuse de la fonctionnalité et de la politique de sécurité

B Formal Validation of ERTMS/ETCS Railway Operating Rules

The B method is a formal specification method and a means of formal verification and validation of safety-critical systems such as railway systems. In this short paper, we use the B4MSecure tool to transform the UML models, fulfilling requirements of European Railway Traffic Management System (ERTMS) operating rules, into B specifications in order to formally validate them

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

Hierarchical Checkpoint Protocol in Data Grids

Grid of computing nodes has emerged as a representative means of connecting distributed computers or resources scattered all over the world for the purpose of computing and distributed storage. Since fault tolerance becomes complex due to the availability of resources in decentralized grid environment, it can be used in connection with replication in data grids. The objective of our work is to present fault tolerance in data grids with data replication-driven model based on clustering. The performance of the protocol is evaluated with Omnet++ simulator. The computational results show the efficiency of our protocol in terms of recovery time and the number of process in rollbacks

Bare‐Bones particle Swarm optimization‐based quantization for fast and energy efficient convolutional neural networks

Neural network quantization is a critical method for reducing memory usage and computational complexity in deep learning models, making them more suitable for deployment on resource-constrained devices. In this article, we propose a method called BBPSO-Quantizer, which utilizes an enhanced Bare-Bones Particle Swarm Optimization algorithm, to address the challenging problem of mixed precision quantization of convolutional neural networks (CNNs). Our proposed algorithm leverages a new population initialization, a robust screening process, and a local search strategy to improve the search performance and guide the population towards a feasible region. Additionally, Deb's constraint handling method is incorporated to ensure that the optimized solutions satisfy the functional constraints. The effectiveness of our BBPSO-Quantizer is evaluated on various state-of-the-art CNN architectures, including VGG, DenseNet, ResNet, and MobileNetV2, using CIFAR-10, CIFAR-100, and Tiny ImageNet datasets. Comparative results demonstrate that our method delivers an excellent tradeoff between accuracy and computational efficiency