Abstract
This paper presents the Electrum Analyzer, a free-software tool to validate and perform model checking of Electrum specifications. Electrum is an extension of Alloy that enriches its relational logic with LTL operators, thus simplifying the specification of dynamic systems. The Analyzer supports both automatic bounded model checking, with an encoding into SAT, and unbounded model checking, with an encoding into SMV. Instance, or counter-example, traces are presented back to the user in a unified visualizer. Features to speed up model checking are offered, including a decomposed parallel solving strategy and the extraction of symbolic bounds. Source code: https://github.com/haslab/ElectrumVideo: https://youtu.be/FbjlpvjgMDA. © 2018 Copyright held by the owner/author(s).

Abstract
The Robot Operating System (ROS) is an open source framework for the development of robotic software, in which a typical system consists of multiple processes communicating under a publisher-subscriber architecture. A great deal of development time goes into orchestration and making sure that the communication interfaces comply with the expected contracts (e.g. receiving a message leads to the publication of another message). Orchestration mistakes are only detected during runtime, stressing the importance of component and integration testing in the verification process. Property-based Testing is fitting in this context, since it is based on the specification of contracts and treats tested components as black boxes, but there is no support for it in ROS. In this paper, we present a first approach towards automatic generation of test scripts for property-based testing of various configurations of a ROS system.

Abstract

Abstract
Scalability is one of the most relevant features of today’s data management systems. In order to achieve high scalability and availability, recent distributed key-value stores refrain from costly replica coordination when processing requests. However, these systems typically do not perform well under churn. In this paper, we propose DataFlagons, a large-scale key-value store that integrates epidemic dissemination with a probabilistic total order broadcast algorithm. By ensuring that all replicas process requests in the same order, DataFlagons provides probabilistic strong data consistency while achieving high scalability and robustness under churn. © 2018, IFIP International Federation for Information Processing.

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Abstract