Proceedings of the 11th Overture Workshop

The 11th Overture Workshop was held in Aarhus, Denmark on Wed/Thu 28–29th Au- gust 2013. It was the 11th workshop in the current series focusing on the Vienna De- velopment Method (VDM) and particularly its community-based tools development project, Overture (http://www.overturetool.org/), and related projects such as COMPASS(http://www.compass-research.eu/) and DESTECS (http://www.destecs.org). Invited talks were given by Yves Ledru and Joe Kiniry. The workshop attracted 25 participants representing 10 nationalities. The goal of the workshop was to provide a forum to present new ideas, to identify and encourage new collaborative research, and to foster current strands of work towards publication in the mainstream conferences and journals. The Overture initiative held its first workshop at FM’05. Workshops were held subsequently at FM’06, FM’08 and FM’09, FM’11, FM’12 and in between

SAM-SoS: A stochastic software architecture modeling and verification approach for complex System-of-Systems

A System-of-Systems (SoS) is a complex, dynamic system whose Constituent Systems (CSs) are not known precisely at design time, and the environment in which they operate is uncertain. SoS behavior is unpredictable due to underlying architectural characteristics such as autonomy and independence. Although the stochastic composition of CSs is vital to achieving SoS missions, their unknown behaviors and impact on system properties are unavoidable. Moreover, unknown conditions and volatility have significant effects on crucial Quality Attributes (QAs) such as performance, reliability and security. Hence, the structure and behavior of a SoS must be modeled and validated quantitatively to foresee any potential impact on the properties critical for achieving the missions. Current modeling approaches lack the essential syntax and semantics required to model and verify SoS behaviors at design time and cannot offer alternative design choices for better design decisions. Therefore, the majority of existing techniques fail to provide qualitative and quantitative verification of SoS architecture models. Consequently, we have proposed an approach to model and verify Non-Deterministic (ND) SoS in advance by extending the current algebraic notations for the formal models as a hybrid stochastic formalism to specify and reason architectural elements with the required semantics. A formal stochastic model is developed using a hybrid approach for architectural descriptions of SoS with behavioral constraints. Through a model-driven approach, stochastic models are then translated into PRISM using formal verification rules. The effectiveness of the approach has been tested with an end-to-end case study design of an emergency response SoS for dealing with a fire situation. Architectural analysis is conducted on the stochastic model, using various qualitative and quantitative measures for SoS missions. Experimental results reveal critical aspects of SoS architecture model that facilitate better achievement of missions and QAs with improved design, using the proposed approach

The hArtes Tool Chain

This chapter describes the different design steps needed to go from legacy code to a transformed application that can be efficiently mapped on the hArtes platform

Enhancing System Realisation in Formal Model Development

Software for mission-critical systems is sometimes analysed using formal specification to increase the chances of the system behaving as intended. When sufficient insights into the system have been obtained from the formal analysis, the formal specification is realised in the form of a software implementation. One way to realise the system's software is by automatically generating it from the formal specification -- a technique referred to as code generation. However, in general it is difficult to make guarantees about the correctness of the generated code -- especially while requiring automation of the steps involved in realising the formal specification. This PhD dissertation investigates ways to improve the automation of the steps involved in realising and validating a system based on a formal specification. The approach aims to develop properly designed software tools which support the integration of formal methods tools into the software development life cycle, and which leverage the formal specification in the subsequent validation of the system. The tools developed use a new code generation infrastructure that has been built as part of this PhD project and implemented in the Overture tool -- a formal methods tool that supports the Vienna Development Method. The development of the code generation infrastructure has involved the re-design of the software architecture of Overture. The new architecture brings forth the reuse and extensibility features of Overture to take into account the needs and requirements of software extensions targeting Overture. The tools developed in this PhD project have successfully supported three case studies from externally funded projects. The feedback received from the case study work has further helped improve the code generation infrastructure and the tools built using it

Modeling and Simulation of Biological Systems through Electronic Design Automation techniques

Modeling and simulation of biological systems is a key requirement for integrating invitro and in-vivo experimental data. In-silico simulation allows testing different experimental conditions, thus helping in the discovery of the dynamics that regulate the system. These dynamics include errors in the cellular information processing that are responsible for diseases such as cancer, autoimmunity, and diabetes as well as drug effects to the system (Gonalves, 2013). In this context, modeling approaches can be classified into two categories: quantitative and qualitative models. Quantitative modeling allows for a natural representation of molecular and gene networks and provides the most precise prediction. Nevertheless, the lack of kinetic data (and of quantitative data in general) hampers its use for many situations (Le Novere, 2015). In contrast, qualitative models simplify the biological reality and are often able to reproduce the system behavior. They cannot describe actual concentration levels nor realistic time scales. As a consequence, they cannot be used to explain and predict the outcome of biological experiments that yield quantitative data. However, given a biological network consisting of input (e.g., receptors), intermediate, and output (e.g., transcription factors) signals, they allow studying the input-output relationships through discrete simulation (Samaga, 2013). Boolean models are gaining an increasing interest in reproducing dynamic behaviors, understanding processes, and predicting emerging properties of cellular signaling networks through in-silico experiments. They are emerging as a valid alternative to the quantitative approaches (i.e., based on ordinary differential equations) for exploratory modeling when little is known about reaction kinetics or equilibrium constants in the context of gene expression or signaling. Even though several approaches and software have been recently proposed for logic modeling of biological systems, they are limited to specific contexts and they lack of automation in analyzing biological properties such as complex attractors, and molecule vulnerability. This thesis proposes a platform based on Electronic Design Automation (EDA) technologies for qualitative modeling and simulation of Biological Systems. It aims at overtaking limitations that affect the most recent qualitative tools

Integrated product design and life-cycle assessment

Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 1998.Includes bibliographical references (p. 111-114).by Inês Sousa.M.Eng

TalkyCars: A Distributed Software Platform for Cooperative Perception among Connected Autonomous Vehicles based on Cellular-V2X Communication

Autonomous vehicles are required to operate among highly mixed traffic during their early market-introduction phase, solely relying on local sensory with limited range. Exhaustively comprehending and navigating complex urban environments is potentially not feasible with sufficient reliability using the aforesaid approach. Addressing this challenge, intelligent vehicles can virtually increase their perception range beyond their line of sight by utilizing Vehicle-to-Everything (V2X) communication with surrounding traffic participants to perform cooperative perception. Since existing solutions face a variety of limitations, including lack of comprehensiveness, universality and scalability, this thesis aims to conceptualize, implement and evaluate an end-to-end cooperative perception system using novel techniques. A comprehensive yet extensible modeling approach for dynamic traffic scenes is proposed first, which is based on probabilistic entity-relationship models, accounts for uncertain environments and combines low-level attributes with high-level relational- and semantic knowledge in a generic way. Second, the design of a holistic, distributed software architecture based on edge computing principles is proposed as a foundation for multi-vehicle high-level sensor fusion. In contrast to most existing approaches, the presented solution is designed to rely on Cellular-V2X communication in 5G networks and employs geographically distributed fusion nodes as part of a client-server configuration. A modular proof-of-concept implementation is evaluated in different simulated scenarios to assess the system\u27s performance both qualitatively and quantitatively. Experimental results show that the proposed system scales adequately to meet certain minimum requirements and yields an average improvement in overall perception quality of approximately 27 %

On the Extensibility of Formal Methods Tools

Modern software systems often have long lifespans over which they must continually evolve to meet new, and sometimes unforeseen, requirements. One way to effectively deal with this is by developing the system as a series of extensions. As requirements change, the system evolves through the addition of new extensions and, potentially, the removal of existing extensions. In order for this kind of development process to thrive, it is necessary that the system have a high level of extensibility. Extensibility is the capability of a system to support the gradual addition of new, unplanned functionalities. This dissertation investigates extensibility of software systems and focuses on a particular class of software: formal methods tools. The approach is broad in scope. Extensibility of systems is addressed in terms of design, analysis and improvement, which are carried out in terms of source code and software architecture. For additional perspective, extensibility is also considered in the context of formal modelling. The work carried out in this dissertation led to the development of various extensions to the Overture tool supporting the Vienna Development Method, including a new proof obligation generator and integration with theorem provers. Additionally, the extensibility of Overture itself was also improved and it now better supports the development and integration of various kinds of extensions. Finally, extensibility techniques have been applied to formal modelling, leading to an extensible architectural style for formal models

Cyber-Physical Systems Design: Formal Foundations, Methods and Integrated Tool Chains

The engineering of dependable cyber-physical systems (CPSs) is inherently collaborative, demanding cooperation between diverse disciplines. A goal of current research is the development of integrated tool chains for model-based CPS design that support co-modelling, analysis, co-simulation, testing and implementation. We discuss the role of formal methods in addressing three key aspects of this goal: providing reasoning support for semantically heterogeneous models, managing the complexity and scale of design space exploration, and supporting traceability and provenance in the CPS design set. We briefly outline an approach to the development of such a tool chain based on existing tools and discuss ongoing challenges and open research questions in this area