Complete Simulation of Automata Networks

Consider a finite set A and . We study complete simulation of transformations of , also known as automata networks. For , a transformation of is n-complete of size m if it may simulate every transformation of by updating one register at a time. Using tools from memoryless computation, we establish that there is no n-complete transformation of size n, but there is one of size . By studying various constructions, we conjecture that the maximal time of simulation of any n-complete transformation is at least 2n. We also investigate the time and size of sequentially n-complete transformations, which may simulate every finite sequence of transformations of . Finally, we show that there is no n-complete transformation updating all registers in parallel, but there exists one updating all but one register in parallel. This illustrates the strengths and weaknesses of sequential and parallel models of computation

Grouping complex systems for classification and parallel simulation

This thesis is concerned with grouping complex systems by means of concurrent model, in order to aid in (i) formulation of classifications and (ii) induction of parallel simulation programs. It observes, and seeks f~ furmalize _ and then exploit, the strong structural resemblance between complex systems and occam programs. The thesis hypothesizes that groups of complex systems may be discriminated according to shared structural and behavioural characteristics. Such an analysis of the complex systems domain may be performed in the abstract with the aid of a model for capturing interesting features of complex systems. The resulting groups would form a classification of complex systems. An additional hypothesis is that, insofar as the model is able to capture sufficient . programmatic information, these groups may be used to define, automatically, algorithmic skeletons for the concurrent simulation of complex systems. In order to test these hypotheses, a specification model and an accompanying formal notation are developed. The model expresses properties of complex systems in a mixture of object-oriented and process-oriented styles .. The model is then used as the basis for performing both classification and automatic induction of parallel simulation programs. The thesis takes the view that specification models should not be overly complex, especially if the specifications are meant to be executable. Therefore the requirement for explicit consideration of concurrency on the part of specifiers is minimized. The thesis formulates specifications of classes of cellular automata and neural networks according to the proposed model. Procedures for verificati6If - and induction of parallel simulation programs are also included

On the Security of Software Systems and Services

This work investigates new methods for facing the security issues and threats arising from the composition of software. This task has been carried out through the formal modelling of both the software composition scenarios and the security properties, i.e., policies, to be guaranteed. Our research moves across three different modalities of software composition which are of main interest for some of the most sensitive aspects of the modern information society. They are mobile applications, trust-based composition and service orchestration. Mobile applications are programs designed for being deployable on remote platforms. Basically, they are the main channel for the distribution and commercialisation of software for mobile devices, e.g., smart phones and tablets. Here we study the security threats that affect the application providers and the hosting platforms. In particular, we present a programming framework for the development of applications with a static and dynamic security support. Also, we implemented an enforcement mechanism for applying fine-grained security controls on the execution of possibly malicious applications. In addition to security, trust represents a pragmatic and intuitive way for managing the interactions among systems. Currently, trust is one of the main factors that human beings keep into account when deciding whether to accept a transaction or not. In our work we investigate the possibility of defining a fully integrated environment for security policies and trust including a runtime monitor. Finally, Service-Oriented Computing (SOC) is the leading technology for business applications distributed over a network. The security issues related to the service networks are many and multi-faceted. We mainly deal with the static verification of secure composition plans of web services. Moreover, we introduce the synthesis of dynamic security checks for protecting the services against illegal invocations

Computer Aided Verification

The open access two-volume set LNCS 11561 and 11562 constitutes the refereed proceedings of the 31st International Conference on Computer Aided Verification, CAV 2019, held in New York City, USA, in July 2019. The 52 full papers presented together with 13 tool papers and 2 case studies, were carefully reviewed and selected from 258 submissions. The papers were organized in the following topical sections: Part I: automata and timed systems; security and hyperproperties; synthesis; model checking; cyber-physical systems and machine learning; probabilistic systems, runtime techniques; dynamical, hybrid, and reactive systems; Part II: logics, decision procedures; and solvers; numerical programs; verification; distributed systems and networks; verification and invariants; and concurrency

Interactive Model-Based Compilation: A Modeller-Driven Development Approach

There is a growing tendency for using domain-specific languages, which help domain experts to stay focussed on abstract problem solutions. It is important to carefully design these languages and tools, which fundamentally perform model-to-model transformations. The quality of both usually decides the effectiveness of the subsequent development and therefore the quality of the final applications. However, as the complexity and safety requirements of modern systems grow, it becomes increasingly burdensome to create highly customized languages and difficult to provide reasonable overviews within these tools. This thesis introduces a new interactive model-based compilation methodology. Compilations for arbitrary model-to-model transformations are themselves described as models. They can be instantiated for particular inputs, e. g. a program, to create concrete compilation runs, which return the result of that compilation. The compilation instance is interactively observable. Intermediate results serve as new inputs and as documentation. They can be used to create highly customized views and facilitate understandability. This methodology guides modellers from the start of the compilation to the final result so that they can interactively refine their models. The methodology has been implemented and validated as the KIELER Compiler (KiCo) and is available as part of the KIELER open-source project. It is used to implement the current reference compiler for the SCCharts language, a statecharts dialect designed for specifying safety-critical reactive systems based on a synchronous model of computation. The interactive model-based compilation approach was key to the rapid prototyping of three different compilation strategies, as well as new language extensions, variations and closely related languages. The results are verified with benchmarks, which are again modelled using the same approach and technology. The usability of the SCCharts language and the KiCo tooling is documented with long-term surveys and real-life industrial, academic and teaching examples

Natively probabilistic computation

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Brain and Cognitive Sciences, 2009.Includes bibliographical references (leaves 129-135).I introduce a new set of natively probabilistic computing abstractions, including probabilistic generalizations of Boolean circuits, backtracking search and pure Lisp. I show how these tools let one compactly specify probabilistic generative models, generalize and parallelize widely used sampling algorithms like rejection sampling and Markov chain Monte Carlo, and solve difficult Bayesian inference problems. I first introduce Church, a probabilistic programming language for describing probabilistic generative processes that induce distributions, which generalizes Lisp, a language for describing deterministic procedures that induce functions. I highlight the ways randomness meshes with the reflectiveness of Lisp to support the representation of structured, uncertain knowledge, including nonparametric Bayesian models from the current literature, programs for decision making under uncertainty, and programs that learn very simple programs from data. I then introduce systematic stochastic search, a recursive algorithm for exact and approximate sampling that generalizes a popular form of backtracking search to the broader setting of stochastic simulation and recovers widely used particle filters as a special case. I use it to solve probabilistic reasoning problems from statistical physics, causal reasoning and stereo vision. Finally, I introduce stochastic digital circuits that model the probability algebra just as traditional Boolean circuits model the Boolean algebra.(cont.) I show how these circuits can be used to build massively parallel, fault-tolerant machines for sampling and allow one to efficiently run Markov chain Monte Carlo methods on models with hundreds of thousands of variables in real time. I emphasize the ways in which these ideas fit together into a coherent software and hardware stack for natively probabilistic computing, organized around distributions and samplers rather than deterministic functions. I argue that by building uncertainty and randomness into the foundations of our programming languages and computing machines, we may arrive at ones that are more powerful, flexible and efficient than deterministic designs, and are in better alignment with the needs of computational science, statistics and artificial intelligence.by Vikash Kumar Mansinghka.Ph.D

Computer Aided Verification

The open access two-volume set LNCS 11561 and 11562 constitutes the refereed proceedings of the 31st International Conference on Computer Aided Verification, CAV 2019, held in New York City, USA, in July 2019. The 52 full papers presented together with 13 tool papers and 2 case studies, were carefully reviewed and selected from 258 submissions. The papers were organized in the following topical sections: Part I: automata and timed systems; security and hyperproperties; synthesis; model checking; cyber-physical systems and machine learning; probabilistic systems, runtime techniques; dynamical, hybrid, and reactive systems; Part II: logics, decision procedures; and solvers; numerical programs; verification; distributed systems and networks; verification and invariants; and concurrency