Combining behavioural types with security analysis

Today's software systems are highly distributed and interconnected, and they increasingly rely on communication to achieve their goals; due to their societal importance, security and trustworthiness are crucial aspects for the correctness of these systems. Behavioural types, which extend data types by describing also the structured behaviour of programs, are a widely studied approach to the enforcement of correctness properties in communicating systems. This paper offers a unified overview of proposals based on behavioural types which are aimed at the analysis of security properties

Computer program to calculate three-dimensional boundary layer flows over wings with wall mass transfer

A system of computer programs for calculating three dimensional transonic flow over wings, including details of the three dimensional viscous boundary layer flow, was developed. The flow is calculated in two overlapping regions: an outer potential flow region, and a boundary layer region in which the first order, three dimensional boundary layer equations are numerically solved. A consistent matching of the two solutions is achieved iteratively, thus taking into account viscous-inviscid interaction. For the inviscid outer flow calculations, the Jameson-Caughey transonic wing program FLO 27 is used, and the boundary layer calculations are performed by a finite difference boundary layer prediction program. Interface programs provide communication between the two basic flow analysis programs. Computed results are presented for the NASA F8 research wing, both with and without distributed surface suction

Distributed Random Convex Programming via Constraints Consensus

This paper discusses distributed approaches for the solution of random convex programs (RCP). RCPs are convex optimization problems with a (usually large) number N of randomly extracted constraints; they arise in several applicative areas, especially in the context of decision under uncertainty, see [2],[3]. We here consider a setup in which instances of the random constraints (the scenario) are not held by a single centralized processing unit, but are distributed among different nodes of a network. Each node "sees" only a small subset of the constraints, and may communicate with neighbors. The objective is to make all nodes converge to the same solution as the centralized RCP problem. To this end, we develop two distributed algorithms that are variants of the constraints consensus algorithm [4],[5]: the active constraints consensus (ACC) algorithm, and the vertex constraints consensus (VCC) algorithm. We show that the ACC algorithm computes the overall optimal solution in finite time, and with almost surely bounded communication at each iteration. The VCC algorithm is instead tailored for the special case in which the constraint functions are convex also w.r.t. the uncertain parameters, and it computes the solution in a number of iterations bounded by the diameter of the communication graph. We further devise a variant of the VCC algorithm, namely quantized vertex constraints consensus (qVCC), to cope with the case in which communication bandwidth among processors is bounded. We discuss several applications of the proposed distributed techniques, including estimation, classification, and random model predictive control, and we present a numerical analysis of the performance of the proposed methods. As a complementary numerical result, we show that the parallel computation of the scenario solution using ACC algorithm significantly outperforms its centralized equivalent

Automatic translation of non-repetitive OpenMP to MPI

Cluster platforms with distributed-memory architectures are becoming increasingly available low-cost solutions for high performance computing. Delivering a productive programming environment that hides the complexity of clusters and allows writing efficient programs is urgently needed. Despite multiple efforts to provide shared memory abstraction, message-passing (MPI) is still the state-of-the-art programming model for distributed-memory architectures. ^ Writing efficient MPI programs is challenging. In contrast, OpenMP is a shared-memory programming model that is known for its programming productivity. Researchers introduced automatic source-to-source translation schemes from OpenMP to MPI so that programmers can use OpenMP while targeting clusters. Those schemes limited their focus on OpenMP programs with repetitive communication patterns (where the analysis of communication can be simplified). This dissertation reduces this limitation and presents a novel OpenMP-to-MPI translation scheme that covers OpenMP programs with both repetitive and non-repetitive communication patterns. We target laboratory-size clusters of ten to hundred nodes (commonly found in research laboratories and small enterprises). ^ With our translation scheme, six non-repetitive and four repetitive OpenMP benchmarks have been efficiently scaled to a cluster of 64 cores. By contrast, the state-of-the-art translator scaled only the four repetitive benchmarks. In addition, our translation scheme was shown to outperform or perform as well as the state-of-the-art translator. We also compare the translation scheme with available hand-coded MPI and Unified Parallel C (UPC) programs

Employing MPI Collectives for Timing Analysis on Embedded Multi-Cores

Static WCET analysis of parallel programs running on shared-memory multicores suffers from high pessimism. Instead, distributed memory platforms which communicate via messages may be one solution for manycore systems. Message Passing Interface (MPI) is a standard for communication on these platforms. We show how its concept of collective operations can be employed for timing analysis. The idea is that the worst-case execution time (WCET) of a parallel program may be estimated by adding the WCET estimates of sequential program parts to the WCET estimates of communication parts. Therefore, we first analyse the two MPI operations MPI_Allreduce and MPI_Sendrecv. Employing these results, we make a timing analysis of the conjugate gradient (CG) benchmark from the NAS parallel benchmark suite

A game-based approach to the teaching of object-oriented programming languages

Students often have difficulties when trying to understand the concepts of object-oriented programming (OOP). This paper presents a contribution to the teaching of OOP languages through a game-oriented approach based on the interaction with tangible user interfaces (TUIs). The use of a specific type of commercial distributed TUI (Sifteo cubes), in which several small physical devices have sensing, wireless communication and user-directed output capabilities, is applied to the teaching of the C# programming language, since the operation of these devices can be controlled by user programs written in C#. For our experiment, we selected a sample of students with a sufficient knowledge about procedural programming, which was divided into two groups: The first one had a standard introductory C# course, whereas the second one had an experimental C# course that included, in addition to the contents of the previous one, two demonstration programs that illustrated some OOP basic concepts using the TUI features. Finally, both groups completed two tests: a multiple-choice exam for evaluating the acquisition of basic OOP concepts and a C# programming exercise. The analysis of the results from the tests indicates that the group of students that attended the course including the TUI demos showed a higher interest level (i.e. they felt more motivated) during the course exposition than the one that attended the standard introductory C# course. Furthermore, the students from the experimental group achieved an overall better mark. Therefore, we can conclude that the technological contribution of Sifteo cubes – used as a distributed TUI by which OOP basic concepts are represented in a tangible and a visible way – to the teaching of the C# language has a positive influence on the learning of this language and such basic concepts

Analyzing One-Sided Communication Using Memory Access Diagrams

n recent years, one-sided communication has emerged as an alternative to message-based communication to improve the scalability of distributed programs. Decoupling communication and synchronization in such programs allows for more asynchronous execution of processes, but introduces new challenges to ensure program correctness and efficiency. The concept of memory access diagrams presented in this paper opens up a new analysis perspective to the programmer. Our approach visualizes the interaction of synchronous, asynchronous, and remote memory accesses. We present an interactive tool that can be used to perform a postmortem analysis of a distributed program execution. The tool supports hybrid parallel programs, shared MPI windows, and GASPI communication operations. In two application studies taken from the European aerospace industry we illustrate the usefulness of memory access diagrams for visualizing and understanding the logical causes of programming errors, performance flaws, and to find optimization opportunities

Multi-agent Confidential Abductive Reasoning

In the context of multi-agent hypothetical reasoning, agents typically have partial knowledge about their environments, and the union of such knowledge is still incomplete to represent the whole world. Thus, given a global query they collaborate with each other to make correct inferences and hypothesis, whilst maintaining global constraints. Most collaborative reasoning systems operate on the assumption that agents can share or communicate any information they have. However, in application domains like multi-agent systems for healthcare or distributed software agents for security policies in coalition networks, confidentiality of knowledge is an additional primary concern. These agents are required to collaborately compute consistent answers for a query whilst preserving their own private information. This paper addresses this issue showing how this dichotomy between "open communication" in collaborative reasoning and protection of confidentiality can be accommodated. We present a general-purpose distributed abductive logic programming system for multi-agent hypothetical reasoning with confidentiality. Specifically, the system computes consistent conditional answers for a query over a set of distributed normal logic programs with possibly unbound domains and arithmetic constraints, preserving the private information within the logic programs. A case study on security policy analysis in distributed coalition networks is described, as an example of many applications of this system

Application Development using Compositional Performance Analysis

A parallel programming archetype [Cha94, CMMM95] is an abstraction that captures the common features of a class of problems with a similar computational structure and combines them with a parallelization strategy to produce a pattern of dataflow and communication. Such abstractions are useful in application development, both as a conceptual framework and as a basis for tools and techniques. The efficiency of a parallel program can depend a great deal on how its data and tasks are decomposed and distributed. This thesis describes a simple performance evaluation methodology that includes an analytic model for predicting the performance of parallel and distributed computations developed for multicomputer machines and networked personal computers. This analytic model can be supplemented by a simulation infrastructure for application writers to use when developing parallel programs using archetypes. These performance evaluation tools were developed with the following restricted goal in mind: We require accuracy of the analytic model and simulation infrastructure only to the extent that they suggest directions for the programmer to make the appropriate optimizations. This restricted goal sacrifices some accuracy, but makes the tools simpler and easier to use. A programmer can use these tools to design programs with decomposition and distribution specialized to a given machine configuration. By instantiating a few architecture-based parameters, the model can be employed in the performance analysis of data-parallel applications, guiding process generation, communication, and mapping decisions. The model is language-independent and machine-independent; it can be applied to help programmers make decisions about performance-affecting parameters as programs are ported across architectures and languages. Furthermore, the model incorporates both platform-specific and application-specific aspects, and it allows programmers to experiment with tradeoffs better than either strictly simulation-based or purely theoretical models. In addition, the model was designed to be simple. In summary, this thesis outlines a simple method for benchmarking a parallel communication library and for using the results to model the performance of applications developed with that communication library. We use compositional performance analysis - decomposing a parallel program into its modular parts and analyzing their respective performances - to gain perspective on the performance of the whole program. This model is useful for predicting parallel program execution times for different types of program archetypes (e.g., mesh and mesh-spectral), using communication libraries built with different message-passing schemes (e.g., Fortran M and Fortran with MPI) running on different architectures (e.g., IBM SP2 and a network of Pentium personal computers)