Execution environment for intelligent real-time control systems

Modern telerobot control technology requires the integration of symbolic and non-symbolic programming techniques, different models of parallel computations, and various programming paradigms. The Multigraph Architecture, which has been developed for the implementation of intelligent real-time control systems is described. The layered architecture includes specific computational models, integrated execution environment and various high-level tools. A special feature of the architecture is the tight coupling between the symbolic and non-symbolic computations. It supports not only a data interface, but also the integration of the control structures in a parallel computing environment

Future of Functional Reactive Programming in Real-Time Systems

The evolution of programming paradigms and the development of new programming languages are driven by the needs of problem domains. Functional reactive programming (FRP) combines functional programming (FP) and reactive programming (RP) concepts that leverage asynchronous dataflow from reactive programming and higher-level abstractions building blocks from functional programming to enable developers to define data flows and transformations declaratively. Declarative programming allows developers to concentrate more on the problem to be solved rather than the implementation details, resulting in efficient and concise code. Over the years, various FRP designs have been proposed in real-time application areas. Still, it remains unclear how FRP-based solutions compare with traditional methods for implementing these applications. In this survey, we studied the usefulness of FRP in some real-time applications, such as game development, animation, graphical user interface(GUI), and embedded system. We conducted a qualitative comparison for game development and studied various applications in animation, GUI, and embedded systems. We found that using FRP in these applications is quite difficult because of insufficient libraries and tools. Additionally, due to high learning curves and a need for experienced developers, the development process in FRP takes time and effort. Our examination of two well-known games: Asteroid and Pong, in three programming paradigms: imperative programming using the Unity game engine, FP in Haskell, and FRP in the Yampa library, showed that imperative programming is effective in terms of performance and usability. The other two paradigms for developing games from scratch are inefficient and challenging. Despite the fact that FRP was designed for animation, the majority of its applications are underperforming. FRP is more successful for GUI applications, where libraries like RxJS have been used in many web interfaces. FRP is also applied in developing embedded system applications for its effective memory management, maintainability, and predictability. Developing efficient solutions from scratch is not suitable in FRP due to several factors, such as poor performance compared to other programming paradigms, programming complexity, and a steep learning curve. Instead, developers can be benefited from utilizing FRP-supported modular platforms to build robust and scalable real-time applications

ChimpCheck: Property-Based Randomized Test Generation for Interactive Apps

We consider the problem of generating relevant execution traces to test rich interactive applications. Rich interactive applications, such as apps on mobile platforms, are complex stateful and often distributed systems where sufficiently exercising the app with user-interaction (UI) event sequences to expose defects is both hard and time-consuming. In particular, there is a fundamental tension between brute-force random UI exercising tools, which are fully-automated but offer low relevance, and UI test scripts, which are manual but offer high relevance. In this paper, we consider a middle way---enabling a seamless fusion of scripted and randomized UI testing. This fusion is prototyped in a testing tool called ChimpCheck for programming, generating, and executing property-based randomized test cases for Android apps. Our approach realizes this fusion by offering a high-level, embedded domain-specific language for defining custom generators of simulated user-interaction event sequences. What follows is a combinator library built on industrial strength frameworks for property-based testing (ScalaCheck) and Android testing (Android JUnit and Espresso) to implement property-based randomized testing for Android development. Driven by real, reported issues in open source Android apps, we show, through case studies, how ChimpCheck enables expressing effective testing patterns in a compact manner.Comment: 20 pages, 21 figures, Symposium on New ideas, New Paradigms, and Reflections on Programming and Software (Onward!2017

OpenVX-Based Python Framework for Real-time Cross-Platform Acceleration of Embedded Computer Vision Applications

Embedded real-time vision applications are being rapidly deployed in a large realm of consumer electronics, ranging from automotive safety to surveillance systems. However, the relatively limited computational power of embedded platforms is considered as a bottleneck for many vision applications, necessitating optimization. OpenVX is a standardized interface, released in late 2014, in an attempt to provide both system and kernel level optimization to vision applications. With OpenVX, Vision processing are modeled with coarse-grained data flow graphs, which can be optimized and accelerated by the platform implementer. Current full implementations of OpenVX are given in the programming language C, which does not support advanced programming paradigms such as object-oriented, imperative and functional programming, nor does it have runtime or type-checking. Here we present a python-based full Implementation of OpenVX, which eliminates much of the discrepancies between the object-oriented paradigm used by many modern applications and the native C implementations. Our open-source implementation can be used for rapid development of OpenVX applications in embedded platforms. Demonstration includes static and real-time image acquisition and processing using a Raspberry Pi and a GoPro camera. Code is given as supplementary information. Code project and linked deployable virtual machine are located on GitHub: https://github.com/NBEL-lab/PythonOpenVX

Preface Volume 30, Issue 3

AbstractOne of the main areas of research in logic programming is the design and implementation of sequential and parallel (constraint) logic programming systems. This research goes broadly from the design and specification of novel implementation technology to its actual evaluation in real life situations. A series of workshops on Implementations of Logic Programming Systems, previously held in Budapest (1993), Ithaca (1994), Portland (1995), Bonn (1996), Port Jefferson (1997), Manchester (1998) and Las Cruces (1999) provided a forum for ongoing research on the design and implementation of sequential and parallel (constraint) logic programming systems.This volume contains a collection of papers presented at the Workshop on Parallelism and Implementation Technology for (Constraint) Logic Programming, held in Las Cruces on December 1st, 1999, in conjunction with ICLP'99. The workshop was sponsored and organised by COMPULOG AMERICAS. The workshop also received support from the Association for Logic Programming and from the Department of Computer Science, New Mexico State University.Papers from both academia and industry were invited. Preference was given to the analysis and description of implemented systems (or currently under implementation) and their associated techniques, problems found in their development or design, and steps taken towards the solution of these problems.Topics included, but were not limited to: •standard and non—standard sequential implementation schemes (e.g., generalization/modification of WAM, translation to C, etc.);implementation of parallel logic programming systems;balance between compile-time effort and run-time machinery;techniques for the implementation of different declarative programming paradigms based on, or extending, logic programming (e.g., constraint logic programming, concurrent constraint languages, equational-logic languages);performance evaluation of sequential and parallel logic programming systems, both through benchmarking and using real world applications;other implementation-related issues, such as memory management, register allocation, use of global optimisations, etc.We were very fortunate to have so many interesting research papers, ranging over widely different subjects and giving a broad coverage of current research in sequential and parallel implementation of logic programming systems. Papers on sequential logic programming systems, focus on varied topics: constraint evaluation, support for extensions to logic programming, and abstract machines for performance evaluation. Papers on parallel logic programming systems also focus on diverse topics ranging from distributed implementations, garbage collection, to optimisations for exploiting and-or parallelism.The editors would like to thank all authors that chose to submit their work to this book, and also for their cooperation in making this document possible. We would also like to thank all referees involved in assessing the papers in this special volume.This volume will be published as volume 30, Issue 3 in the series Electronic Notes in Theoretical Computer Science (ENTCS). This series is published electronically through the facilities of Elsevier Science B.V. and its auspices. The volumes in the ENTCS series can be accessed at the URL http://www.elsevier.nl/locate/entcs March 14, 2000Horst Reiche

Reusability in software engineering

This paper surveys recent work concerning reusability in software engineering. The current directions in software reusability are discussed, and the two major approaches of reusable building blocks and reusable patterns studied. An extensive bibliography, parts of which are annotated, is included

Logic programming in the context of multiparadigm programming: the Oz experience

Oz is a multiparadigm language that supports logic programming as one of its major paradigms. A multiparadigm language is designed to support different programming paradigms (logic, functional, constraint, object-oriented, sequential, concurrent, etc.) with equal ease. This article has two goals: to give a tutorial of logic programming in Oz and to show how logic programming fits naturally into the wider context of multiparadigm programming. Our experience shows that there are two classes of problems, which we call algorithmic and search problems, for which logic programming can help formulate practical solutions. Algorithmic problems have known efficient algorithms. Search problems do not have known efficient algorithms but can be solved with search. The Oz support for logic programming targets these two problem classes specifically, using the concepts needed for each. This is in contrast to the Prolog approach, which targets both classes with one set of concepts, which results in less than optimal support for each class. To explain the essential difference between algorithmic and search programs, we define the Oz execution model. This model subsumes both concurrent logic programming (committed-choice-style) and search-based logic programming (Prolog-style). Instead of Horn clause syntax, Oz has a simple, fully compositional, higher-order syntax that accommodates the abilities of the language. We conclude with lessons learned from this work, a brief history of Oz, and many entry points into the Oz literature.Comment: 48 pages, to appear in the journal "Theory and Practice of Logic Programming