An intermediate language to define dynamic semantics

An instruction set is given for an abstract machine which uses a pushdown stack as its principal memory. The proposed instructions serve the similar purposes of (1) defining the dynamic semantics of programming languages by describing the operations of programs on the abstract machine and (2) describing an intermediate language to be used in compiling programming languages into machine language. It is shown how the intermediate language can be used in the translation of the programming languages ADA, FORTRAN and PASCAL into IBM 360 assembly language and advantages over other intermediate languages such as three-address code and P-code.     

SEMANOL (73) a metalanguage for programming the semantics of programming languages

Summary SEMANOL is a practical programming system for writing readable formal specifications of the syntax and semantics of programming languages. SEMANOL is based on a theory of semantics which embraces algorithmic (operational) and extensional (input/output) semantics. Specifications for large contemporary languages have been constructed in the formal language, SEMANOL (73), which is a readable high-level notation. A SEMANOL (73) specification can be executed (by an existing interpreter program); when given a program from the specified language, and its input, the execution of the SEMANOL (73) specification produces the program's output. The demonstrated executability of SEMANOL (73) provides important practical advantages. This paper includes discussions of the theory of semantics underlying SEMANOL, the syntax and semantics of the SEMANOL (73) language, the use of the SEMANOL (73) language in the SEMANOL method for describing programming languages, and the contrast between the Vienna definition method (VDL) and SEMANOL.     

StreamPI: a stream-parallel programming extension for object-oriented programming languages

Because multicore CPUs have become the standard with all major hardware manufacturers, it becomes increasingly important for programming languages to provide programming abstractions that can be mapped effectively onto parallel architectures. Stream processing is a programming paradigm where computations are expressed as independent actors that communicate via FIFO data-channels. The coarse-grained parallelism exposed in stream programs facilitates such an efficient mapping of actors onto the underlying multicore hardware. We propose a stream-parallel programming abstraction that extends object-oriented languages with stream-programming facilities. StreamPI consists of a class hierarchy for actor-specification together with a language-independent runtime system that supports the execution of stream programs on multicore architectures. We show that the language-specific part of StreamPI, i.e., the class hierarchy, can be implemented as a library-level programming language extension. A library-level extension has the advantage that an existing programming language implementation need not be touched. Legacy-code can be mixed with a stream-parallel application, and the use of sequential legacy code with actors is supported. Unlike previous approaches, StreamPI allows dynamic creation and subsequent execution of stream programs. StreamPI actors are typed. Type-safety is achieved through type-checks at stream graph creation time. We have implemented StreamPI??s language-independent runtime system and language interfaces for Ada?2005 and C++ for Intel multicore architectures. We have evaluated StreamPI for up to 16 cores on a two?CPU 8-core Intel Xeon X7560 server, and we provide a performance comparison with StreamIt?(Gordon et al. in International Conference on Architectural Support for Programming Languages and Operating Systems, 2006), which is the de facto standard for stream-parallel programming. Although our approach provides greater programming flexibility than StreamIt, the performance of StreamPI compares favorably to the static compilation model of StreamIt.     

Model checking agent programming languages

In this paper we describe a verification system for multi-agent programs. This is the first comprehensive approach to the verification of programs developed using programming languages based on the BDI (belief-desire-intention) model of agency. In particular, we have developed a specific layer of abstraction, sitting between the underlying verification system and the agent programming language, that maps the semantics of agent programs into the relevant model-checking framework. Crucially, this abstraction layer is both flexible and extensible; not only can a variety of different agent programming languages be implemented and verified, but even heterogeneous multi-agent programs can be captured semantically. In addition to describing this layer, and the semantic mapping inherent within it, we describe how the underlying model-checker is driven and how agent properties are checked. We also present several examples showing how the system can be used. As this is the first system of its kind, it is relatively slow, so we also indicate further work that needs to be tackled to improve performance.     

可重构硬件操作系统技术

为了充分发挥可重构计算的高性能和可编程能力,需要将可重构资源和硬件任务纳入到操作系统管理范畴.因此面向可重构计算的操作系统技术—可重构硬件操作系统技术成为一个新的研究热点.本文在简要介绍可重构计算系统体系结构的基础上,详细介绍了国内外的研究现状.最后,结合可重构计算系统的特点,阐述了可重构硬件操作系统的关键技术.     

支持多种并行计算模型的面向对象框架研究

为了支持并行程序设计,几乎所有的程序设计语言均通过提供并行与同步通信机制来支持某一高级并行计算模型,如Ada语言的任务与会合机制以及Java语言的线程和同步方法.显然,这样的程序设计语言仅能支持一种高级并行计算模型.尽管单模型的途径对某些应用来说简单而有效,但由于现实世界中的问题往往较为繁杂而难以完全用单一模型来解决.文章采用面向对象的语言机制和框架技术来解决此问题.通过分析现有各种语言中高级并行计算模型的共性,提出了若干新的面向对象语言机制.以此为基础,提出了并行面向对象框架的概念,并讨论用其表达和使用     

Exception handling in the spreadsheet paradigm

Exception handling is widely regarded as a necessity in programming languages today and almost every programming language currently used for professional software development supports some form of it. However, spreadsheet systems, which may be the most widely used type of “programming language” today in terms of number of users using it to create “programs” (spreadsheets), have traditionally had only extremely limited support for exception handling. Spreadsheet system users range from end users to professional programmers and this wide range suggests that an approach to exception handling for spreadsheet systems needs to be compatible with the equational reasoning model of spreadsheet formulas, yet feature expressive power comparable to that found in other programming languages. We present an approach to exception handling for spreadsheet system users that is aimed at this goal. Some of the features of the approach are new; others are not new, but their effects on the programming language properties of spreadsheet systems have not been discussed before in the literature. We explore these properties, offer our solutions to problems that arise with these properties, and compare the functionality of the approach with that of exception handling approaches in other languages     

Systems implementation languages and IRONMAN

The U.S. Department of Defense has recently issued a set of requirements, which it called IRONMAN, for the design of a programming language that it will use for embedded computer applications. To date four competing languages have been designed and, after considerable debate and scrutiny, these have been reduced to two. It is expected that the winning language will be selected during 1979. This report compares the IRONMAN requirements against the state-of-the-art in systems implementation language design in an attempt to see the extent to which IRONMAN can be met from existing technology. Particular emphasis is given to the areas of large-scale program structuring, parallel programming, exception handling and hardware interaction. Finally, Dijkstra's criticism of IRONMAN and the competing languages will be examined. It will be argued that he may be justified in doubting the viability of a language with such diverse features.     

基于深度学习的跨自然语言与程序语言生成任务综述

近年来,随着人工智能技术的发展,许多编程人员期望计算机代替他们自动完成程序代码或者代码注释的编写等任务。跨自然语言与程序语言(Natural languages and programming languages, NL-PL)生成即为此类任务,指自然语言和程序语言之间的相互转换任务,包括自然语言到程序语言的生成和程序语言到自然语言的生成两类任务。最近几年,跨NL-PL生成在研究与应用方面呈现出爆发式的增长,尤其是随着深度学习(Deep learning,DL)技术的发展,越来越多研究人员开始利用DL技术来提升跨NL-PL生成任务效果。他们通过优化程序表示方式、改进神经网络模型以及设计大型预训练模型等方法,在该领域取得了众多突破性的进展。在基于DL的跨NL-PL生成技术获得迅猛发展的同时,大型互联网公司逐渐将该领域的研究成果付诸商用,因此,模型应用安全性也受到了学术界和业界的紧密关注。为了进一步系统地研究跨NL-PL生成技术,对这些已有的成果进行梳理非常必要。本文以程序生成和注释生成这两类典型跨NL-PL生成任务为切入点,对该领域具有代表性的最新文献进行归纳总结。我们从众多已有参考文献...     

MUPPET: A programming environment for message-based multiprocessors

MUPPET is a problem-solving environment for scientific computing with message-based multiprocessors. It consists of four part—concurrent languages, programming environments, application environments and man-machine interfaces. The programming paradigm of MUPPET is based on parallel abstract machines and transformations between them. This paradigm allows the development of programs which are portable among multiprocessors with different interconnection topologies.

In this paper we discuss the MUPPET programming paradigm. We give an introduction to the language CONCURRENT MODULA-2 and the graphic specification system GONZO. The graphic specification system tries to introduce graphics as a tool for programming. It is also the basis for programming generation and transformation.     

A proposal to merge Multiple Tuple Spaces,Object Orientation,and Logic Programming

We define a new language that naturally satisfies the requirements of concurrency support, modularity, and declarativity. Although some classes of existing languages already cover a subset of these requirements, there is no example of a programming language entirely fulfilling them. We propose to merge three programming paradigms, Multiple Tuple Spaces, Object Orientation, and Logic Programming, as a solution to our requirement list. Each paradigm is well characterized and satisfies one of the given requirements. Moreover, we claim that the merging will reveal new directions in the inception and development of future programming languages.     

Using B SP and Python to simplify parallel programming

Scientific computing is usually associated with compiled languages for maximum efficiency. However, in a typical application program, only a small part of the code is time-critical and requires the efficiency of a compiled language. It is often advantageous to use interpreted high-level languages for the remaining tasks, adopting a mixed-language approach. This will be demonstrated for Python, an interpreted object-oriented high-level language that is well suited for scientific computing. Particular attention is paid to high-level parallel programming using Python and the BSP model. We explain the basics of BSP and how it differs from other parallel programming tools like MPI. Thereafter we present an application of Python and BSP for solving a partial differential equation from computational science, utilizing high-level design of libraries and mixed-language (Python–C or Python–Fortran) programming.