Debugging mixed‐environment programs with Blink

Programmers build large‐scale systems with multiple languages to leverage legacy code and languages best suited to their problems. For instance, the same program may use Java for ease of programming and C to interface with the operating system. These programs pose significant debugging challenges, because programmers need to understand and control code across languages, which often execute in different environments. Unfortunately, traditional multilingual debuggers require a single execution environment. This paper presents a novel composition approach to building portable mixed‐environment debuggers, in which an intermediate agent interposes on language transitions, controlling and reusing single‐environment debuggers. We implement debugger composition in Blink, a debugger for Java, C, and the Jeannie programming language. We show that Blink is (i) simple: it requires modest amounts of new code; (ii) portable: it supports multiple Java virtual machines, C compilers, operating systems, and component debuggers; and (iii) powerful: composition eases debugging, while supporting new mixed‐language expression evaluation and Java native interface bug diagnostics. To demonstrate the generality of interposition, we build prototypes and demonstrate debugger language transitions with C for five of six other languages (Caml, Common Lisp, C#, Perl 5, Python, and Ruby) without modifications to their debuggers. Using real‐world case studies, we show that diagnosing language interface errors require prior single‐environment debuggers to restart execution multiple times, whereas Blink directly diagnoses them with one execution. Copyright © 2014 John Wiley & Sons, Ltd.     

Scientific computing with Java and C++: a case study using functional magnetic resonance neuroimages

Modern systems for the analysis of image‐based biomedical data, such as functional magnetic resonance imaging (fMRI), require fast computational techniques and rapid, robust development. Object‐oriented programming languages such as Java and C++ provide the foundations for the development of complex data analysis applications. This case study explores the advantages and disadvantages of using these two programming environments for scientific computation as typified in the analysis of fMRI datasets. C++ is well suited for computational and memory optimization while Java is more compliant to the object‐oriented paradigm, supports cross‐platform development and has a rich set of application programming interface (API) classes. The same data model and algorithms were implemented in C++ and Java, and a user interface was developed with the Java API. Comparisons were made with respect to computational performance and ease of development. Benchmarks show that C++ generally outperforms Java, while Java is easier to use, leading to more robust code and shorter development times. However, with the advent of newer just‐in‐time compilers, Java performance is at times comparable to C++. The latest Java virtual machine technology is closing the gap and eventually Java should be a good compromise between efficient algorithm performance and effective application development. Copyright © 2004 John Wiley & Sons, Ltd.     

Effective strategic programming for Java developers

In object programming languages, the Visitor design pattern allows separation of algorithms and data structures. When applying this pattern to tree‐like structures, programmers are always confronted with the difficulty of making their code evolve. One reason is that the code implementing the algorithm is interwound with the code implementing the traversal inside the visitor. When implementing algorithms such as data analyses or transformations, encoding the traversal directly into the algorithm turns out to be cumbersome as this type of algorithm only focuses on a small part of the data‐structure model (e.g., program optimization). Unfortunately, typed programming languages like Java do not offer simple solutions for expressing generic traversals. Rewrite‐based languages like ELAN or Stratego have introduced the notion of strategies to express both generic traversal and rule application control in a declarative way. Starting from this approach, our goal was to make the notion of strategic programming available in a widely used language such as Java and thus to offer generic traversals in typed Java structures. In this paper, we present the strategy language SL that provides programming support for strategies in Java. Copyright © 2012 John Wiley & Sons, Ltd.     

Accurate garbage collection in uncooperative environments revisited

Implementing a concurrent programming language such as Java by means of a translator to an existing language is attractive as it provides portability over all platforms supported by the host language and reduces development time—as many low‐level tasks can be delegated to the host compiler. The C and C++ programming languages are popular choices for many language implementations due to the availability of efficient compilers on a wide range of platforms. For garbage‐collected languages, however, they are not a perfect match as no support is provided for accurately discovering pointers to heap‐allocated data on thread stacks. We evaluate several previously published techniques and propose a new mechanism, lazy pointer stacks, for performing accurate garbage collection in such uncooperative environments. We implemented the new technique in the Ovm Java virtual machine with our own Java‐to‐C/C++ compiler using GCC as a back‐end compiler. Our extensive experimental results confirm that lazy pointer stacks outperform existing approaches: we provide a speedup of 4.5% over Henderson's accurate collector with a 17% increase in code size. Accurate collection is essential in the context of real‐time systems, we thus validate our approach with the implementation of a real‐time concurrent garbage collection algorithm. Copyright © 2009 John Wiley & Sons, Ltd.     

VCluster: a thread‐based Java middleware for SMP and heterogeneous clusters with thread migration support

Clusters, composed of symmetric multiprocessor (SMP) machines and heterogeneous machines, have become increasingly popular for high‐performance computing. Message‐passing libraries, such as message‐passing interface (MPI) and parallel virtual machine (PVM), are de facto parallel programming libraries for clusters that usually consist of homogeneous and uni‐processor machines. For SMP machines, MPI is combined with multithreading libraries like POSIX Thread and OpenMP to take advantage of the architecture. In addition to existing parallel programming libraries that are in C/C++ and FORTRAN programming languages, the Java programming language presents itself as another alternative with its object‐oriented framework, platform neutral byte code, and ever‐increasing performance. This paper presents a new parallel programming model and a library, VCluster, which implements this model. VCluster is based on migrating virtual threads instead of processes to support clusters of SMP machines more efficiently. The implementation uses thread migration, which can be used in dynamic load balancing. VCluster was developed in pure Java, utilizing the portability of Java to support clusters of heterogeneous machines. Several applications are developed to illustrate the use of this library and compare the usability and performance of VCluster with other approaches. Copyright © 2007 John Wiley & Sons, Ltd.     

A type system for static and dynamic checking of C++ pointers

Object-oriented programming is the most used programming paradigm when dealing with large-scale, modular software. In this field, the two leading languages are Java and C++. The former has superior qualities in terms of safety and ease of programming, whereas the latter is often considered an “old” language, too complex and potentially unsafe.In this paper, we describe a new type system designed to analyze the security problems derived from pointer manipulation in C++. This type system tries to trap the most common errors through static analysis, i.e., at compile-time, and only when static analysis fails it generates and embeds code fragments that apply runtime checks on specific instructions. The aim of this new type system is to give C++ the same safety of Java in the most important memory-related operations, without adding much runtime overhead. An experimental implementation of the type system is also presented, embedded in a C++ analysis tool called GPCC.     

基于JavaCC的C代码自动并行化的设计与实现

针对当前大量遗产代码无法重复利用的问题,设计一种新的编译工具将C的串行代码转换为基于MPI+OpenMP的混合并行编程代码,降低了并行编程的开发成本。首先,通过对JavaCC的优化,实现一种可以解析C语言的词法和语法分析器,进行源代码分析并生成抽象语法树;其次,根据语法树对源代码进行控制依赖性和数据依赖性分析,产生可并行化的语句块分区;再次,按照提出的并行代码生成方法得到目标代码;最后,基于Visual Studio 2010构建目标代码仿真验证环境。实验结果表明,该工具可以较为理想地实现串行代码自动并行化,与手工编写的代码在加速比上的误差为8.2%~18.4%。     

在Java中访问自动化COM组件

与其他编程语言相比，Java有很多优点，尽管如此。你常常希望在你的代码中访问其他语言写的应用或者程序库．尤其是COM组件。标准Java没有对COM提供支持，但是。你可以对自动化COM组件主要是COM组件的ldispatch接口进行封装，然后通过使用Java本地接口（JNI）采访问COM组件。     

在Java中访问自动化COM组件

与其他编程语言相比,Java有很多优点,尽管如此,你常常希望在你的代码中访问其他语言写的应用或者程序库,尤其是COM组件。标准Java没有对COM提供支持,但是,你可以对自动化COM组件主要是COM组件的Idispatch接口进行封装,然后通过使用Java本地接口(JNI)来访问COM组件。     

Choosing a programming language

This paper evaluates the use of a functional language for implementing domain-specific functionality. The factors we consider when choosing a programming language are programmer productivity, maintainability, efficiency, portability, tool support, and software and hardware interfaces. The choice of programming language is a fine balancing act. Modern object-oriented languages such as Java and C# are more orthogonal and hide fewer surprises for the programmer, although the inevitable accumulation of features makes this statement less true with every new version of each language.     

C-Java自动程序转换系统的设计

程序设计语言的相互转换技术可以被广泛运用在软件维护、遗留系统的升级改造以及软件逆向工程等领域中。文中先对现有的几种移植方法进行了分析和研究,分析表明在将程序库移植到Java中和将它们与Java整合时,这些方法暴露出了各自的局限性和不足。借鉴语言转换经验,制定了转换的设计原则并探讨了将C语言转换到Java语言的过程中需要解决的一些问题,以及这个转换系统的设计思想和实现方法。文中所阐述的内容为实现异种程序设计语言的程序代码转换,提高程序代码的可移植性和重用性提供了有意义的思路和实现方法。     

A comparative study of Java and C performance in two large‐scale parallel applications

In the 1990s the Message Passing Interface Forum defined MPI bindings for Fortran, C, and C++. With the success of MPI these relatively conservative languages have continued to dominate in the parallel computing community. There are compelling arguments in favour of more modern languages like Java. These include portability, better runtime error checking, modularity, and multi‐threading. But these arguments have not converted many HPC programmers, perhaps due to the scarcity of full‐scale scientific Java codes, and the lack of evidence for performance competitive with C or Fortran. This paper tries to redress this situation by porting two scientific applications to Java. Both of these applications are parallelized using our thread‐safe Java messaging system—MPJ Express. The first application is the Gadget‐2 code, which is a massively parallel structure formation code for cosmological simulations. The second application uses the finite‐domain time‐difference method for simulations in the area of computational electromagnetics. We evaluate and compare the performance of the Java and C versions of these two scientific applications, and demonstrate that the Java codes can achieve performance comparable with legacy applications written in conventional HPC languages. Copyright © 2009 John Wiley & Sons, Ltd.     

Java与C/C++的结合

JNI是JDK提供的本地编程接口,它允许Java代码操作其他语言编写的应用程序和库,但调用本地方法的同时也带来了安全问题.CORBA是一个分布式的、面向对象的应用架构规范,它允许对象在异构的、分布式的环境中透明传输,从而也能实现Java与C/C＋ ＋的互操作.本文比较了JNI和CORBA两种方法的优缺点,并将CORBA应用在一个J2EE架构下的项目中,解决了项目中Java与C/C＋ ＋的交互问题.     

Java异常处理策略研究

异常处理机制是程序设计语言的重要标志之一,在程序设计过程中用来处理程序运行中的异常。传统的程序设计语言里异常处理较为繁杂。Java是一种面向对象的程序设计语言,且引入了异常处理机制。合理完备的异常处理可以增强程序运行的可靠性、提高软件的健壮性,可以较为快速地确定错误的位置。文章分析了Java异常处理的逻辑,阐述了异常类、异常处理机制以及异常处理方法,提出了异常处理的一些策略。综合运用这些策略可以使编程人员编写出更加简洁、高效的程序代码。     

Coping with Java threads

A thread is a basic unit of program execution that can share a single address space with other threads - that is, they can read and write the same variables and data structures. Originally, only assembly programmers used threads. A few older programming languages such as PL/I supported thread concurrency, but newer languages such as C and C++ use libraries instead. Only recently have programming languages again begun to build in direct support for threads. Java and Ada are examples of industry-strength languages for multithreading. The Java thread model has its roots in traditional concurrent programming. As the "real-time specification for Java" sidebar describes, RTSJ attempts to remove some of the limitations relative to real-time applications - primarily by circumventing garbage collection. But RTSJ does not make the language safer. It retains standard Java's threading pitfalls and is a risky candidate for critical concurrent applications.     

Adoption and use of Java generics

Support for generic programming was added to the Java language in 2004, representing perhaps the most significant change to one of the most widely used programming languages today. Researchers and language designers anticipated this addition would relieve many long-standing problems plaguing developers, but surprisingly, no one has yet measured how generics have been adopted and used in practice. In this paper, we report on the first empirical investigation into how Java generics have been integrated into open source software by automatically mining the history of 40 popular open source Java programs, traversing more than 650 million lines of code in the process. We evaluate five hypotheses and research questions about how Java developers use generics. For example, our results suggest that generics sometimes reduce the number of type casts and that generics are usually adopted by a single champion in a project, rather than all committers. We also offer insights into why some features may be adopted sooner and others features may be held back.