Programming Language Techniques Research Articles

Identification of Reptile Species Using Convolutional Neural Networks (CNN)

Reptiles are one of the most common fauna in the territory of Indonesia. quite a lot of people who have an interest in knowing more about this fauna in order to increase knowledge. Based on previous research, Deep Learning is needed in particular the CNN method for computer programs to identify reptile species through images. This reseacrh aims to determine the right model in producing high accuracy in the identification of reptile species. Thousands of images are generated through data augmentation processes for manually captured images. Using the Python programming language and Dropout technique, an accuracy of 93% was obtained by this research in identifying 14 different types of reptiles.

ПРАГМАТИЧЕСКИЙ ПОТЕНЦИАЛ ПРИЕМОВ НЕЙРОЛИНГВИСТИЧЕСКОГО ПРОГРАММИРОВАНИЯ В ПУБЛИЦИСТИЧЕСКОМ ДИСКУРСЕ

The object of the research is the specificity of neurolinguistic programming language techniques. Scientific novelty of this work lies in identifying the consistent link between the practical realisation of neurolinguistic programming techniques and their pragmatic potential with the dominant functions of the media discourse: informative, manipulative, communicative, expressive and aesthetic ones. The authors specify the classification of neurolinguistic programming language techniques, which include additionally introduced ones: expressions with a universal quantifier, explication of causal relations and affirmation.

Special Issue on Programming Languages for Big Data Editorial

Ideas from programming languages play an important role in a range of advanced applications of databases, in database system implementation, distributed programming (MapReduce), streaming computation, and high-performance (GPU/multicore) computation. This creative research area is broadening into a subfield of data-centric computation. Although the interaction of databases and programming has a long history (the 16th biennial Database Programming Languages symposium was held in 2017), there has been a recent renewal of interest and broadening of programming language techniques for dealing with data from several quarters in the last few years, including workshops at Microsoft Research (RADICAL 2010), ICFP (XLDI 2012), POPL (DDFP 2013, DCM 2014) and a Dagstuhl Seminar on Programming Languages for Big Data (December 2014). This special issue recognises and encourages the publication of mature research contributions in this area.

Programming language techniques for differential privacy

Differential privacy is rigorous framework for stating and enforcing privacy guarantees on computations over sensitive data. Informally, differential privacy ensures that the presence or absence of a single individual in a database has only a negligible statistical effect on the computation's result. Many specific algorithms have been proved differentially private, but manually checking that a given program is differentially private can be subtle, tedious, or both. This approach becomes unfeasible when larger programs are considered.

Scaling network verification using symmetry and surgery

On the surface, large data centers with about 100,000 stations and nearly a million routing rules are complex and hard to verify. However, these networks are highly regular by design; for example they employ fat tree topologies with backup routers interconnected by redundant patterns. To exploit these regularities, we introduce network transformations: given a reachability formula and a network, we transform the network into a simpler to verify network and a corresponding transformed formula, such that the original formula is valid in the network if and only if the transformed formula is valid in the transformed network. Our network transformations exploit network surgery (in which irrelevant or redundant sets of nodes, headers, ports, or rules are ``sliced'' away) and network symmetry (say between backup routers). The validity of these transformations is established using a formal theory of networks. In particular, using Van Benthem-Hennessy-Milner style bisimulation, we show that one can generally associate bisimulations to transformations connecting networks and formulas with their transforms. Our work is a development in an area of current wide interest: applying programming language techniques (in our case bisimulation and modal logic) to problems in switching networks. We provide experimental evidence that our network transformations can speed up by 65x the task of verifying the communication between all pairs of Virtual Machines in a large datacenter network with about 100,000 VMs. An all-pair reachability calculation, which formerly took 5.5 days, can be done in 2 hours, and can be easily parallelized to complete in

SPOT: A DSL for Extending Fortran Programs with Metaprogramming

Metaprogramming has shown much promise for improving the quality of software by offering programming language techniques to address issues of modularity, reusability, maintainability, and extensibility. Thus far, the power of metaprogramming has not been explored deeply in the area of high performance computing (HPC). There is a vast body of legacy code written in Fortran running throughout the HPC community. In order to facilitate software maintenance and evolution in HPC systems, we introduce a DSL that can be used to perform source-to-source translation of Fortran programs by providing a higher level of abstraction for specifying program transformations. The underlying transformations are actually carried out through a metaobject protocol (MOP) and a code generator is responsible for translating a SPOT program to the corresponding MOP code. The design focus of the framework is to automate program transformations through techniques of code generation, so that developers only need to specify desired transformations while being oblivious to the details about how the transformations are performed. The paper provides a general motivation for the approach and explains its design and implementation. In addition, this paper presents case studies that illustrate the potential of our approach to improve code modularity, maintainability, and productivity.

Functional programs as compressed data

We propose an application of programming language techniques to lossless data compression, where tree data are compressed as functional programs that generate them. This "functional programs as compressed data" approach has several advantages. First, it follows from the standard argument of Kolmogorov complexity that the size of compressed data can be optimal up to an additive constant. Secondly, a compression algorithm is clean: it is just a sequence of β-expansions (i.e., the inverse of β-reductions) for ?-terms. Thirdly, one can use program verification and transformation techniques (higher-order model checking, in particular) to apply certain operations on data without decompression. In this article, we present algorithms for data compression and manipulation based on the approach, and prove their correctness. We also report preliminary experiments on prototype data compression/transformation systems.

Non-disclosure for distributed mobile code

With the emergence of the new possibilities offered by global computing, new security issues follow from the fact that these possibilities can be equally exploited by parties with malicious intentions. Many attacks arise at the application level, and can be tackled by means of programming language techniques. For instance, confidentiality can be violated during the execution of programs that reveal secret information. This kind of program behaviour can be avoided by information flow analyses that detect the encoding of illegal flows.This paper studies information flows that occur in distributed programs with code mobility from a language-based security perspective. New forms of security leaks that are introduced by code mobility, which we callmigration leaks, are presented and compared with well-known forms of illegal flow. We propose an information flow property that is adequate for networks consisting of a generalisation of the non-disclosure policy. We design a type and effect system for enforcing it on an expressive distributed calculus, and explain a soundness proof methodology in detail.

Effcient programming techniques for the SACLIB computer algebra library

This dissertation describes three contributions to the SACLIB computer algebra library. Using generic programming we specify the Recursively Fixed Iterator and the Structure Protecting Iterator concepts. We prove that models of these concepts cannot leak or double delete resources. Through template metaprogramming, we implement models of these concepts that provide this memory safety at compile-time and without any run-time overhead. Using aspect oriented programming, we allow unit and regression tests to be automatically obtained from an executing SACLIB program. This program instrumentation is transparent both to SACLIB maintainers and clients. This mechanism allows the automated creation of regression test suites during the execution of normal SACLIB programs. Using code generation and auto-tuning, we allow high performance implementations of the Taylor shift, de Casteljau's algorithm, and the Descartes Method for polynomial root isolation to be automatically tuned for different architectures. This allows a speedup of 10-20 over existing methods to be obtained on modern CPU architectures. The key to this speedup is the creation of a tiling scheme that allows the irregular structure of the computation to be tiled using a small number of tiles that are easy for a code generator to produce code for. The implementation of the Recursively Fixed Iterator and the Structure Protecting Iterator provide memory safety by using C++ template metaprograms that selectively disable certain classes of side effects in programs using the iterators. Other safety properties can be achieved using similar disabling of side effects. We believe that the most important continuation of the work presented here is the development of programming language techniques to allow programmers to control where their code should sit along the spectrum of the absence of side effects in pure functional languages and the unrestricted side effects of imperative language.

PetaBricks

It is often impossible to obtain a one-size-fits-all solution for high performance algorithms when considering different choices for data distributions, parallelism, transformations, and blocking. The best solution to these choices is often tightly coupled to different architectures, problem sizes, data, and available system resources. In some cases, completely different algorithms may provide the best performance. Current compiler and programming language techniques are able to change some of these parameters, but today there is no simple way for the programmer to express or the compiler to choose different algorithms to handle different parts of the data. Existing solutions normally can handle only coarse-grained, library level selections or hand coded cutoffs between base cases and recursive cases. We present PetaBricks, a new implicitly parallel language and compiler where having multiple implementations of multiple algorithms to solve a problem is the natural way of programming. We make algorithmic choice a first class construct of the language. Choices are provided in a way that also allows our compiler to tune at a finer granularity. The PetaBricks compiler autotunes programs by making both fine-grained as well as algorithmic choices. Choices also include different automatic parallelization techniques, data distributions, algorithmic parameters, transformations, and blocking. Additionally, we introduce novel techniques to autotune algorithms for different convergence criteria. When choosing between various direct and iterative methods, the PetaBricks compiler is able to tune a program in such a way that delivers near-optimal efficiency for any desired level of accuracy. The compiler has the flexibility of utilizing different convergence criteria for the various components within a single algorithm, providing the user with accuracy choice alongside algorithmic choice.

The liberty structural specification language

Rapid exploration of the design space with simulation models is essential for quality hardware systems research and development. Despite striking commonalities across hardware systems, designers routinely fail to achieve high levels of reuse across models constructed in existing general-purpose and domain-specific languages. This lack of reuse adversely impacts hardware system design by slowing the rate at which ideas are evaluated. This paper presents an examination of existing languages to reveal their fundamental limitations regarding reuse in hardware modeling. With this understanding, a solution is described in the context of the design and implementation of the Liberty Structural Specification Language (LSS), the input language for a publicly available high-level digital-hardware modeling tool called the Liberty Simulation Environment. LSS is the first language to enable low-overhead reuse by simultaneously supporting static inference based on hardware structure and flexibility via parameterizable structure. Through LSS, this paper also introduces a new type inference algorithm and a new programming language technique, called use-based specialization , which, in a manner analogous to type inference, customizes reusable components by statically inferring structural properties that otherwise would have had to have been specified manually.

Non-restrictive computational reflection

Adaptable software systems and architectures give the programmer the ability to create applications that might customize themselves to runtime-emerging requirements. Computational reflection is a programming language technique that is commonly used to achieve the development of this kind of systems. Most runtime reflective systems use Meta-Object Protocols (MOPs). However, MOPs restrict the amount of features an application can customize, and the way they can express its own adaptation. Furthermore, this kind of systems uses a fixed programming language: they develop an interpreter, not a whole language-independent platform. What we present in this paper a non-restrictive reflective platform, called nitrO, that achieves a real computational-environment jump, making every application and language feature adaptable at runtime—without any previously defined restriction. Moreover, the platform has been built using a generic interpreter, in which the reflection mechanism is independent of the language selected by the programmer. Different applications may dynamically adapt each other, regardless of the programming language they use.

On parallel object oriented programming in Fortran 90

The C++ programming language [6, 10] is well-known for its support of object oriented concepts, useful in abstraction modeling. Containing many important features, its popularity is growing with a new generation of scientists anxious to bring clarity and flexibility to their programming efforts. Nevertheless, most of the scientific applications in development and use today are based on Fortran, the most popular language for scientific programming.Fortran is not a static language, it has continually evolved to include the most recent proven ideas and concepts garnered from other programming languages. Until recently, many of the most modern features were not available, complicating abstraction modeling for large scale development projects. This can make software difficult to comprehend, unsafe and potentially useless. The emergence of Fortran 90 [3] has dramatically changed the prospects of Fortran programming. Not only are many of the most modern aspects of programming language techniques included in the standard, there are also specific new additions that will undoubtedly affect the next generation of all languages used in scientific programming [8].

An integrated intelligent process planning system for prismatic parts using PC-based CAD and CAM software packages

Traditional machining process planning relies heavily on human decision making and manual calculations. The utilisation of CAM software and computers to aid machining reduces errors and planning time. A fully integrated planning system using CAD and CAM software would further increase the efficiency of process planning. The goal of this research is the automation of machining process planning for prismatic parts by integrating Autocad and Mastercam software packages using the Autolisp programming language and artificial intelligence techniques. Using only a 3D representation of the prismatic part geometry drawn in Autocad as input, the integrated system will be capable of producing NC code for the machining of the part with minimal human intervention. This system would greatly enhance the productivity of machining process planning.

Types and persistence in database programming languages

Traditionally, the interface between a programming language and a database has either been through a set of relatively low-level subroutine calls, or it has required some form of embedding of one language in another. Recently, the necessity of integrating database and programming language techniques has received some long-overdue recognition. In response, a number of attempts have been made to construct programming languages with completely integrated database management systems. These languages, which we term database programming languages , are the subject of this review. The design of these languages is still in its infancy, and the purpose of writing this review is to identify the areas in which further research is required. In particular, we focus on the problems of providing a uniform type system and mechanisms for data to persist. Of particular importance in solving these problems are issues of polymorphism, type inheritance, object identity, and the choice of structures to represent sets of similar values. Our conclusion is that there are areas of programming language research—modules, polymorphism, persistence, and inheritance—that must be developed and applied to achieve the goal of a useful and consistent database programming language. Other research areas of equal importance, such as implementation, transaction handling, and concurrency, are not examined here in any detail.