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The syntax of the programming languages has a significant impact on the definition and validation of mathematical calculations. In particular, the management of code identification and validation processes can be made easier and faster, depending on the parametric behavior of the functions. In this article, a programming language that supports the use of mathematical function structures is designed and an interpreter, which can evaluate the source code written in this language, is developed. The language syntax is represented by an LL (k) grammar defined in the BNF notation. The interpreter consists of several basic components such as parser, semantic controller and code evaluator, each of which makes a different kind of code interpretation. The LL (k) parser component used for the syntactic analysis of the language is generated via an automatic code generation tool called JavaCC. The other components work on the abstract syntactic tree that this parser generates. To illustrate the use of the language with code samples, several mathematical algorithms that include calculations on different sequences of numbers, are programmed and interpreted.

The purpose of this paper is to re-examine the relationship between grammars and processing systems in light of the various forms of experimental research (especially of an electrophysiological nature) that has been conducted in the last fifteen years or so. First, the notion of ‘processing strategy’ or ‘heuristics processing’ is considered followed by a discussion of structures of great morphosyntactic complexity that parsing systems seem to tackle by simply respecting complex grammatical laws, instead of by resorting to shortcuts. Then, grammatical illusions and what these can teach us about the processing of grammar are considered. It is argued that illusions allow us to discern a few explanatory principles that may redefine the way we see parser–grammar relations. Among these is the idea that how long illusions last in the online-to-offline transition depends in part on their ‘templatability’, that is, the ease with which they become gestaltic templates. Another key idea is that some apparent illusions are in fact nothing more than grammar contemplated at work as in slow motion.

Natural language processing problems (such as speech recognition, text-based data mining, and text or speech generation) are becoming increasingly important. Before effectively approaching many of these problems, it is necessary to process the syntactic structures of the sentences. Syntactic parsing is the task of constructing a syntactic parse tree over a sentence which describes the structure of the sentence. Parse trees are used as part of many language processing applications. In this paper, we present a multi-lingual dependency parser. Using advanced deep learning techniques, our parser architecture tackles common issues with parsing such as long-distance head attachment, while using `architecture engineering' to adapt to each target language in order to reduce the feature engineering often required for parsing tasks. We implement a parser based on this architecture to utilize transfer learning techniques to address important issues related with limited-resourced language. We exceed the accuracy of state-of-the-art parsers on languages with limited training resources by a considerable margin. We present promising results for solving core problems in natural language parsing, while also performing at state-of-the-art accuracy on general parsing tasks.

Sayısal hesaplama ya da diğer adıyla nümerik analiz, uygulamalı matematiğin önemli bir dalıdır. Matematiğinanalitik çözüm üretemediği veya üretilen çözümün uygulama açısından yüksek hesaplama karmaşıklığına sahipolduğu durumlarda sayısal yöntemler kullanılır. Bu makalede, sayısal yöntemlerin programlanabilmesinisağlayan bir programlama dilinin tasarımı yapılmış ve bu dilde yazılan kaynak kodun değerlendirmesiniyapabilen bir yorumlayıcı geliştirilmiştir. Dilin sözdizimi BNF (Backus Naur Form) notasyonunda tanımlananbir LL(k) grameri ile temsil edilmiştir. Yorumlayıcı, her biri kodun farklı türden yorumlamasını yapan ayrıştırıcı,anlamsal denetleyici, simgesel türev alıcı ve kod değerlendirici gibi birkaç temel bileşenden oluşmaktadır. Dilinsözdizim analizi için kullanılan LL(k) ayrıştırıcı bileşeni, otomatik kod üretim aracı olan JavaCC yardımıylaüretilmiştir. Diğer bileşenler bu ayrıştırıcının oluşturduğu soyut sözdizim ağacı üzerinde çalışmaktadır. Dilinkullanımına yönelik olarak, birkaç sayısal kök bulma yönteminin programlaması ve yorumlaması gösterilmiştir.Bazı popüler diller ile dil metriklerine dayalı bir karşılaştırma yapılmış ve koşum zamanları değerlendirilmiştir.

The complexity of hardware designs is still increasing according to Moore’s law. With embedded systems being more and more intertwined and working together not only with each other, but also with their environments as cyber physical systems (CPSs), more streamlined development workflows are employed to handle the increasing complexity during a system’s design phase. SystemC is a C++ library for the design of hardware/software systems, enabling the designer to quickly prototype, e.g., a distributed CPS without having to decide about particular implementation details (such as whether to implement a feature in hardware or in software) early in the design process. Thereby, this approach reduces the initial implementation’s complexity by offering an abstract layer with which to build a working prototype. However, as SystemC is based on C++, analyzing designs becomes a difficult task due to the complex language features that are available to the designer. Several fundamentally different approaches for analyzing SystemC designs have been suggested. This work illustrates several different SystemC analysis approaches, including their specific advantages and shortcomings, allowing designers to pick the right tools to assist them with a specific problem during the design of a system using SystemC.

Source code plagiarism in students solutions of programming tasks is a serious problem, especially important in distance learning. Naturally, it should be prevented, but publicly available code plagiarism detection tools are not fully adjusted to this purpose. This paper proposes the specific approach to detecting code duplicates. This approach is based on adapting of detection process to characteristics of programming tasks and comprise of freshly developed detecting tools, which could be configured and tuned to fit individual features of the programming task. Particular attention is paid to the possibility of an automatic elimination of duplicate codes from the set of all solutions. As a minimum, this requires the rejection of false-positive duplicates, even for simple, schematic tasks. The case in the use of tools is presented in this context. The discussion is illustrated by applying of proposed tools to duplicates detection in the set of actual, real-life, codes written in Java programming language.