Popular Programming Languages Research Articles

TEACHING ALGORITHMIZATION AND PROGRAMMING USING PYTHON LANGUAGE

The article describes requirements to educational programming languages and considers the use of Python as the first programming language. The issues of introduction of this programming language into teaching and replacing Pascal by Python are examined. The advantages of such approach are regarded. The comparison of popular programming languages is represented from the point of view of their convenience of use for teaching algorithmization and programming. Python supports lots of programming paradigms: structural, object-oriented,functional, imperative and aspect-oriented, and learning can be started without any preparation.There is one more advantage of the language: all algorithms are written easily and structurally in Python. Therefore, due to all mentioned above, it is possible to affirm that Python pretends to become a decent replacement for educational programming language PASCAL both at schools and on the first courses of higher education establishments.

Using Nion Swift for Data Collection, Analysis and Display

Nion Swift is an open-source software platform for the collection, processing, quantification, visualization, and management of scientific data. Built on the popular Python programming language [1], Swift is written from the ground up to be extensible at every level. Although initially developed as software for controlling Nion electron microscopes and collecting and processing data from them, Swift has been designed to serve as a resource for the scientific community across a range of applications. It includes: • Open source code based on Python • Instrument control and data collection • Data visualization, processing, and analysis • Data management, storage, and retrieval based on metadata • Multi-platform support: Windows and Mac OS presently, Linux in the future

VIBes: A Visualizer for Intervals and Boxes

VIBes is an Open Source scientific visualization system that aims at providing people working with interval methods an easy way to display results (boxes, pavings), without worrying about graphical user interface programming. It provides drawing functions accessible from multiple programming languages, without complex installation and library dependencies. VIBes is made of a visualization program and an application programming interface for popular programming languages (currently C++ and MATLAB, more are planned). It is designed for instant setup in any project and has a very short learning curve, which makes it a good visualization tool for teaching labs and tutorials. The communication between programs and VIBes goes through named-pipe or files and consists in human-readable messages. Very simple drawing functions are provided, and the VIBes viewer features navigating inside drawings and exporting images. This paper presents the main concepts driving the design of VIBes, and its software architecture. Two short programs displaying the results of a set-inversion problem and the display of projected 3-D data are provided, and future development directions are detailed.

Intellectual Property Right Protection of Browser based Software through Watermarking Technique

With the explosive growth of internet technology, many innovative web applications have been launched. For designing web applications Java has become a very popular programming language. Java bytecode technique makes it with high portability. However, it also poses large dangers to malicious users. Many techniques have been proposed for software copyright protection. They are useful for stand-alone Java applications. Due to special characteristics of Java web applications, copyright protection faces new challenge. In this paper, a copyright protection scheme for browser based Java applications have been introduced. The core of this scheme is a software watermarking algorithm. Code tamper-proofing and code obfuscation are also applied to watermarked Java code for better protection. The experimental results demonstrate the feasibility of the scheme.

The top 10 programming languages spectrum's 2014 ranking [dataflow

Working with computational journalist Nick Diakopoulos, IEEE Spectrum has weighted and combined 12 metrics from 10 sources (including IEEE Xplore, Google, and GitHub) to rank the most popular programming languages. If you don?t agree with our weighting, want to see more languages, or are interested in what?s dominant in a specific subsector, such as mobile, go to our online interactive version. There you can adjust the weight of each metric and create your own custom ranking.

Natural language processing pipelines to annotate BioC collections with an application to the NCBI disease corpus

BioC is a new format and associated code libraries for sharing text and annotations. We have implemented BioC natural language preprocessing pipelines in two popular programming languages: C++ and Java. The current implementations interface with the well-known MedPost and Stanford natural language processing tool sets. The pipeline functionality includes sentence segmentation, tokenization, part-of-speech tagging, lemmatization and sentence parsing. These pipelines can be easily integrated along with other BioC programs into any BioC compliant text mining systems. As an application, we converted the NCBI disease corpus to BioC format, and the pipelines have successfully run on this corpus to demonstrate their functionality. Code and data can be downloaded from http://bioc.sourceforge.net.Database URL: http://bioc.sourceforge.net

An Overview on R Packages for Seasonal Analysis of Time Series

Time series analysis consists of approaches for analysing time series data so thatimportant information and other features can be isolated from the data. Time series forecasting is the use of a model to predict perspective values on the basis of previouly observed values by a model. Statisticians generally use R project or R language, a free and popular programming language and computer software environment for statistical computing and graphics, for developing statistical computer software and data analysis. Plenty of time series display cyclic variation significant as seasonality, periodic variation, or periodic fluctuations in statistics. This study introducesabundant functions in the R packages TSA, marls, depersonalize and season for analyzing seasonal processes of time series, are introduced in this study. Note that R packages marls, depersonalize and season are included in the comprehensive R archive network task view TimeSeries.

An Overview on R Packages for Structural Equation Modeling

The aim of this study is to present overview on R packages for structural equation modeling. Structural equation modeling, a statistical technique for testing and estimating causal relations using an amalgamation of statistical data and qualitative causal hypotheses, allow both confirmatory and exploratory modeling, meaning they are matched to both hypothesis testing and theory development. R project or R language, a free and popular programming language and computer software surroundings for statistical computing and graphics, is popularly used among statisticians for developing statistical computer software and data analysis. The major finding is that it is necessary to build excellent and enough structural equation modeling packages for R users to do research. Numerous packages for structural equation modeling of R project are introduced in this study and most of them are enclosed in the Comprehensive R Archive Network task view Psychometrics.

The characteristic direction: a geometrical approach to identify differentially expressed genes

BackgroundIdentifying differentially expressed genes (DEG) is a fundamental step in studies that perform genome wide expression profiling. Typically, DEG are identified by univariate approaches such as Significance Analysis of Microarrays (SAM) or Linear Models for Microarray Data (LIMMA) for processing cDNA microarrays, and differential gene expression analysis based on the negative binomial distribution (DESeq) or Empirical analysis of Digital Gene Expression data in R (edgeR) for RNA-seq profiling.ResultsHere we present a new geometrical multivariate approach to identify DEG called the Characteristic Direction. We demonstrate that the Characteristic Direction method is significantly more sensitive than existing methods for identifying DEG in the context of transcription factor (TF) and drug perturbation responses over a large number of microarray experiments. We also benchmarked the Characteristic Direction method using synthetic data, as well as RNA-Seq data. A large collection of microarray expression data from TF perturbations (73 experiments) and drug perturbations (130 experiments) extracted from the Gene Expression Omnibus (GEO), as well as an RNA-Seq study that profiled genome-wide gene expression and STAT3 DNA binding in two subtypes of diffuse large B-cell Lymphoma, were used for benchmarking the method using real data. ChIP-Seq data identifying DNA binding sites of the perturbed TFs, as well as known drug targets of the perturbing drugs, were used as prior knowledge silver-standard for validation. In all cases the Characteristic Direction DEG calling method outperformed other methods. We find that when drugs are applied to cells in various contexts, the proteins that interact with the drug-targets are differentially expressed and more of the corresponding genes are discovered by the Characteristic Direction method. In addition, we show that the Characteristic Direction conceptualization can be used to perform improved gene set enrichment analyses when compared with the gene-set enrichment analysis (GSEA) and the hypergeometric test.ConclusionsThe application of the Characteristic Direction method may shed new light on relevant biological mechanisms that would have remained undiscovered by the current state-of-the-art DEG methods. The method is freely accessible via various open source code implementations using four popular programming languages: R, Python, MATLAB and Mathematica, all available at: http://www.maayanlab.net/CD.

Research on Java Development Kit Based on Complex Networks

Java is a computer programming language that is class-based, object-oriented, java is, as of 2013, one of the most popular programming languages in use. The Java Development Kit (JDK) is an implementation of java language, which consists of a Java Virtual Machine and all of the java class libraries. There are thousands of classes in the java class libraries, and there are many kinds of relationships between classes. In this paper, we use complex network theory to study the topology of the java class libraries, according to analyzing to the networks feature characters, important classes and interfaces in java class libraries are found, we hope to find the relationship between the characters of complex networks and software reliability.

Development of a digital receiver for range imaging atmospheric radar

In this paper, we describe a new digital receiver developed for a 1.3-GHz range imaging atmospheric radar. The digital receiver comprises a general-purpose software-defined radio receiver referred to as the Universal Software Radio Peripheral 2 (USRP2) and a commercial personal computer (PC). The receiver is designed to collect received signals at an intermediate frequency (IF) of 130MHz with a sample rate of 10MSs−1. The USRP2 digitizes IF received signals, produces IQ time series, and then transfers the IQ time series to the PC through Gigabit Ethernet. The PC receives the IQ time series, performs range sampling, carries out filtering in the range direction, decodes the phase-modulated received signals, integrates the received signals in time, and finally saves the processed data to the hard disk drive (HDD). Because only sequential data transfer from the USRP2 to the PC is available, the range sampling is triggered by transmitted pulses leaked to the receiver. For range imaging, the digital receiver performs real-time signal processing for each of the time series collected at different frequencies. Further, the receiver is able to decode phase-modulated oversampled signals. Because the program code for real-time signal processing is written in a popular programming language (C++) and widely used libraries, the signal processing is easy to implement, reconfigure, and reuse. From radar experiments using a 1-μs subpulse width and 1-MHz frequency span (i.e., 2-MHz frequency bandwidth), we demonstrate that range imaging in combination with oversampling, which was implemented for the first time by the digital receiver, is able to resolve the fine-scale structure of turbulence with a vertical scale as small as 100m or finer.

Defining a test coverage criterion for model-level testing of FBD programs

ContextThe Programmable Logic Controller (PLC) is being integrated into the automation and control of computer systems in safety–critical domains at an increasing rate. Thoroughly testing such software to ensure safety is crucial. Function Block Diagram (FBD) is a popular data-flow programming language for PLC. Current practice often involves translating an FBD program into an equivalent C program for testing. Little research has been conducted on coverage of direct testing a data-flow program, such as an FBD program, at the model level. There are no commonly accepted structural test coverage criteria for data-flow programs. The objective of this study is to develop effective structural test coverage criterion for testing model-level FBD programs. The proposed testing scheme can be used to detect mutation errors at the logical function level. ObjectiveThe purpose of this study is to design a new test coverage criterion that can directly test FBD programs and effectively detect logical function mutation errors. MethodA complete test set for each function and function block in an FBD program are defined. Moreover, this method augments the data-flow path concept with a sensitivity check to avoid fault masking and effectively detect logical function mutation errors. ResultsPreliminary experiments show that this test coverage criterion is comprehensive and effective for error detection. ConclusionThe proposed coverage criterion is general and can be applied to real cases to improve the quality of data-flow program design.

A New Approach for Code Generation from UML State Machine

The emergence of Unified Modeling Language (UML) as a standard for modeling systems has encouraged the use of automated software tools that facilitate the development process from analysis through coding. The UML state machine diagram is used for modeling the dynamic aspects of systems and includes many concepts that are not present in most popular programming languages, like Java or C++. There exists a gap between high level modeling language and a programming language. This paper proposes an approach to narrow the gap between multiple UML models and an implemented system. The narrowing of gap is achieved by generating compact and efficient Java code directly from UML state machine having sequential and concurrent substates. The code generation is achieved by creating a mapping between UML behavior and the Java programming language. Our model can work as a basis for automatic code generation for object-oriented systems.

Analyzing the Characteristic of JAVA Objects

Java is a very popular Object-oriented programming (OOP) language because of its platform independent and automatic memory release mechanism (or garbage collection). However, garbage collection also speeds CPU time and should be done after careful consideration. In the paper, memory usage behavior and run-time object characteristics, including heap and object size, object age and access frequency, are studied using several commercial benchmarks. The profiler design method and experiment detail are represented in the paper. The runtime object characteristics are very important to guide the employment of different memory management algorithm.

On the use of R programming language in the analyses of spatial data

R is a powerful and increasingly popular programming language with strong graphical and presentation features and large expanŽdability. Although primarily intended for statistical computing, R has paved its way to the field of GIS through the development of specialized extension packages. It offers a wide range of functions at all GIS levels: data acquisition, data manipulation, graphical reŽpresentation and quantitative analysis. The paper presents R as an open source alternative to the existing commercial GIS software. It proves especially well when advanced quantitative methods on spatial data are needed (e.g. spatial modelling). We demonstrate R capabilities through spatial analysis of forest area in Snežnik (South Slovenia), where the possibilities of data import, conversion and export into various GIS formats and possibilities of geostatistics, spatial modelling and spatial visualization are demonstrated.

Node Summit: The Evolution of Javascript

Hear about the evolution of Javascript from a panel of experts who have taken it from an idea to where it stands today, and learn what is on the horizon for the little scripting language that became one of the most popular programming languages in the world.

프로그래밍 언어들 간의 인지적인 거리측정에 관한 연구

컴퓨터관련 교육기관들은 시대의 변천에 따라 다양한 프로그래밍 언어들을 교육시켜 왔으나 많은 학생들은 컴퓨터 활용의 측면에서는 능숙하지만 프로그래밍은 배우기 어려운 분야로 인식되고 있다. 프로그래밍에 대한 거부감은 컴퓨터관련 전공에 대한 기피현상으로 이어졌고, 전 세계적으로 프로그래머 인력의 부족 문제가 대두되고 있는 설정이다. 본 연구는 프로그래밍 언어들에 대해서 프로그래머들이 지각하고 있는 언어들 간의 유사성올 조사함으로써 각 언어의 상대적인 위치를 파악하고, 좌표평면 상에 나타내어 각 차원이 의미하는 바를 추정하고 규명하였다. Although the educational institutions of computers have evolved to train students in pace with the changes of computing, many students still believe that computer programming is hard to be mastered. The reluctance of students toward programming languages have been tied to the decrease of computer-related majors and now many countries are in short of computer programmers. By investigating the similarities among eleven popular programming languages, this research is intended to measure the relative distances and understand the dimensions that scattered the languages.

PyElph - a software tool for gel images analysis and phylogenetics

BackgroundThis paper presents PyElph, a software tool which automatically extracts data from gel images, computes the molecular weights of the analyzed molecules or fragments, compares DNA patterns which result from experiments with molecular genetic markers and, also, generates phylogenetic trees computed by five clustering methods, using the information extracted from the analyzed gel image. The software can be successfully used for population genetics, phylogenetics, taxonomic studies and other applications which require gel image analysis. Researchers and students working in molecular biology and genetics would benefit greatly from the proposed software because it is free, open source, easy to use, has a friendly Graphical User Interface and does not depend on specific image acquisition devices like other commercial programs with similar functionalities do.ResultsPyElph software tool is entirely implemented in Python which is a very popular programming language among the bioinformatics community. It provides a very friendly Graphical User Interface which was designed in six steps that gradually lead to the results. The user is guided through the following steps: image loading and preparation, lane detection, band detection, molecular weights computation based on a molecular weight marker, band matching and finally, the computation and visualization of phylogenetic trees. A strong point of the software is the visualization component for the processed data. The Graphical User Interface provides operations for image manipulation and highlights lanes, bands and band matching in the analyzed gel image. All the data and images generated in each step can be saved. The software has been tested on several DNA patterns obtained from experiments with different genetic markers. Examples of genetic markers which can be analyzed using PyElph are RFLP (Restriction Fragment Length Polymorphism), AFLP (Amplified Fragment Length Polymorphism), RAPD (Random Amplification of Polymorphic DNA) and STR (Short Tandem Repeat). The similarity between the DNA sequences is computed and used to generate phylogenetic trees which are very useful for population genetics studies and taxonomic classification.ConclusionsPyElph decreases the effort and time spent processing data from gel images by providing an automatic step-by-step gel image analysis system with a friendly Graphical User Interface. The proposed free software tool is suitable for researchers and students which do not have access to expensive commercial software and image acquisition devices.

The Impedance Mismatch in Light of the Unified State Model

In this paper we discuss the misunderstanding that have arisen over the years around the broadly defined term of the object-relational impedance mismatch. It occurs in various aspects of database application programming. There are three concerns judged the most important: mismatching data models, mismatching binding times and mismatching object lifecycle. This paper focuses on the data model mismatch. We introduce the common state theory, i.e. a unified model of objects in popular programming languages and databases. The proposed model exploits and emphasizes common properties of all these objects. Using our model we demonstrate that there are notably more similarities than differences. We conclude that the impact of the mismatch of data models can be significantly reduced.

Pattern matching for the masses using custom notations

For many programmers, the notion of “pattern matching” evokes nothing more than regular expressions for matching unstructured text, or technologies such as XPath to match semi-structured data in XML. This common perception of pattern matching is partly due to the success of regular expressions and XPath, which are supported in many popular programming languages today, either as standard libraries or as part of the language. But it is also due to the fact that many programmers never used another elegant form of pattern matching—on structured data, i.e., the native data structures of a programming language. This form of matching is common in functional or logic languages used in the research, but unfortunately much less used in the software industry. It is indeed very surprising that none of the popular languages in use today support, in their standard form, a nearly general form of structured data matching, decades after this technology has been discovered and continuously improved.This paper shows that programmers do not have to wait for next generation languages to integrate pattern matching, neither need they use non-standard pre-processors, thereby losing some advantages that are most important in an industrial setting: official support, compatibility, standardization, etc. Instead, pattern matching of native data in custom notations can be implemented as a minimalist library in popular object languages. Thus, some of the comfortable existing notations from logic languages can be reused, existing standard notations for structured data such as JSON (JavaScript Object Notation) can be smoothly extended to support pattern matching, and new notations can be designed.As in most library implementations of regular expressions, custom notation patterns are simply represented as strings. They can be used in two different modes: interpreted and compiled. This paper presents two open-source implementations of custom matching notations, for Java and JavaScript, exhibiting a reasonable overhead compared to other forms of pattern matching.