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About 2,896 papers for “programming language comparison”

Programming and natural language comparison

A.U. Aleksandrov, Алексеев, I.I. Zyenok · Institutional Repository National Mining University of Ukraine (National Mining University of Ukraine) · 2017

Cited by 0Open access

Comparison Of Python (An Open Source Programming Language) With Other Programming Languages

Kumar*1, Sushil · Zenodo (CERN European Organization for Nuclear Research) · 2018

Language is a communication tool through which we can communicate with each other like Hindi, English etc any other language. So if we want to communicate with computer, we need computer programming languages. So in computer we have two types of languages, one is low level language which is easily understood by computer but difficult to learn. Second is high level language which is same like English language, not understood by computer but easy to learn. Python is a high level language. This language was developed by Guido van Rossum. He was a from the Netherlands. Python is a interpreted, high level language and it becomes very popular because of simple and easy syntax which increases the readability of the program. Python is a portable language i.e. we can python in any operating system. The scoreboard system for the Melbourne city of Australian Cricket Ground is written in Python.

Cited by 0Open access

Comparison of an Object-Oriented Programming Language to a Procedural Programming Language for Effectiveness in Program Maintenance

Sallie M. Henry, Matthew C. Humphrey · VTechWorks (Virginia Tech) · 1988

New software tools and methodologies make claims that managers often believe intuitively, without evidence. Many unsupported claims have been made about object-oriented programming. However, without scientific evidence, it is impossible to accept these claims as valid. Although experimentation has been done in the past, most of the research is very recent and the most relevant research has serious drawbacks. This paper describes an experiment which compares the maintainability of two functionally equivalent systems in order to explore the claim that systems developed with object-oriented languages are more easily maintained than those programmed with procedural languages. We found supporting evidence that programmers produce more maintainable code with an object oriented language than a standard procedural language.

Cited by 9Open access

Comparison of an object-oriented programming language to a procedural programming language for effectiveness in program maintenance

Humphrey, Matthew Cameron · VTechWorks (Virginia Tech) · 1988

New software tools and methodologies make claims that managers often believe intuitively without evidence. Many unsupported claims have been made about object-oriented programming. However, without rigorous scientific evidence, it is impossible to accept these claims as valid. Although experimentation has been done in the past, most of the research is very recent and the most relevant research has serious drawbacks. This study attempts to empirically verify the claim that object-oriented languages produce programs that are more easily maintained than those programmed with procedural languages. Measurements of subjects performing maintenance tasks onto two identical programs, one object-oriented and the other procedure-oriented show the object-oriented version to be more maintainable.

Cited by 0Open access

Java Programming Language: Time Permanence Comparison with Other Languages: A Review

Rebin Abdulkareem Hamaamin, Omar Mohammed Amin Ali, Shahab Wahhab Kareem · Springer Link (Chiba Institute of Technology) · 2024

Programming languages are necessary tools for teaching computer programming languages, so it is no surprise that deciding which one is the “right tool for the job” can be a contentious issue. To build solid foundations for such debates, we must first consider how different languages’ features relate to one another. Many Java programmers do not think about how to make their programs run faster. Application developers should tune their applications before putting them into production. Application code tuning often results in significant performance gains. The proposed model intended to assist Java programmers in fine-tuning and improving Java -based applications. This article review work in time, the time required to execute some algorithm, i.e., speed of operation, flexibility in modifying some code, and performance, are all factors in the comparison operation. To evaluate the program is better; the same code used to compare the two. in this review, researcher work in terms of the time compare in Java with other language, before compare other language, show performance Java in time and runtime Java, after select some language to compare with Java, like C language, C++ language, C# language and Python, to compare Java performance with other language and illustrate best execution time performance. Comparing Java with other languages reveals that the latest JDK runs faster and executes tasks more swiftly than older versions of Java JDK.

Cited by 0

A Semantics Comparison Workbench for a Concurrent, Asynchronous, Distributed Programming Language

Corrodi, Claudio, Heußner, Alexander, Poskitt, Christopher M. · arXiv (Cornell University) · 2017

A number of high-level languages and libraries have been proposed that offer novel and simple to use abstractions for concurrent, asynchronous, and distributed programming. The execution models that realise them, however, often change over time---whether to improve performance, or to extend them to new language features---potentially affecting behavioural and safety properties of existing programs. This is exemplified by SCOOP, a message-passing approach to concurrent object-oriented programming that has seen multiple changes proposed and implemented, with demonstrable consequences for an idiomatic usage of its core abstraction. We propose a semantics comparison workbench for SCOOP with fully and semi-automatic tools for analysing and comparing the state spaces of programs with respect to different execution models or semantics. We demonstrate its use in checking the consistency of properties across semantics by applying it to a set of representative programs, and highlighting a deadlock-related discrepancy between the principal execution models of SCOOP. Furthermore, we demonstrate the extensibility of the workbench by generalising the formalisation of an execution model to support recently proposed extensions for distributed programming. Our workbench is based on a modular and parameterisable graph transformation semantics implemented in the GROOVE tool. We discuss how graph transformations are leveraged to atomically model intricate language abstractions, how the visual yet algebraic nature of the model can be used to ascertain soundness, and highlight how the approach could be applied to similar languages.

Cited by 0Open access

Java Programming Language: Time Permanence Comparison with Other Languages: A Review

Rebin Abdulkareem Hamaamin, Omar Mohammed Amin Ali, Shahab Wahhab Kareem · ITM Web of Conferences · 2024

Programming languages are necessary tools for teaching computer programming languages, so it is no surprise that deciding which one is the “right tool for the job” can be a contentious issue. To build solid foundations for such debates, we must first consider how different languages’ features relate to one another. Many Java programmers do not think about how to make their programs run faster. Application developers should tune their applications before putting them into production. Application code tuning often results in significant performance gains. The proposed model intended to assist Java programmers in fine-tuning and improving Java -based applications. This article review work in time, the time required to execute some algorithm, i.e., speed of operation, flexibility in modifying some code, and performance, are all factors in the comparison operation. To evaluate the program is better; the same code used to compare the two. in this review, researcher work in terms of the time compare in Java with other language, before compare other language, show performance Java in time and runtime Java, after select some language to compare with Java, like C language, C++ language, C# language and Python, to compare Java performance with other language and illustrate best execution time performance. Comparing Java with other languages reveals that the latest JDK runs faster and executes tasks more swiftly than older versions of Java JDK.

Cited by 2Open access

Comparison of PHP Programming Language with Codeigniter Framework in Project CRUD

Muqorobin Muqorobin, Nendy Akbar Rozaq Rais · International Journal of Computer and Information System (IJCIS) · 2022

Programming Language is a certain code that is designed to create an application program design. The number of programming languages currently circulating, it is necessary to test the level of reliability of a programming language. The purpose of this research is to compare the programming language PHP and Codeigniter Framework, both of these programming languages are back end languages so that they have close specifications in processing data from the database. Implementation developed with CRUD-based Codelgniter Framework. CodeIgniter is an open source web application network that is used to build dynamic PHP applications on the Project CRUD (Create Read Update Delete) model. In general, the two programming languages aim to manage the database so that it can be displayed and managed by the application. The research method used is literature study and practicum in lectures with students. The basic difference in this study is that the PHP language does not require special Driver Connection Tools so that in connecting the database to the application, it is enough to create a connection script, while the Codeigniter Framework is required to use Driver Connections when connecting to the database. The final result of this research is based on System Testing at PHP Performance Level 85% and Framework 75%, PHP Information 73% and Framework 85%, PHP Control 74% and Framework 87%, PHP 75% Efficiency Framework 82%, Service on PHP 73 % and Framework 82%.

Cited by 11Open access

A Comparison of Large Language Models and Genetic Programming for Program Synthesis

Dominik Sobania, Justyna Petke, Martin Briesch et al. · IEEE Transactions on Evolutionary Computation · 2024

Large language models have recently become known for their ability to generate computer programs, especially through tools, such as GitHub Copilot, a domain where genetic programming (GP) has been very successful so far. Although they require different inputs (free-text versus input/output examples) their goal is the same—program synthesis. Therefore, in this work, we compare how well GitHub Copilot and GP perform on common program synthesis benchmark problems. We study the structure and diversity of the generated programs by using well-known software metrics. We find that GitHub Copilot and GP solve a similar number of benchmark problems (85.2% versus 77.8%, respectively). We find that GitHub Copilot generated smaller and less complex programs as GP, while GP is able to find new and unique problem solving strategies. This increase in diversity of solutions comes at a cost. When analyzing the success rates for 100 runs per problem, GitHub Copilot outperforms GP on over 50% of the problems.

Cited by 6

Analysis and comparison of sorting and search algorithms in C programming language

Anto Ivić · Repository of FERIT Osijek · 2022

U ovom završnom radu analizirani su i uspoređeni algoritmi za sortiranje i pretraživanje. Implementacija ovog zadatka izvršena je u programskom jeziku C. Definirani su pojmovi algoritma i strukture podataka. Rad prikazuje princip rada za svaki algoritam, te analizira vremensku složenost za svaki od njih. Analiza je pokazala kako su merge sort i quick sort najbrži algoritmi sortiranja, također analiza pokazuje kako odabir algoritma za pretraživanje ovisi o strukturi podataka koju koristimo, te ulaznim podacima.

Cited by 0

First Programming Language for Humanities Majors-A Comparison of Java and Swift

有賀 妙子, ARIGA Taeko · 2022

While Java, C family, and Python are the top three languages used in introductory programming courses in higher education, Swift is seldom used. This study considers whether the Swift language can be used as a first language for introductory programming for humanities majors. Learning programming is important for students regardless of major to foster computational thinking and utilize programming for their study. Our department conducted two courses to learn programming in Java and Swift for the creation of digital contents and media studies. This paper presents the contents of both courses, results of examinations, and students’ self-reflections. The result indicates that students can learn the basic programming concepts in Swift in the same way as in Java, but the effect of the Swift course for the GUI and OO parts was inferior to that of the Java course. The finding from students’ self-reflections concerning programming shows that students perceived that their confidence was enhanced in both the Swift and the Java courses.

Cited by 0

Complexity measurement of a graphical programming language and comparison of a graphical and a textual design language

Roger Goff · VTechWorks (Virginia Tech) · 1987

For many years the software engineering community has been attacking the software reliability problem on two fronts. First via design methodologies, languages and tools as a precheck on quality and second by measuring the quality of produced software as a postcheck. This research attempts to unify the approach to creating reliable software by providing the ability to measure the quality of a design prior to its implementation. Also presented is a comparison of a graphical and a textual design language in an effort to support cognitive science research findings that the human brain works more effectively in images than in text.

Cited by 0Open access

COMPARISON OF MODERN METHODS USING THE PYTHON PROGRAMMING LANGUAGE IN MASS HOUSING VALUATION

Gültekin Büyük, Fatma Bünyan Ünel · 2021

Multiple methods are used in the mass housing valuation. With the developing technology, modern methods have gained speed. In this study, a systematic study was conducted with machine learning to estimate the final price of housing property. The studied dataset contains 73 samples and 18 arguments. In this study with the Python programming language, NumPy, Pandas, Scikit–learn, Matplotlib and Seaborn, which are the basic libraries of Python, were used. Multiple linear regression (MLR) and decision tree regression method were used to perform the study. The adjusted determination coefficient ( ) was used to measure the performance of the estimation accuracy of applications. As a result of applications, the multiple linear regression model showed better results than the decision tree model.

Cited by 2

Evaluating the Haxe Programming Language Performance comparison between Haxe and platform-specific languages

Stepan Stepasyuk, Yavor Paunov · Gothenburg University Publications Electronic Archive (Gothenburg University) · 2013

The goal of this paper is to evaluate the performance of Haxe, a cross-platform programming language. By applying an experi-mental method and a statistical test, we measure and analyze the performance associated with compiling Haxe source code to five of its targets. We find a significant difference in performance between Haxe-compiled and target-specific language code on four out of five targets, two of which in favour of Haxe and two against it. Our findings are useful for developers who are consid-ering adopting the language with the intent of replacing their current development toolbox with it.

Cited by 4Open access

Coloured Petri Nets and the Language for Distributed Programming UPL: their Comparison and Translation

Аркадий Валентинович Климов · Program systems theory and applications · 2023

Сети Петри широко используются как средство моделирования распределенных мультиагентых систем. Существуют инструменты работы с расширенными сетями Петри, в которых токены нагружены произвольными данными. В частности, CPN Tools позволяет описывать, проигрывать и исследовать цветные сети Петри (Coloured Petri Nets, CPN). Ставится вопрос о возможности использовать этот инструмент для разработки, прототипирования и исследования параллельных распределенных вычислительных алгоритмов, в идеале — превращения их в работающие эффективные параллельные программы. У нас есть опыт экспериментального программирования разных алгоритмов в нашем графическом языке UPL, который пока существует как бы «на бумаге». Его сравнение с CPN показывает, что в их семантиках много общего. В статье оба языка определяются, сравниваются на примерах и через правила перевода из одного в другой. Также описываются средства управления распределением вычислений для UPL. Интересен вопрос об их переносе в CPN, где им пока аналога нет.

Cited by 0Open access