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1

Garg, Rakesh, and Supriya Raheja. "Fuzzy Distance-Based Approach for the Assessment and Selection of Programming Languages." International Journal of Decision Support System Technology 15, no. 1 (January 1, 2023): 1–19. http://dx.doi.org/10.4018/ijdsst.315761.

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Анотація:
The desire to develop software with more and more functionalities to make human work easier pushes the industry towards developing various programming languages. The existence of the various programming languages in today's scenario raises the need for their evaluation. The motive of this research is the development of a deterministic decision support framework to solve the object-oriented programming (OOP) language's selection problem. In the present study, OOP language's selection problem is modeled as a multi-criteria decision-making, and a novel fuzzy-distance based approach is anticipated to solve the same. To demonstrate the working of developed framework, a case study consisting of the selection of seven programming languages is presented. The results of this study depict that Python is the most preferred language compared to other object-oriented programming languages. Selection of OOP languages helps to select the most appropriate language, which provides better opportunities in the business domain and will result in high success for engineering students.
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2

Tratt, Laurence, and Adam Welc. "Programming Languages." IEEE Software 31, no. 5 (September 2014): 33–34. http://dx.doi.org/10.1109/ms.2014.119.

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3

Trott, Peter. "Programming languages." ACM SIGPLAN Notices 32, no. 1 (January 1997): 14–57. http://dx.doi.org/10.1145/251595.251598.

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4

Wand, Mitchell, and Daniel P. Friedman. "Programming languages." ACM SIGPLAN Notices 43, no. 11 (November 30, 2008): 133–35. http://dx.doi.org/10.1145/1480828.1480857.

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5

Anderson, Ben, and Blair MacIntyre. "Programming languages." ACM SIGCHI Bulletin 28, no. 3 (July 1996): 15–19. http://dx.doi.org/10.1145/231132.231137.

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6

Meek, Brian L. "Programming languages." ACM SIGPLAN Notices 29, no. 4 (April 1994): 49–57. http://dx.doi.org/10.1145/181761.181768.

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7

Rajaraman, V. "Programming languages." Resonance 3, no. 12 (December 1998): 43–54. http://dx.doi.org/10.1007/bf02838097.

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8

Allen, Ben. "Common Language: Business Programming Languages and the Legibility of Programming." IEEE Annals of the History of Computing 40, no. 2 (2018): 17–31. http://dx.doi.org/10.1353/ahc.2018.0011.

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9

Rock, S. T. "Developing robot programming languages using an existing language as a base—A viewpoint." Robotica 7, no. 1 (January 1989): 71–77. http://dx.doi.org/10.1017/s0263574700005051.

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SUMMARYThe development of robot languages has followed a pattern similar to that of conventional programming languages, where robot languages have been based on an existing programming language. This paper first identifies the use of an existing base as one way of developing robot programming languages, and discusses the areas of difficulty in this approach. Then, on-line and off-line programming of robots is discussed and the requirements of robot programming languages that are different to those of non-specialised programming languages are presented. A discussion and evaluation of some programming languages in terms of their appropriateness for use as the base for an intelligent robot programming language is presented. This leads to the conclusion that no current language forms an adequate base for intelligent robot programming languages. What is needed as a base is a language for use in the artificial intelligence domain, that incorporates real-time facilities.
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10

Mominjon Ogli, Khaitov Azizjon. "MODERN PROGRAMMING LANGUAGES: CLASSIFICATION AND CHARACTERIZATION." International Journal of Advance Scientific Research 02, no. 11 (November 1, 2022): 108–11. http://dx.doi.org/10.37547/ijasr-02-11-16.

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11

Thewlis, David. "Editorial: Programming languages." Software Engineering Journal 1, no. 4 (1986): 146. http://dx.doi.org/10.1049/sej.1986.0021.

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12

Goldberg, Benjamin. "Functional programming languages." ACM Computing Surveys 28, no. 1 (March 1996): 249–51. http://dx.doi.org/10.1145/234313.234414.

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13

Annevelink, Jurgen. "Database programming languages." ACM SIGMOD Record 20, no. 2 (April 1991): 318–27. http://dx.doi.org/10.1145/119995.115841.

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14

Lindsey, C. H. "Comparative programming languages." Science of Computer Programming 12, no. 2 (July 1989): 172–73. http://dx.doi.org/10.1016/0167-6423(89)90047-6.

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15

Xu, Jiafu, and Fanming Song. "Quantum programming languages." Frontiers of Computer Science in China 2, no. 2 (June 2008): 161–66. http://dx.doi.org/10.1007/s11704-008-0013-z.

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16

Heim, Bettina, Mathias Soeken, Sarah Marshall, Chris Granade, Martin Roetteler, Alan Geller, Matthias Troyer, and Krysta Svore. "Quantum programming languages." Nature Reviews Physics 2, no. 12 (November 16, 2020): 709–22. http://dx.doi.org/10.1038/s42254-020-00245-7.

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17

Thielscher, Michael. "Action Programming Languages." Synthesis Lectures on Artificial Intelligence and Machine Learning 2, no. 1 (January 2008): 1–91. http://dx.doi.org/10.2200/s00143ed1v01y200807aim005.

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18

Unruh, Dominique. "Quantum programming languages." Informatik - Forschung und Entwicklung 21, no. 1-2 (September 16, 2006): 55–63. http://dx.doi.org/10.1007/s00450-006-0012-y.

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19

Turner, Raymond. "Understanding Programming Languages." Minds and Machines 17, no. 2 (June 8, 2007): 203–16. http://dx.doi.org/10.1007/s11023-007-9062-6.

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20

Urusov, Ruslan Mukhtarovich, and Elmir Imanbekov. "CURRENT PROGRAMMING LANGUAGES." Theoretical & Applied Science 143, no. 03 (March 30, 2025): 305–8. https://doi.org/10.15863/tas.2025.03.143.23.

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21

López-Fraguas, Francisco. "Programming and Languages." JUCS - Journal of Universal Computer Science 12, no. (11) (November 28, 2006): 1464–65. https://doi.org/10.3217/jucs-012-11.

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22

D. Vu, Hieu. "PROGRAMMING LANGUAGES CHRONICLE." INTERNATIONAL JOURNAL OF COMPUTER ENGINEERING AND TECHNOLOGY 16, no. 3 (June 6, 2025): 315–29. https://doi.org/10.34218/ijcet_16_03_023.

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23

Nazarova, Nigora Karimovna. "Fundamentals of Programming." Multidisciplinary Journal of Science and Technology 5, no. 5 (June 4, 2025): 1720–23. https://doi.org/10.5281/zenodo.15593870.

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Анотація:
This scientific article presents the fundamental principles of programming, including the concepts of algorithms, data structures, programming logic, and programming languages. Basic constructs used in imperative languages are outlined, along with key principles of object-oriented programming. The paper analyzes the main stages of software development and common debugging techniques. Emphasis is placed on understanding syntax, semantics, and program logic, which serve as a solid foundation for learning modern programming languages.
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24

Van Hentenryck, Pascal. "Constraint logic programming." Knowledge Engineering Review 6, no. 3 (September 1991): 151–94. http://dx.doi.org/10.1017/s0269888900005798.

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AbstractConstraint logic programming (CLP) is a generalization of logic programming (LP) where unification, the basic operation of LP languages, is replaced by constraint handling in a constraint system. The resulting languages combine the advantages of LP (declarative semantics, nondeterminism, relational form) with the efficiency of constraint-solving algorithms. For some classes of combinatorial search problems, they shorten the development time significantly while preserving most of the efficiency of imperative languages. This paper surveys this new class of programming languages from their underlying theory, to their constraint systems, and to their applications to combinatorial problems.
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25

Đurđev, Darko. "Popularity of programming languages." AIDASCO Reviews 2, no. 2 (December 31, 2024): 24–29. https://doi.org/10.59783/aire.2024.59.

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Анотація:
Programming languages have evolved significantly since their beginning, allowing developers to communicate with machines much more quickly. From assembly languages to modern tools like Python and Rust, the IT landscape continues to grow and diversify. This paper examines the popularity and usage trends of programming languages by analyzing three prominent ranking systems: the PYPL index, the TIOBE index, and the Stack Overflow Developer Survey. These metrics provide us with insight into how many different languages are being studied and used in projects, as well as their general popularity and relevance. By comparing the data, this study shows Pythons clear dominance in the last few years, high interest in newer languages like Rust and Go, as well as the continued relevance of older languages like Visual Basic, Fortran, and PHP. This analysis highlights how programming languages are constantly evolving and shaping technological advancements.
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26

Olatunji, Ezekiel K., John B. Oladosu, Odetunji A. Odejobi, and Stephen O. Olabiyisi. "A Needs Assessment for Indigenous African Language-Based Programming Languages." Annals of Science and Technology 4, no. 2 (December 1, 2019): 1–5. http://dx.doi.org/10.2478/ast-2019-0007.

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AbstractThe development of an African native language-based programming language, using Yoruba as a case study, is envisioned. Programming languages based on the lexicons of indigenous African languages are rare to come by unlike those based on Asian and / or European languages. Availability of programming languages based on lexicons of African indigenous language would facilitate comprehension of problem-solving processes using computer by indigenous learners and teachers as confirmed by research results. In order to further assess the relevance, usefulness and needfulness of such a programming language, a preliminary needs assessment survey was carried out. The needs assessment was carried out through design of a structured questionnaire which was administered to 130 stakeholders in computer profession and computer education; including some staffers and learners of some primary, secondary and tertiary educational institutions in Oyo and Osun states of Nigeria, Africa. The responses to the questionnaire were analyzed using descriptive statistics. The analysis of the responses to the questionnaire shows that 89% of the respondents to the questionnaire expressed excitement and willingness to program or learn programming in their mother tongue-based programming language, if such a programming language is developed. This result shows the high degree of relevance, usefulness and needfulness of a native language-based programming language as well as the worthwhileness of embarking on development of such a programming language.
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27

Jain, Abhishek, Manohar Kumar, and Manohar Kumar. "System Programming Drawbacks." Journal of Advance Research in Computer Science & Engineering (ISSN: 2456-3552) 2, no. 4 (April 30, 2015): 16–22. http://dx.doi.org/10.53555/nncse.v2i4.453.

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A system programming language usually refers to a programming language used for system programming; such languages are designed for writing system software, which usually requires different development approaches when compared to application software. System software is computer software designed to operate and control the computer hardware, and to provide a platform for running application software. System software includes software categories such as operating systems, utility software, device drivers, compilers, and linkers. In contrast with application languages, system programming languages typically offer more-direct access to the physical hardware of the machine: an archetypical system programming language in this sense was BCPL. System programming languages often lack built in input/output facilities because a system-software project usually develops its own input/output or builds on basic monitor I/O or screen management services facilities. The distinction between languages for system programming and applications programming became blurred with widespread popularity of PL/I, C and Pascal.
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28

Adawiyah Ritonga and Yahfizham Yahfizham. "Studi Literatur Perbandingan Bahasa Pemrograman C++ dan Bahasa Pemrograman Python pada Algoritma Pemrograman." Jurnal Teknik Informatika dan Teknologi Informasi 3, no. 3 (November 10, 2023): 56–63. http://dx.doi.org/10.55606/jutiti.v3i3.2863.

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Анотація:
Programming Language is a language used to write computer program codes. Programming languages ​​allow programmers to instruct computers to perform certain tasks. There are many different programming languages ​​such as Python, Java, C++, PHP, JavaScript and so on. This article only focuses on explaining the C++ and Python programming languages. The aim of this article is to find out the differences between the C++ and Python programming languages ​​and to find out the advantages and functions of each programming language. From the results obtained, the two C++ programming languages ​​are more focused on Windows development, while Python is more often used in software development and the C++ programming language is more difficult to understand than the Python programming language.
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29

Muhammad, Hisham, and Roberto Ierusalimschy. "C APIs in Extension and Extensible Languages." JUCS - Journal of Universal Computer Science 13, no. (6) (June 28, 2007): 839–53. https://doi.org/10.3217/jucs-013-06-0839.

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Scripting languages are used in conjuction with C code in two ways: as extension languages, where the interpreter is embedded as a library into an application; or as extensible languages, where the interpreter loads C code as add-on modules. These two scenarios share many similarities, as in both of them two-way communication of code and data needs to take place. However, the differences between them impose design tradeoffs that affect the C API that bridges the two languages, often making a scripting language more suitable for extending than embedding, or vice-versa. This paper discusses how these tradeoffs are handled in the APIs of popular scripting languages, and the impact on their use as embedded or extensible languages.
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30

Wirth, Niklaus. "Hardware architectures for programming languages and programming languages for hardware architectures." ACM SIGARCH Computer Architecture News 15, no. 5 (November 1987): 2–8. http://dx.doi.org/10.1145/36177.36178.

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31

Wirth, Niklaus. "Hardware architectures for programming languages and programming languages for hardware architectures." ACM SIGOPS Operating Systems Review 21, no. 4 (October 1987): 2–8. http://dx.doi.org/10.1145/36204.36178.

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32

Wirth, Niklaus. "Hardware architectures for programming languages and programming languages for hardware architectures." ACM SIGPLAN Notices 22, no. 10 (October 1987): 2–8. http://dx.doi.org/10.1145/36205.36178.

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33

TKACHUK, STANISLAV, and OLEKSII MELNYK. "METHODS OF STUDYING THE SEMANTICS OF PROGRAMMING LANGUAGES BY THE STUDENTS OF PROFESSIONAL EDUCATION INSTITUTIONS." Scientific Issues of Ternopil Volodymyr Hnatiuk National Pedagogical University. Series: pedagogy 1, no. 1 (July 11, 2023): 177–84. http://dx.doi.org/10.25128/2415-3605.23.1.23.

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The article shows that in institutions of professional (vocational and technical) education, the inclusion of a block of questions devoted to the semiotics of programming languages into the content of learning languages and programming methods will contribute to the successful implementation of the system of their fundamental training in the subject field «Information Technologies». The methodological system of education, built within the framework of the methodologicalical theory, helps students acquire knowledge and skills in the semiotics of programming languages. The main theoretical and methodological provisions are outlined, on the basis of which a methodical system of teaching the semiotics of programming languages ​​and a metamodel of the teaching method itself in the form of a methodical theory have been built. On the basis of the classification of models of syntax and semantics of programming languages, carried out to build a conceptual basis for the methodological theory of teaching semiotics of programming languages, there have been selected the following sections for teaching semiotics of programming languages: formal syntax of programming languages; meaningful operational semantics of programming languages; formal operational semantics of programming languages; formal deductive semantics of programming languages; denotational semantics of programming languages. At the stage of selecting the content of the elements of the model of the methodical system for teaching the semiotics of programming languages, the central place is occupied by the problem of setting learning goals, since the selection of the content of other elements is aimed at achieving the set goals. Semiotic educational models include a system of tasks, in which the subject area of activity is developed within the framework of specific teaching methods, which involve textual statements of educational problems or tasks. The goals and content of learning the semiotics of programming languages, largely influencing each other, determine the choice of teaching methods for the section in question. For example, when considering the last block of learning content, there has been chosen a simulation or social learning model, which provides for the student’s assimilation of new information, as well as attempts to get involved in the situation of solving professional tasks based on it.
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34

Turskienė, Sigita. "Kompiuterinių matematikos sistemų programavimo kalbų lyginamoji analizė." Lietuvos matematikos rinkinys 44 (December 17, 2004): 377–82. http://dx.doi.org/10.15388/lmr.2004.31946.

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The paper analyses possibilities of programming languages of computer mathematics systems. The sum­mary table of operations of 5 programming languages is presented. The advantages and disadvantages between programming languages of computer mathematics systems (MAPLE, MATHEMATICA, MAT­LAB) and professional programming languages (C/C++, PASCAL) are presented, too. That makes easier the application of computer mathematics systems in practice.
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35

Ghasani Fathonia and Yahfizham Yahfizham. "Analisis Studi Literatur Penyelesaian Operator Aritmatika Serta Bilangan Bulat Dengan Code Sederhana Pada Bahasa Pemrograman C++." SABER : Jurnal Teknik Informatika, Sains dan Ilmu Komunikasi 2, no. 1 (November 8, 2023): 09–16. http://dx.doi.org/10.59841/saber.v2i1.604.

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Анотація:
In this increasingly sophisticated era, technology is also very often used in any situation. The use of various types of technology is growing so rapidly that learning activities in the field of technology have emerged which are usually called programming. Programming is also very interesting in the eyes of students because there are courses that are directly related to programming, namely Programming Algorithms. In programming, there are several types of languages ​​that are often used, for example the C and C++ programming languages. The C and C++ programming languages ​​are programming languages ​​that can simplify calculations in mathematics subjects, especially in the basic concepts of Arithmetic and Integers by using integer data types which contain numbers. So this literature concept study really makes it easier for programming users and readers to better understand the C and C++ programming languages ​​in calculating basic operations of Arithmetic Operators as well as calculations with simple codes on integers.
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36

Stites, Sam, John M. Li, and Steven Holtzen. "Multi-Language Probabilistic Programming." Proceedings of the ACM on Programming Languages 9, OOPSLA1 (April 9, 2025): 1239–66. https://doi.org/10.1145/3720482.

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Анотація:
There are many different probabilistic programming languages that are specialized to specific kinds of probabilistic programs. From a usability and scalability perspective, this is undesirable: today, probabilistic programmers are forced up-front to decide which language they want to use and cannot mix-and-match different languages for handling heterogeneous programs. To rectify this, we seek a foundation for sound interoperability for probabilistic programming languages: just as today’s Python programmers can resort to low-level C programming for performance, we argue that probabilistic programmers should be able to freely mix different languages for meeting the demands of heterogeneous probabilistic programming environments. As a first step towards this goal, we introduce MultiPPL, a probabilistic multi-language that enables programmers to interoperate between two different probabilistic programming languages: one that leverages a high-performance exact discrete inference strategy, and one that uses approximate importance sampling. We give a syntax and semantics for MultiPPL, prove soundness of its inference algorithm, and provide empirical evidence that it enables programmers to perform inference on complex heterogeneous probabilistic programs and flexibly exploits the strengths and weaknesses of two languages simultaneously.
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37

Guzdial, Mark, and Susan Landau. "Programming programming languages, and analyzing Facebook's failure." Communications of the ACM 61, no. 6 (May 23, 2018): 8–9. http://dx.doi.org/10.1145/3204443.

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38

Hosseini-Rad, Mina, Majid Abdulrozzagh-Nezzad, and Seyyed-Mohammad Javadi-Moghaddam. "Study of Scheduling in Programming Languages of Multi-Core Processor." Data Science: Journal of Computing and Applied Informatics 2, no. 2 (July 1, 2019): 101–9. http://dx.doi.org/10.32734/jocai.v2.i2-282.

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Анотація:
Over the recent decades, the nature of multi core processors caused changing the serial programming model to parallel mode. There are several programming languages for the parallel multi core processors and processors with different architectures that these languages have faced programmers to challenges to achieve higher performance. In additional, different scheduling methods in the programming languages for the multi core processors have significant impact on efficiency of the programming languages. Therefore, this article addresses the investigation of the conventional scheduling techniques in the programming languages of multi core processors which allows researcher to choose more suitable programing languages by comparing efficiency than application. Several languages such as Cilk++، OpenMP، TBB and PThread were studied and their scheduling efficiency has been investigated by running Quick-Sort and Merge-Sort algorithms as well
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39

Hosseini-Rad, Mina, Majid Abdolrazzagh-Nezhad, and Seyyed-Mohammad Javadi-Moghaddam. "Study of Scheduling in Programming Languages of Multi-Core Processor." Data Science: Journal of Computing and Applied Informatics 2, no. 2 (August 3, 2018): 101–9. http://dx.doi.org/10.32734/jocai.v2.i2-327.

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Анотація:
Over the recent decades, the nature of multi-core processors caused changing the serial programming model to parallel mode. There are several programming languages for the parallel multi-core processors and processors with different architectures that these languages have faced programmers to challenges to achieve higher performance. In addition, different scheduling methods in the programming languages for the multi-core processors have the significant impact on the efficiency of the programming languages. Therefore, this article addresses the investigation of the conventional scheduling techniques in the programming languages of multi-core processors which allows the researcher to choose more suitable programing languages by comparing efficiency than application. Several languages such as Cilk++، OpenMP، TBB and PThread were studied, and their scheduling efficiency has been investigated by running Quick-Sort and Merge-Sort algorithms as well.
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40

Chete, Fidelis, and Obinna Ikeh. "Towards the Design and Implementation of a Programming Language (Beex)." International Journal of Software Engineering and Computer Systems 8, no. 2 (July 1, 2022): 51–66. http://dx.doi.org/10.15282/ijsecs.8.2.2022.6.0103.

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Анотація:
Software Engineers, Computer Scientists, and Software Experts alike are faced to decide which programming language is best suited for a certain purpose as the use of programming languages grows. When we consider the various types of programming languages available today, such as Domain Specific Languages (DSL), General Purpose Languages (GPL), Functional Programming Languages (FPL), Imperative Programming Languages (IPL), amongst others, this becomes complicated. In this study, we introduce BeeX, an interpreted language, with the aim of showing the process and principles involved in language design and consider various choices faced by language designers of various programming languages. BeeX was created with simplicity in mind, thus the study focused on architectural design options. We look at the implementation standpoint and try to figure out what the basic building parts of most programming languages are, such as lexical analysis, syntax analysis, and evaluation phase. To achieve this, we created an interactive command interface that evaluated various BeeX language constructs(conditional logic statements, arithmetic expressions, loop constructs etc.) which allowed students to easily experiment with the proposed language. The results of the tests showed that students and programmers alike can use the BeeX programming language to create a variety of code structures that are simple to use.
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41

KOLODIYCHUK, A.V. "Features of application of standard programming languages for the decision of problems of development of national economy." Market Relations Development in Ukraine №10(245)2021 108 (December 28, 2021): 20–24. https://doi.org/10.5281/zenodo.5807255.

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Анотація:
The subject of the research is the peculiarities of the application of standard programming languages for solving the problems of national economy development. The purpose of the research is to determine the characteristic features of the use of standard programming languages to solve problems of national economy. Research methods. The dialectical method of scientific cognition, the method of analysis and synthesis, the comparative method, the method of generalization of data are used in the work. Results of work. The paper highlights the strengths and weaknesses of typical programming languages and reveals the features of their use to solve problems of national economy development. The Ukrainian market of programming languages is analyzed, the market shares of typical programming languages are determined. The purposes of application of programming languages in the context of economic dynamics at micro– and macro–levels are characterized. Conclusions. The results of the conducted study were the following conclusions. Statistical research has shown that the typical programming languages in Ukraine are «Java», «Java Script», C#, PHP, «Python», C++, Ruby, Swift, Objective–C, Scala, respectively. «Java», «Java Script», C# occupy 50% of the IT market, respectively. Python, Go and Kotlin can be considered as promising programming languages in our country. Features of the Android operating system and its connection with programming environments are also considered.
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42

Sushil, Kumar*1 &. Richa Aggarwal2. "COMPARISON OF PYTHON (AN OPEN SOURCE PROGRAMMING LANGUAGE) WITH OTHER PROGRAMMING LANGUAGES." Global Journal of Engineering Science and Researches 5, no. 1 (January 21, 2018): 60–63. https://doi.org/10.5281/zenodo.1156358.

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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.
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43

Usoltseva, Natalia, and Yuri Usoltsev. "Programming Language as Eligible One: Legal Aspects." Legal Linguistics, no. 30(41) (December 29, 2023): 95–101. http://dx.doi.org/10.14258/leglin(2023)3016.

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The article examines the situation with the introduction of programming languages as an eligible element and the possibilities of recognizing programming languages as acceptable and recognized by the state. It is the case now that the issues of the existence and application of programming languages for social regulations cause significant debate, although in fact we are talking only about smart contracts and the use of programming languages for their writing and launching. In other situations of professional use of programming languages, significant legal issues have not yet been raised so acutely. But the development of digital technologies and their implementation, including in the legal social regulations, is happening very rapidly. The likelihood of the need to use programming languages to regulate social relations, and with a significant overrun beyond the strictly professional range of issues, is a very near future. The existing gaps between natural and artificial languages, between regulatory norms and the technologies used for their implementation, are being annihilated very quickly. All this forces us to evaluate programming languages in the legal domain and determine the conditions and boundaries of their existence along with natural languages. The main part of the article examines the relationship between natural and artificial languages, defines the system of artificial languages proper and their classification. The status and position of programming languages existing at the moment are revealed. As a result of the research, a conclusion is made about the prospects for the existence of a programming language as an eligible one, about the possibilities and conditions of its use beyond the boundaries of professional use. The methodological basis of the research is made up of general scientific and special scientific methods: analysis, comparison, description, systematic and structural, comparative and legal, formal and logical, etc.
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44

Nigiyan, S. A. "$ \lambda $-DEFINABILITY OF BUILT-IN McCARTHY FUNCTIONS AS FUNCTIONS WITH INDETERMINATE VALUES OF ARGUMENTS." Proceedings of the YSU A: Physical and Mathematical Sciences 53, no. 3 (250) (December 16, 2019): 191–202. http://dx.doi.org/10.46991/pysu:a/2019.53.3.191.

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The built-in functions of programming languages are functions with indeterminate values of arguments. The built-in McCarthy functions $ car $, $ cdr $, $ cons $, $ null $, $ atom $, $ if $, $ eq $, $ not $, $ and $, $ or $, are used in all functional programming languages. In this paper we show the $ \lambda $-definability of the built-in McCarthy functions as functions with indeterminate values of arguments. This result is necessary when translating typed functional programming languages into untyped functional programming languages.
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45

Cummins, Fred A. "Object-oriented programming languages." ACM SIGPLAN OOPS Messenger 4, no. 2 (April 1993): 81–83. http://dx.doi.org/10.1145/157710.157725.

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46

Maxim, Bruce R. "Programming languages—comparatively speaking." ACM SIGCSE Bulletin 25, no. 1 (March 1993): 25–29. http://dx.doi.org/10.1145/169073.169092.

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47

Haftmann, Florian, Cezary Kaliszyk, and Walther Neuper. "CTP-based programming languages?" ACM Communications in Computer Algebra 44, no. 1/2 (July 29, 2010): 27–41. http://dx.doi.org/10.1145/1838599.1838621.

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48

Foster, Ian. "Compositional parallel programming languages." ACM Transactions on Programming Languages and Systems 18, no. 4 (July 1996): 454–76. http://dx.doi.org/10.1145/233561.233565.

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49

Bruce, Kim B. "Progress in programming languages." ACM Computing Surveys 28, no. 1 (March 1996): 245–47. http://dx.doi.org/10.1145/234313.234413.

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50

Zdancewic, Steve, Dan Grossman, and Greg Morrisett. "Principals in programming languages." ACM SIGPLAN Notices 34, no. 9 (September 1999): 197–207. http://dx.doi.org/10.1145/317765.317799.

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