Syntax Of Programming Language Research Articles

Effective Approach for Fine-Tuning Pre-Trained Models for the Extraction of Texts From Source Codes

This study introduces SR-Text, a robust approach leveraging pre-trained models like BERT and T5 for enhanced text extraction from source codes. Addressing the limitations of traditional manual summarization, our methodology focuses on fine-tuning these models to better understand and generate contextual summaries, thus overcoming challenges such as long-term dependency and dataset quality issues. We conduct a detailed analysis of programming language syntax and semantics to develop syntax-aware text retrieval techniques, significantly boosting the accuracy and relevance of the texts extracted. The paper also explores a hybrid approach that integrates statistical machine learning with rule-based methods, enhancing the robustness and adaptability of our text extraction processes across diverse coding styles and languages. Empirical results from a meticulously curated dataset demonstrate marked improvements in performance metrics: precision increased by 15%, recall by 20%, and an F1 score enhancement of 18%. These improvements underscore the effectiveness of using advanced machine learning models in software engineering tasks. This research not only paves the way for future work in multilingual code summarization but also discusses broader implications for automated software analysis tools, proposing directions for future research to further refine and expand this methodology.

We Need to Fix Secondary School Computer Science

In recent years, the push for secondary school students to “learn to code” has increased significantly. Currently, about half of secondary schools in the United States have computer science education available to students in some form. Unfortunately, many of these schools choose a curriculum bogged down in the nuances of programming language syntax, leaving students bored, confused, unable to apply their learning to useful problems outside the classroom, and therefore disheartened about further pursuing a more conceptual computer science education in college. As a current undergraduate who has helped teach secondary school computer science, I witnessed firsthand the problems with current approaches. I, therefore, propose a shift in the focus of computing education research away from teaching “coding” effectively to elucidating a more abstract but nevertheless more pragmatic characterization of computer science as an academic field, rather than programming as a trade.

GAST: A generic AST representation for language-independent source code analysis

Organizations use various programming languages to develop their systems. These aim to take advantage of the most appropriate features of each language for a given domain and require programmers to command different languages and also to face the growing complexity of software development and maintenance. So, they need tools to help them analyze programs to identify relationships between their internal elements, uncover patterns, and calculate quality metrics. However, most tools have limited support for parsing multiple programming languages and high acquisition costs. Therefore, there is a need for new methods to analyze code written in multiple programming languages. This article describes the design of a method to automatically transform the syntax of various programming languages into a universal language with a generic syntax. The function of the generic language is to encapsulate the specificities of each specific language, so that the analysis of programs is facilitated in a single programming syntax and not in multiple syntaxes. The advantage of this approach is that only one analysis engine is required, not multiple code analyzers, to study the programs.

Computerized E-learning platform for teaching Python programming using Hausa language

Staff and students from almost every country are now learning python programming language. However, the syntax of programming languages, libraries, documentation, and instructional materials are taught and presented in English language. Non-native English speaking counties are faced with many challenges with the contents, reading and writing codes in Python. In West African countries Hausa language is one of the languages spoken by over 80 million people globally primarily found in Nigeria, Niger, Sudan, Ghana, and Cameroon. Therefore, it is imperative to teach python programming using mother’s tongue which can be understood easily by non-native English speaking country. The methodology used in this paper is python programming and Hausa languages. Results obtained indicated that there is significant increase in the rate of understanding using this technique.

METHODS OF STUDYING THE SEMANTICS OF PROGRAMMING LANGUAGES BY THE STUDENTS OF PROFESSIONAL EDUCATION INSTITUTIONS

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.

A replication study on the intuitiveness of programming language syntax

In this article, we present a replication of an empirical experiment that evaluates intuitiveness and comprehensibility of keywords relating to different concepts in programming languages, originally conducted by Stefik and Gellenbeck. Novice programmers face many barriers when learning programming. One of these barriers is syntax, which for many languages is not designed based on empirical evidence. The purpose of the experiment was to provide more empirical evidence on the subject, to find out if the results of the original experiment can be replicated and if conducting the experiment in an environment where English is not the native language affects the results. The results of our experiment replicated most of the findings of the original study and provided further evidence that some syntactic choices in many popular programming languages are unintuitive for novice programmers. Our results suggest that the native language of participants who otherwise had good English skills had little effect when compared to the original study. These results may support programming language designers in making evidence-based design decisions and teachers of introductory programming courses in identifying some of the barriers novice programmers face.

ERROR-FREE 2D PICTOGRAMMIC SYNTAX IN A PROGRAMMING LEARNING ENVIRONMENT FOR PRESCHOOL CHILDREN

When mastering the basics of programming by preschoolers, serious difficulties are created by the need to diagnose and correct syntactic errors. With the traditional method of “on-screen” program editing, these difficulties can be avoided by blocking the child’s actions that lead to syntactic violations. Today, the technique of compiling programs from material objects (tangible objects) with command icons printed on them is gaining popularity. When using this technique, no blocking of user actions is possible. In this situation, the authors propose to protect the child from syntactical errors by postulating the two-dimensionality of the program and defining the syntax and semantics of the pictogram programming language for beginners using indentation so that any placement of pictograms in the cells of a two-dimensional table gives a syntactically correct and executable program. This approach has been implemented and tested in the domestic educational environment “PictoMir” of pictogram programming for preschoolers.

Method of generating ORM models software code based on relational database schemes

Abstract. Problem. Databases and data stores are an important part of any system, regardless of the field of application. It is at this level that all system information is stored, such as a list of online store products, user personal data, system configuration parameters, etc. In addition, they allow to structure information in the desired format. Although the use of databases is associated with obvious advantages, it has some disadvantages, in particular the process of designing them and integrating their software code is labor-intensive and time-consuming. This problem is usually attempted to be circumvented by using ORM libraries, which provide a convenient programming interface for performing basic queries. But the process of setting up an ORM library including developing ORM models still takes a lot of time. Goal. The purpose of the work is to develop an algorithm for the automatic generation of software code for ORM models based on the selected ORM library and the data scheme presented in the form of a configuration file. To achieve the goal, it is necessary to establish the optimal representation of the data scheme in text format, to determine the structure of the data configuration scheme and to describe all stages of the generation of software code for ORM models. Methodology. System approach, analysis of existing methods of visual design, formats of text representation of configuration data and methods of configuration data storing. Results. The developed method for software code generation for the selected ORM library based on the scheme of the relational database provides the user with the opportunity to obtain a qualitatively designed software code with minimal time expenditure. Originality. The developed method implements a unique approach which allows to create program code for various ORM libraries, supports the syntax and features of a specific programming language, and provides work with data schemas from various relational databases. Practical value. Developed generation algorithm can be used as part of the software in which the automated process of preparing the data schema in the appropriate text formatted form will be implemented. As a result, such a web-application will represent a platform for working with the data layer for IT professionals.

SynShine: Improved Fixing of Syntax Errors

Novice programmers struggle with the complex syntax of modern programming languages like <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Java</small> , and make lot of syntax errors. The diagnostic syntax error messages from compilers and IDEs are sometimes useful, but often the messages are cryptic and puzzling. Novices could be helped, and instructors' time saved, by automated repair suggestions when dealing with syntax errors. Large samples of novice errors and fixes are now available, offering the possibility of data-driven machine-learning approaches to help novices fix syntax errors. Current machine-learning approaches do a reasonable job fixing syntax errors in shorter programs, but don't work as well even for moderately longer programs. We introduce <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">SynShine</small> , a machine-learning based tool that substantially improves on the state-of-the-art, by learning to use compiler diagnostics, employing a very large neural model that leverages unsupervised pre-training, and relying on multi-label classification rather than autoregressive synthesis to generate the (repaired) output. We describe <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">SynShine</small> 's architecture in detail, and provide a detailed evaluation. We have built <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">SynShine</small> into a free, open-source version of Visual Studio Code (VSCode); we make all our source code and models freely available.

Naming Practices in Object-oriented Programming: An Empirical Study

Currently, research indicates that comprehending code takes up far more developer time than writing code. Given that most modern programming languages place little to no limitations on identifier names, and so developers are allowed to choose identifier names at their own discretion, one key aspect of code comprehension is the naming of identifiers. Research in naming identifiers shows that informative names are crucial to improving the readability and maintainability of programs: essentially, intention-revealing names make code easier to understand and act as a basic form of documentation. Poorly named identifiers tend to hurt the comprehensibility and maintainability of software systems. However, most computer science curricula emphasize programming concepts and language syntax over naming guidelines and conventions. Consequently, programmers lack knowledge about naming practices. This article is an extension of our previous study on naming practices. Previously, we set out to explore naming practices of Java programmers. To this end, we analyzed 1,421,607 identifier names (i.e., attributes, parameters, and variables names) from 40 open-source Java projects and categorized these names into eight naming practices. As a follow-up study to further investigate naming practices, we examined 40 open-source C++ projects and categorized 1,181,774 identifier names according to the previously mentioned eight naming practices. We examined the occurrence and prevalence of these categories across C++ and Java projects and our results also highlight in which contexts identifiers following each naming practice tend to appear more regularly. Finally, we also conducted an online survey questionnaire with 52 software developers to gain insight from the industry. All in all, we believe the results based on the analysis of 2,603,381 identifier names can be helpful to enhance programmers’ awareness and contribute to improving educational materials and code review methods.

Sequre: a high-performance framework for secure multiparty computation enables biomedical data sharing

Secure multiparty computation (MPC) is a cryptographic tool that allows computation on top of sensitive biomedical data without revealing private information to the involved entities. Here, we introduce Sequre, an easy-to-use, high-performance framework for developing performant MPC applications. Sequre offers a set of automatic compile-time optimizations that significantly improve the performance of MPC applications and incorporates the syntax of Python programming language to facilitate rapid application development. We demonstrate its usability and performance on various bioinformatics tasks showing up to 3–4 times increased speed over the existing pipelines with 7-fold reductions in codebase sizes.

Search based Software Modularization Using Evolution Algorithm

To comprehend a Software system, Software modularization strategies are used. The goal of modularization is to break down a software system into meaningful and intelligible sub-systems from its source-code (modules). Because software classification modularization is an NP-hard task, evolutionary methods produce better modularization quality rather than avaricious algorithms. All available transformative techniques for software modularization only take into account structural aspects reliant on programming language syntax. Because most computer languages lack a mechanism for extracting structural characteristics, they cannot be modularized. A novel heuristic is proposed in this work. with several objectives that accomplishes both in order to lead optimization algorithms towards a proper decomposition of software systems automatically, structural (e.g.; calling dependence and in-heritance dependency) and non- structural (e.g.; semantics in code comments and identifier names) aspects are used. It is analyzed using 3 optimization plans, viz; global-based-search, combining global and local search, and Estimation of Distribution (EoD) to upgrade it. According to outcomes on Mozilla Firefox, suggested optimization algorithm based on EoD and the newly developed MOF function exceed those so it use structural-based objective functions in finding more understandable modules, as well as guiding the optimization procedure. In the lack of a unique concept, structure, the original design can be identified by using the source code of the disturbed software. Effective software maintenance depends on the concept of software system. One of most powerful techniques in software clustering is the ability to divide enormous Software systems into workable subsystems with modules of identical characteristics, thereby reducing the complexity of the system. A metaheuristic optimization imperialist competitive system has emerged algorithm, genetic algorithm, and their combination is examined for software clustering in this paper. When it comes to value, of clustering, the number of epochs required for convergence, and the standard unconventionality found at the end of repeated application of these algorithms, it appears that recursive application is the most effective for achieving the best performance.

From Critique to Computational Thinking: A Peer-Assessment-Supported Problem Identification, Flow Definition, Coding, and Testing Approach for Computer Programming Instruction

Scholars believe that computational thinking is one of the essential competencies of the 21st century and computer programming courses have been recognized as a potential means of fostering students’ computational thinking. In tradition instruction, PFCT (problem identification, flow definition, coding, and testing) is a commonly adopted procedure to guide students to learn and practice computer programming. However, without further guidance, students might focus on learning the syntax of computer programming language rather than the concept of solving problems. This study proposes a peer-assessment-supported PFCT (PA-PFCT) approach for boosting students’ computer programming knowledge and computational thinking awareness. A quasi-experiment was conducted on a computer programming course in a high school to evaluate its influence on students’ learning achievement, computational thinking awareness, learning motivation, and self-efficacy. An experimental group of 51 students learned with the proposed approach, while a control group of 49 students learned with the traditional PFCT (T-PFCT) approach. The experimental results show that the proposed approach significantly enhanced the students’ computational thinking awareness, learning motivation, and self-efficacy, while not having significant impacts on their computer programming knowledge test scores.

Counterexample-guided Spatial Flow Model Checking Methods for C Code

Software verification has always been a popular research topic to ensure the correctness and security of software. However, due to the complex semantics and syntax of programming languages, the formal methods for verifying the correctness of programs have the problems of low accuracy and low efficiency. In particular, the state change in address space caused by pointer operations makes it difficult to guarantee the verification accuracy of existing model checking methods. By combining model checking and sparse value-flow analysis, this paper designs a spatial flow model to effectively describe the state behavior of C code at the symbolic-variable level and address-space level and proposes a model checking algorithm of CounterExample-Guided Abstraction refinement and Sparse value-flow strong update (CEGAS), which enables points-to-sensitive formal verification for C code. This paper establishes a C-code benchmark containing a variety of pointer operations and conducts comparative experiments on the basis of this benchmark. These experiments indicate that in the task of analyzing multi-class C code features, the model checking algorithm CEGAS proposed in this paper can achieve outstanding results compared with the existing model checking tools. The verification accuracy of CEGAS is 92.9%, and the average verification time of each line of code is 2.58 ms, both of which are better than those of existing verification tools.

Sequence-to-Sequence Learning-Based Conversion of Pseudo-Code to Source Code Using Neural Translation Approach

Pseudo-code refers to an informal means of representing algorithms that do not require the exact syntax of a computer programming language. Pseudo-code helps developers and researchers represent their algorithms using human-readable language. Generally, researchers can convert the pseudo-code into computer source code using different conversion techniques. The efficiency of such conversion methods is measured based on the converted algorithm&#x2019;s correctness. Researchers have already explored diverse technologies to devise conversion methods with higher accuracy. This paper proposes a novel pseudo-code conversion learning method that includes natural language processing-based text preprocessing and a sequence-to-sequence deep learning-based model trained with the SPoC dataset. We conducted an extensive experiment on our designed algorithm using descriptive bilingual understudy scoring and compared our results with state-of-the-art techniques. Result analysis shows that our approach is more accurate and efficient than other existing conversion methods in terms of several performances metrics. Furthermore, the proposed method outperforms the existing approaches because our method utilizes two Long-Short-Term-Memory networks that might increase the accuracy.

Incorporating Visualization Tools and Active Learning Approach for Programming Courses

Programming languages are a vital domain for Computer and Information Technology engineering. The programming languages like C, C++, Java, Python, Mobile Application Development, and Web Technologies are important programming courses in CSE and IT curriculum. Understanding the programming courses includes a basic understanding of the syntax of programming language, logical &amp; critical thinking to solve the problem, use of various editors to write and execute the program. Effective delivery of the programming course creates a great deal of influence on student’s interest in programming and software development. The students lose their interest in programming due to the inefficient delivery of these courses which leads to a gap in technical competency required by the IT sector. The current Covid 19 pandemic exposed the limitation of traditional teaching methods for programming courses. Teaching such programming courses on online mode becomes a big challenge for faculty by considering the skillset required to inculcate amongst the students for learning programming courses. The primary objective of this paper is to overcome these challenges by the effective use of a pedagogical approach for teaching programming courses. The various active learning methods and tools are discussed in this paper that was used to teach the programming language. The result shows that by implementation of such methods &amp; tools you can retain the interest of students in programming courses and thus increase their performance and improve the skillset required in IT industry. Keywords— Computer Programming, Activity-based learning, Visualization tools, logic building, Critical thinking, Continuous Assessment.

Design and Implementation of a Programming Learning Support System Using the Concepts of Physical Visualization and Serious Gaming

The purpose of this research is the design and implementation of a support system for learning programming. To archive this purpose, in this article, we propose a Puzzle Programming System that uses jigsaw puzzles as an example of the application of physical visualization, which visualizes logical constraints to physical ones. This Puzzle Programming System aims to teach basic programming concepts by presenting the invisible constraints of programming language syntax using the visual constraints of jigsaw puzzle pieces. This system runs on an Apple iPad and was developed using the Unity game engine. We used YAML as a data format for serializing structured data for data management. By inviting high school students to try out a prototype, we could confirm the usefulness of the Puzzle Programming System. The experimental evaluation results also shed light on aspects of the game that need to be redesigned and parts where the visual programming model needs to be modified and expanded.

The execution complexity of logical formulas with restricted quantifiers based on CF-grammars

The polynomial realized formulas are introduced with quantifiers acting on hierarchy lists described by CF-grammars. Upper estimates of execution complexity are obtained depending from the sort of grammar. These formulas have been applied for formal definition of context-dependent syntax of programming languages and describing dynamic discrete system.

Development and Application of a Software Tool to Support the Teaching of Formal Languages

The purpose of the article is to present the results of a study on the possibility of using a deductive approach in the study of programming languages (from the theory of formal languages to specific programming languages) and the development of a training system for implementing this approach. The issue of training specialists in the field of information technology is still relevant, and the variety of programming languages is so great that it is not always possible to guess which of them will be in demand in professional activities. According to the authors, the application of this approach will allow you to see common elements and find syntactic differences in programming languages, and therefore simplify and speed up their development. The article analyzes the methods of teaching programming, substantiates the relevance of learning formal languages by future IT specialists, formulates the requirements for a software tool to support learning formal languages, describes its implementation. Materials and methods. Theory of formal languages, syntax and semantics of programming languages, lexical analysis, analysis of various sources of information on the subject under study, systematization of the collected data, technologies for designing, implementing and testing software products, experimental research. Results. A methodology for learning programming languages through formal languages is proposed. A software training system has been created that allows you to link the theory of formal languages with high-level languages through appropriate examples. The algorithm of checking the correctness of the task execution by means of syntactic analysis of the program entered by the student and imitation of its execution is developed and implemented in the specified system. Experiments have shown the feasibility of the approach and the performance of the software product. Currently, the developed system is used at Vologda State University when teaching the disciplines “Theory of programming languages and translation methods” and “Theory of automata and formal languages”. Conclusion. The results of the study show the acceptability of the proposed approach and the expediency of using the developed program when learning programming languages.

A Model for Enhancing Algorithmic Thinking in Programming Education using PAAM

Most novice programmers consider learning to program as a difficult and challenging field of study for them. As a result, high dropout and failure rates in programming one courses reported. One of the reasons is that most programming (1) courses don’t give equal attention to syntax and semantics of programming language and algorithmic thinking. In this study, a web application based on Problem Analysis and Algorithmic Model (PAAM) was prepared and acquainted in the programming (1) course. The application focuses on problem analysis and algorithmic thinking. The influence on genders' opinion after offering the PAAM model in the programming (1) course determined by organizing a survey. The mean values of the male and female survey respondents compared by performing the T-test. The purpose is to determine if there is any significant difference between the mean values. Results show that students appreciated the web application in the programming (1) course. Male students discerned more positive responses in the survey questions compared to female students. The T-test result shows a significant difference between the values of respondents because the p-value for equal variances assumed is (.000), which is less than p = 0.05. The application encourages a new approach based on four steps (problem statement → problem analysis → problem-solving skills → code) for novices. The application helps students to understand programming structures, program design and comprehension.