Journal of Computer Languages最新文献

{"title":"Application of Normalized Systems Theory to pure functional code to achieve sustainability of web front-end applications","authors":"Jan Slifka,&nbsp;Robert Pergl","doi":"10.1016/j.cola.2025.101346","DOIUrl":"10.1016/j.cola.2025.101346","url":null,"abstract":"<div><div>Modern web front-end applications frequently encounter challenges in maintaining long-term stability as they evolve to accommodate new requirements. This growing complexity often leads to diminishing maintainability and, in some cases, costly rewrites. To address this issue, we propose a methodology that integrates Normalized Systems Theory (NST)–which provides the structural foundations for stable software—with functional programming (FP) principles to construct inherently evolvable front-end systems. Our approach is implemented and evaluated using Elm, a statically typed, purely functional language designed for web front-end development. By aligning Elm’s design patterns with NST theorems, we establish a framework for building systems that are modular, maintainable, and resilient to change. We validate the efficacy of this methodology through a case study of a production-grade Elm application, demonstrating notable improvements in evolvability and system sustainability. While our implementation focuses on Elm, the underlying principles extend to other functional technologies, offering a broadly applicable strategy for achieving long-term stability in web front-end architecture.</div></div>","PeriodicalId":48552,"journal":{"name":"Journal of Computer Languages","volume":"85 ","pages":"Article 101346"},"PeriodicalIF":1.8,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144880113","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Lua and lunar re-entry: Experiences with Lua for modelling and simulation of high-speed aerodynamics","authors":"Rowan J. Gollan,&nbsp;Peter A. Jacobs","doi":"10.1016/j.cola.2025.101356","DOIUrl":"10.1016/j.cola.2025.101356","url":null,"abstract":"<div><div>We describe our 15＋ years of experience using Lua as part of the development toolkit for a physics-based simulation code, <span>Eilmer</span>. The code is specialised for the simulation of gas motions at high-speeds and the use of Lua aids to manage complexity and provide flexibility. We discuss our uses of Lua including: user-programmable input configuration, user-defined run-time customisation, for data description, and as a scripting layer to D language code. The paper presents both user and developer perspectives and experiences. We conclude with some lessons learnt about using Lua in the context of a physics-based simulation code, and close with a recommendation that the inclusion of Lua in our toolkit has been a net positive and fruitful decision.</div></div>","PeriodicalId":48552,"journal":{"name":"Journal of Computer Languages","volume":"85 ","pages":"Article 101356"},"PeriodicalIF":1.8,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145465921","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Goliath and the Cognitive Load Theory","authors":"Tiago Carvalho Freitas ,&nbsp;Alvaro Costa Neto ,&nbsp;Maria João Varanda Pereira ,&nbsp;Pedro Rangel Henriques","doi":"10.1016/j.cola.2025.101372","DOIUrl":"10.1016/j.cola.2025.101372","url":null,"abstract":"<div><div>A successful teaching effort is usually dependant on several factors. From the right environment, to a precisely worded exercise statement, it rests on the teacher’s shoulders the concoction of the most effective learning assets to their students. A significant part of this process lies on practise: students commonly solidify their knowledge by solving exercises. Creating new programming exercises, specially in high-demand environments such as large classrooms, is a repetitive and error-prone process, specially when stacked with other typical affairs that educators are required to attend to. Goliath, one of the two main contributions of this article, is a template-based, Artificial Intelligence (AI) supported exercise generator, that aims to facilitate the creation of exercise repositories. By using a Domain-Specific Language (DSL) to define exercise templates, combined with the automatic generation of different exercise types, educators can use Goliath’s features to improve their exercise repositories, both in size and variety. This systematic approach allows for greater control and automatisation than using a Large Language Model (LLM) directly, as the exercises’ main components can be pre-defined and pre-configured via their templates. Goliath, which is available online for free access, has been tested and its usability assessed. Combined with these functionalities, the content of the exercises themselves, the manner in which they are presented, and how they are rated for difficulty should also be considered in high regard when designing programming exercises. The Cognitive Load Theory (CLT) provides a conceptual foundation to understand problem-solving mechanisms that are commonly found in several aspects and situations of daily life, such as solving programming exercises. This foundation has been explored and systematically structured to construct the second main contribution of this article: guides to create exercise templates in Goliath founded on the Cognitive Load Theory, aiming to improve both teaching and learning computer programming.</div></div>","PeriodicalId":48552,"journal":{"name":"Journal of Computer Languages","volume":"85 ","pages":"Article 101372"},"PeriodicalIF":1.8,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145465922","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The role of data transformation in modern analytics: A comprehensive survey","authors":"Sanae Borrohou,&nbsp;Rachida Fissoune,&nbsp;Hassan Badir","doi":"10.1016/j.cola.2025.101329","DOIUrl":"10.1016/j.cola.2025.101329","url":null,"abstract":"<div><div>Data transformation is a fundamental step in modern data analytics, enabling the conversion of raw data into structured, high-quality formats suitable for analysis. This process plays a crucial role in data cleaning, integration, and preprocessing, ensuring consistency across diverse data sources while addressing challenges such as missing values, inconsistencies, and redundancy. By applying techniques such as scaling, normalization, encoding, feature extraction, and aggregation, data transformation enhances the accuracy and efficiency of analytical and machine learning models. This study provides a comprehensive survey of data transformation techniques, categorizing them into key types: data cleaning and preprocessing, normalization and standardization, feature engineering, encoding categorical data, data augmentation, discretization and data aggregation. We analyze their impact on data quality and explore their interdependencies, presenting a structured framework that connects these transformations within the broader data preprocessing workflow. Additionally, we highlight the challenges of implementing transformation methods in large-scale, heterogeneous datasets, including data integration complexities, security concerns, and resource constraints. By synthesizing recent advancements in the field, this research offers a structured reference for data scientists and researchers, guiding them in selecting appropriate transformation strategies based on their specific analytical needs. Future work will focus on developing a complete data cleaning workflow that integrates transformation techniques for large-scale applications, emphasizing automation and scalability in modern analytics.</div></div>","PeriodicalId":48552,"journal":{"name":"Journal of Computer Languages","volume":"84 ","pages":"Article 101329"},"PeriodicalIF":1.7,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144123177","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advanced LPeg techniques: A dual case study approach","authors":"Zixuan Zhu","doi":"10.1016/j.cola.2025.101343","DOIUrl":"10.1016/j.cola.2025.101343","url":null,"abstract":"<div><div>This paper presents advanced optimization techniques for Lua Parsing Expression Grammars (LPeg) through two complementary case studies: a high-performance JSON parser and a sophisticated Glob-to-LPeg pattern converter. We demonstrate how strategic grammar construction can dramatically improve parsing performance without modifying the underlying LPeg library. For the JSON parser, we implement substitution capture and table construction optimization to reduce memory allocation overhead and improve object processing. For the Glob converter, we introduce segment-boundary separation, implement Cox’s flattened search strategy, and develop optimized braced condition handling to prevent exponential backtracking. Comprehensive benchmarks demonstrate that our JSON parser achieves processing speeds up to 125 MB/s on complex documents, consistently outperforming dkjson and showing competitive results against rxi_json across most test cases. Our Glob-to-LPeg converter exhibits 14%–92% better performance than Bun.Glob and runs 3–14 times faster than Minimatch across diverse pattern matching scenarios. This research provides practical optimization techniques for LPeg-based parsers, contributing valuable strategies to the text processing ecosystem.</div></div>","PeriodicalId":48552,"journal":{"name":"Journal of Computer Languages","volume":"84 ","pages":"Article 101343"},"PeriodicalIF":1.7,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144501341","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Supporting learners in the transition from block-based to text-based programming, a systematic review","authors":"Glenn Strong,&nbsp;Nina Bresnihan,&nbsp;Brendan Tangney","doi":"10.1016/j.cola.2025.101342","DOIUrl":"10.1016/j.cola.2025.101342","url":null,"abstract":"<div><div>This paper describes a systematic review of the approaches being taken to providing support to learners as they transition from block-based programming environments to text-based ones. It identifies and analyses the literature in the area, identifies the themes which are common across the different approaches being used, and determines gaps in the literature. With the widespread use of block-based programming environments in introductory programming education, the question of how to support learners in the transition to text-based environments has received much attention. The contribution of this paper is to analyse and characterise the approaches being taken to support learners by considering the question: what approaches have been developed to facilitate the transition from block-based programming to text-based programming for learners? To answer this, a systematic literature review was undertaken, combining manual and automatic searches to identify work in the field. A thematic analysis of the literature found eight themes covering technical and non-technical approaches to supporting transition, prompting a set of recommendations for gaps to be addressed in future development in the field.</div></div>","PeriodicalId":48552,"journal":{"name":"Journal of Computer Languages","volume":"84 ","pages":"Article 101342"},"PeriodicalIF":1.7,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144492003","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Novice modelers’ subjective comprehension and interaction with token-animated process models","authors":"Ilia Maslov ,&nbsp;Stephan Poelmans ,&nbsp;Yves Wautelet ,&nbsp;Frederik Gailly","doi":"10.1016/j.cola.2025.101350","DOIUrl":"10.1016/j.cola.2025.101350","url":null,"abstract":"<div><div>Process modeling is fundamental for effective (business) process management. Comprehension of process models by novice modelers and the effective integration of learning technologies present crucial challenges that can be addressed through the application of visualization, animation, and simulation techniques. In this study, we examine the experiences and perceptions of novice modelers deploying token-animated process models, drawing upon data from 119 college students specializing in business management and business engineering who answered comprehension questions based on these models. We concentrate on investigating perceived understanding through the utilization of Technology Adoption Model (TAM) constructs, employing Partial Least Square to validate an extended research model based on TAM. We additionally analyze qualitative data from respondents' answers to open questions to extract codes and themes that complete the research model's findings. The results confirm that token-animated process models are useful and preferred as a learning technique. Tokens enhance cognitive facilitation by incorporating visualization, animation, and simulation functionalities, resulting in improved objective and perceived comprehension. We extend the comprehension determinants of process models with perceived enjoyment and show that emotional states are also important in the utilization of tokens for teaching purposes. Over 80 % of participants reported a clear preference for using token-animated process models, confirming high levels of student acceptance. Our study also identified recommendations for enhancement and potential limitations associated with the use of animated tokens in education. Further theoretical and practical implications are finally discussed.</div></div>","PeriodicalId":48552,"journal":{"name":"Journal of Computer Languages","volume":"84 ","pages":"Article 101350"},"PeriodicalIF":1.8,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144757584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improving LLM-based code completion using LR parsing","authors":"Md Monir Ahammod Bin Atique ,&nbsp;Hyeon-Ah Moon ,&nbsp;Isao Sasano ,&nbsp;Kwanghoon Choi","doi":"10.1016/j.cola.2025.101352","DOIUrl":"10.1016/j.cola.2025.101352","url":null,"abstract":"<div><div>Code completion is a crucial feature in modern IDEs, improving programming efficiency. Traditional systems rely on prefix filtering and static ranking but often overwhelm users with lengthy, alphabetically sorted lists. Recent research has introduced LR-parsing-based approaches that derive completion candidates from language syntax and compute their ranks using open-source programs; however, these methods only suggest structural candidates, requiring manual refinement into complete code. To address this, we propose a hybrid method that integrates LR parsing with LLMs to enhance accuracy and usability. Our approach refines structural candidates using LR parsing into textual code suggestions via an LLM, referencing a database of ranked candidates from open-source programs. This combines the syntactic precision of LR parsing with the generative capabilities of LLMs. This study examines whether LLMs benefit from LR structural candidates in code completion. By comparing completions with and without these candidates, we assess their impact. Building on prior research, we also explore how leveraging top-ranked structural candidates can effectively enhance LLM-based code completion precision. We also demonstrate our method through VSCode extensions for Microsoft Small Basic and C. As a language-agnostic solution, our system applies to any language with a defined LR grammar. Our findings suggest that integrating LR parsing with LLM-based completion improves both accuracy and usability, paving the way for more effective code completion in modern IDEs.</div></div>","PeriodicalId":48552,"journal":{"name":"Journal of Computer Languages","volume":"84 ","pages":"Article 101352"},"PeriodicalIF":1.8,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144750140","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investigating the energy consumption of C++ and Java solutions mined from a programming contest site","authors":"Sérgio Queiroz de Medeiros,&nbsp;Marcelo Borges Nogueira,&nbsp;Gustavo Quezado","doi":"10.1016/j.cola.2025.101341","DOIUrl":"10.1016/j.cola.2025.101341","url":null,"abstract":"<div><div>The current concern about global warming has led to an increasing interest in the energy efficiency of computer applications. Assuming power is constant, the general trend is that faster programs consume less energy, thus optimizing a program for speed would also improve its energy efficiency.</div><div>We investigate this tendency in a set of C++ and Java solutions mined from Code Submission Evaluation System (CSES), a popular programming competition site, where each solution must give the correct answer under a given time limit. In such context, we can consider that all correct solutions for a problem were written with a speed concern, but not with energy efficiency in mind.</div><div>We selected 15 problems from CSES and for each of them we mined at least 30 C++ and Java solutions, evaluating time and energy efficiency of each solution in at least two different machines. In our scenario, where there is a great diversity of programming styles, execution speed, and memory usage, we could confirm the general trend: faster programs consume less energy. Moreover, we were able to use ordinary least squares to fit a linear function, with good precision, that relates energy consumption of a program to its execution time, as well as to automatically identify programs with abnormal energy consumption. A manual analysis of these programs revealed that often they perform a different amount of allocation and deallocation operations when compared to programs with similar execution times.</div><div>We also calculated the energy consumption profile of sets of random C++ solutions for these 15 CSES problems, and we tried to associate each set with its corresponding CSES problem by using the energy consumption profiles previously computed for each one of them. By using this approach, we could restrict, for each set of random C++ solutions, the classification task to a subset of 7 CSES problems, a reduction of more than 50% in the search space.</div></div>","PeriodicalId":48552,"journal":{"name":"Journal of Computer Languages","volume":"84 ","pages":"Article 101341"},"PeriodicalIF":1.7,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144308119","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Python’s evolution on Stack Overflow: An empirical analysis of topic trends","authors":"Fengqi Hu,&nbsp;Weihao Xue,&nbsp;Siyuan Zhou,&nbsp;Ye Wang,&nbsp;Bo Jiang,&nbsp;Qiao Huang,&nbsp;Hua Zhang","doi":"10.1016/j.cola.2025.101340","DOIUrl":"10.1016/j.cola.2025.101340","url":null,"abstract":"<div><div>With the rapid development of information technology and changing programming practices, the demand for programming discussions on online Q&amp;A platforms is growing. This study analyzes over two million Python-related posts on Stack Overflow to identify core topics and challenges over fifteen years. By using a Gradient Boosting Decision Tree (GBDT) model to quantify post popularity, we objectively show what the hottest as well as the most disturbing topics related to Python are to users at different times. We find that: The domains most closely associated with Python are data processing and machine learning, while development environments as well as automation and testing are gradually increasing in popularity. Machine learning is the area that bothers users the most. Moreover, we found that some questions that confuse users can increase the popularity of related topics. These findings can help developers grasp the direction of the Python language so that they can better plan their personal learning and project development. Enterprises and organizations can also optimize resource allocation based on trends in hot topics for training, tool development, and technical support.</div></div>","PeriodicalId":48552,"journal":{"name":"Journal of Computer Languages","volume":"84 ","pages":"Article 101340"},"PeriodicalIF":1.7,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144297313","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}