Zan‐Kai Chong, Hiroyuki Ohsaki, Bryan Ng et al. · 2016
Rateless erasure code (REC) is an erasure code, where the encoder generates a potentially infinite number of encoded symbols and the original message can be reconstructed from a sufficient number of correctly received packets. Many REC-based transmission protocols have been proposed for improving network throughput in lossy channel. However, state-of-the-art RECs (such as LT code and Raptor code) are not efficient for transmitting short messages. Recent studies suggest that network traffic is characterised by bursts of short messages and thus existing transmission protocols do not benefit from the gains of deploying REC. In this paper, we propose an REC-based transmission protocol, namely UDP-RC, which integrates the simplicity of UDP and strength of systematic Random code suited to network traffic with short messages. It attains high throughput by transmitting short messages reliably with lower overheads over lossy channel. We experimentally show that UDP-RC achieves at least 50% higher throughput and maintains more stable throughput compared to TCP (Transmission Control Protocol) and UDT (UDP Data transfer) protocol under both ideal and lossy channel conditions.
Cited by 2
Monteiro-Fialho, Leonardo, Cueto, Enrique · Zenodo (CERN European Organization for Nuclear Research) · 2024
The following are the Jupyter Notebook in charge of the analysis for the smart card systematic mapping review and the datasets. This systematic mapping review aims to comprehensively examine the current state-of-the-art in using smart cards for analytical studies applied to public transportation research. The review focuses on identifying and analyzing the main analytical purposes, algorithmic approaches, methods, datasets, and trends employed in these studies. The methodology followed the PRISMA statement for systematic reviews. This code is used for obtaining the results after extracting the data from the selected studies, also provided in the datasets folder. The software repository in GitHub: GeoTecINIT/smartcard-systematic-mapping-review (github.com)
Cited by 0Open access
Monteiro-Fialho, Leonardo, Cueto, Enrique · Zenodo (CERN European Organization for Nuclear Research) · 2024
The following are the Jupyter Notebook in charge of the analysis for the smart card systematic mapping review and the datasets. This systematic mapping review aims to comprehensively examine the current state-of-the-art in using smart cards for analytical studies applied to public transportation research. The review focuses on identifying and analyzing the main analytical purposes, algorithmic approaches, methods, datasets, and trends employed in these studies. The methodology followed the PRISMA statement for systematic reviews. This code is used for obtaining the results after extracting the data from the selected studies, also provided in the datasets folder. The software repository in GitHub: GeoTecINIT/smartcard-systematic-mapping-review (github.com)
Cited by 0Open access
Shaw, Kelsey · Figshare · 2025
All data and code for a systematic review of models of co-circulating pathogens of human disease
Cited by 0Open access
2008
Abstract — This paper presents an authentication watermarking method which can localize the tampering regions in fine granularity. Unlike the previous block-wise Tampering-Localization watermarking methods which embed authentication messages including the image index, block index and block hash, the present scheme encodes the block hash with a systematic error correcting code and then merely embeds the parity symbols into the blocks. At the verification stage, each block hash can be recovered with the embedded parity symbols if the number of tampered blocks is within a threshold value. Since the total size of parity symbols is much smaller than the total size of block hashes, the present paper reduces the size of the authentication message greatly and hence increases the localizing granularity or security strength.
Cited by 0
Jesús Moreno-León, Gregório Robles · 2016
The use of computer programming in K-12 spread into schools worldwide in the 70s and 80s of the last century, but it disappeared from the educational landscape in the early 90s. With the development of visual programming languages such as Scratch, this movement has emerged again in recent years, as teachers at all educational levels and from different disciplines consider that the use of programming enhances learning in many subjects and allows students to develop important skills. The systematic literature review presented in this article aims to summarize the results of recent research using programming with Scratch in subjects not related to computing and communications, as well as studies analyzing the kind of skills students develop while learning to code in this environment. Although the analyzed papers provide promising results regarding the use of programming as an educational resource, this review highlights the need to conduct more empirical research in classrooms, using larger samples of students that allow to obtain clear conclusions about the types of learning that could be enhanced through programming.
Cited by 58
Akond Rahman, Rezvan Mahdavi-Hezaveh, Laurie Williams · Information and Software Technology · 2018
Cited by 150Open access
Praveen Singh Thakur, Satyendra Singh Chouhan, Santosh Singh Rathore et al. · Journal of Systems and Software · 2026
Cited by 0
Linhua MA, Shiping LIU, Xing HU et al. · SHILAP Revista de lepidopterología · 2018
In order to solve the delay caused by step-by-step calculation and the computational complexity caused by iterative “exclusive-or” computation during the encoding process,a dimensionality reduction strategy was proposed and defined.Based on this,system polarization code parallel coding algorithm for cracking strategy was proposed.Simulation and computational complexity analysis were carried out on AWGN channel.The results show that the coding gain of the above algorithm is slightly better than the traditional one or almost the same,but the computational complexity is up to 80.92%,which is more suitable for hardware implementation and engineering application.It is more suitable for hardware implementation and has a certain practical value.
Cited by 0Open access
Aymane Rgaguena, Imane Chlioui, Maryam Radgui · 2025
Generative artificial intelligence (AI) has greatly advanced the code translation process, particularly through large language models (LLMs), which translate source code from one programming language into another. This translation has historically been error-prone, labor-intensive, and highly dependent on manual intervention. Although traditional tools such as compilers and transpilers have restrictions in managing complex programming paradigms, recent generative AI models most importantly those based on transformer architectures, have shown promise. This systematic mapping study intends to evaluate and compile studies on Generative AI applications in code translation released between 2020 and 2025. Using five main criteria, the publication year and channel, research type, publication type, empirical study type, and AI models. A total of 53 relevant articles were chosen and examined. The results show that conferences and journals are the most often used publishing venues. Although historical-based evaluations and case studies were the empirical methodologies most often used, researchers have primarily focused on implementing transformer-based artificial intelligence models.
Cited by 0Open access
Tony, Catherine, Díaz Ferreyra, Nicolás E., Mutas, Markus et al. · TUHH Open Research · 2025
Large Language Models (LLMs) are gaining momentum in software development with prompt-driven programming enabling developers to create code from Natural Language (NL) instructions. However, studies have questioned their ability to produce secure code and, thereby, the quality of prompt-generated software. Alongside, various prompting techniques that carefully tailor prompts have emerged to elicit optimal responses from LLMs. Still, the interplay between such prompting strategies and secure code generation remains underexplored and calls for further investigations. Objective: In this study, we investigate the impact of different prompting techniques on the security of code generated from NL instructions by LLMs. Method: First, we perform a systematic literature review to identify the existing prompting techniques that can be used for code generation tasks. A subset of these techniques are evaluated on GPT-3, GPT-3.5, and GPT-4 models for secure code generation. For this, we used an existing dataset consisting of 150 NL security-relevant code generation prompts. Results: Our work (i) classifies potential prompting techniques for code generation (ii) adapts and evaluates a subset of the identified techniques for secure code generation tasks, and (iii) observes a reduction in security weaknesses across the tested LLMs, especially after using an existing technique called Recursive Criticism and Improvement (RCI), contributing valuable insights to the ongoing discourse on LLM-generated code security.
Cited by 0Open access
Pedro Valente · Mendeley Data · 2022
Systematic literature review of automatic code generation approaches based on modeling
Cited by 0Open access
Jaime Sayago-Heredia, Ricardo Pérez‐Castillo, Mario Piattini · Greater South Information System · 2021
Code repositories contain valuable information, which can be extracted, processed and synthesized into valuable information.It enabled developers to improve maintenance, increase code quality and understand software evolution, among other insights.Certain research has been made during the last years in this field.This paper presents a systematic mapping study to find, evaluate and investigate the mechanisms, methods and techniques used for the analysis of information from code repositories that allow the understanding of the evolution of software.Through this mapping study, we have identified the main information used as input for the analysis of code repositories (commit data and source code), as well as the most common methods and techniques of analysis (empirical/experimental and automatic).We believe the conducted research is useful for developers working on software development projects and seeking to improve maintenance and understand the evolution of software through the use and analysis of code repositories.
Cited by 0Open access
J. E. Fernández, V. G. Molinari · Advances in X-ray Analysis · 1992
Cited by 1
Hieke Keuning, Johan Jeuring, Bastiaan Heeren · 2023
While functionality and correctness of code has traditionally been the main focus of computing educators, quality aspects of code are getting increasingly more attention. High-quality code contributes to the maintainability of software systems, and should therefore be a central aspect of computing education. We have conducted a systematic mapping study to give a broad overview of the research conducted in the field of code quality in an educational context. The study investigates paper characteristics, topics, research methods, and the targeted programming languages. We found 195 publications (1976-2022) on the topic in multiple databases, which we systematically coded to answer the research questions. This paper reports on the results and identifies developments, trends, and new opportunities for research in the field of code quality in computing education.
Cited by 48
Abhishilpa Nandini, Randeep Singh, Amit Rathee · International Journal of System of Systems Engineering · 2024
Software systems with code smells are difficult to maintain and evolve, and this impaired quality raises question marks on their future sustainability. Researchers have spent decades studying refactoring and code smells, which are key factors behind this problem. In lieu of the fact that the literature contains a huge collection of research publications that keeps evolving with time, dealing with code smell and refactoring activities is a challenge. Therefore, this paper targets a tertiary systematic literature survey. It aims at defining code smell and refactoring in general, identifying and analysing various tools and techniques available for code smell along with refactoring, identifying standard datasets available in the literature for the research community, and determining actively tackled code smells. This review paper considers 280 primary research publications collected from leading databases. The presented observations and recommendations are crucial for academic researchers as well as industry professionals.
Cited by 4Open access
Frank F. Xu, Uri Alon, Graham Neubig et al. · 2022
Large language models (LMs) of code have recently shown tremendous promise in completing code and synthesizing code from natural language descriptions. However, the current state-of-the-art code LMs (e.g., Codex) are not publicly available, leaving many questions about their model and data design decisions. We aim to fill in some of these blanks through a systematic evaluation of the largest existing models: Codex, GPT-J, GPT-Neo, GPT-NeoX-20B, and CodeParrot, across various programming languages. Although Codex itself is not open-source, we find that existing opensource models do achieve close results in some programming languages, although targeted mainly for natural language modeling. We further identify an important missing piece in the form of a large open-source model trained exclusively on a multi-lingual corpus of code. We release a new model, PolyCoder, with 2.7B parameters based on the GPT-2 architecture, that was trained on 249GB of code across 12 programming languages on a single machine. In the C programming language, PolyCoder outperforms all models including Codex. Our trained models are open-source and publicly available at https://github.com/VHellendoorn/Code-LMs, which enables future research and application in this area. We have an online appendix at https://arxiv.org/abs/2202.13169.
Cited by 469Open access
José Pereira dos Reis, Fernando Brito e Abreu, Glauco de Figueiredo Carneiro et al. · Repositório Institucional do ISCTE-IUL (ISCTE-IUL) · 2022
Cited by 14Open access
Minoru Kuribayashi, Masakatu Morii · IEICE Transactions on Information and Systems · 2016
Quick Response (QR) code is a two dimensional barcode widely used in many applications. A standard QR code consists of black and white square modules, and it appears randomized patterns. By modifying the modules using certain rule, it is possible to display a logo image on the QR code. Such a QR code is called an aesthetic QR code. In this paper, we change the encoding method of the Reed-Solomon (RS) code to produce an aesthetic QR code without sacrificing its error correcting capability. The proposed method randomly produces candidates of RS blocks and finds the best one during encoding. Considering an image to be displayed, we also introduce a weighting function during random selection that classifies the visually important regions in the image. We further investigate the shape of modules which represents the image and consider the trade-off between the visual quality and its readability. As a result, we can produce a beautiful aesthetic QR code, which still can be decoded by standard QR code reader.
Cited by 9Open access
Amit Rathee, Randeep Singh, Abhishilpa Nandini · International Journal of System of Systems Engineering · 2023
Cited by 0Open access