Real-time collaborative code editors allow developers, working in distributed environments, to contribute to the same source code at the same time. This type of systems needs to host complex concurrency management, conflict resolution, and high-level user awareness logic to ensure various developers’ workflow. The following survey paper provides a structured review of twenty influential research papers: both journal articles and preprints published in the period from 2021 to 2025. We research the basic algorithms used, such as OT and CRDTs, architectures, and consider human-centric aspects. Moreover, we compare these projects’ performance measures, such as scalability, synchronization latency, and usability. The reviewed systems demonstrate high efficacy, with up to 95% operational convergence accuracy and 92% user satisfaction rates in empirical deployments. This work concludes by synthesizing a clear map of unresolved research gaps, primarily in data provenance, largescale latency optimization, and the nascent field of AI-driven collaborative coding.

We are announcing OpenCSP, an open-source platform including source code, applications, and data to enable collaborative development for the CSP community worldwide, supporting industry, research, and education. OpenCSP includes components of code, data, mechanical designs, tools, and documents, all provided under an open-source license allowing unlimited use. The OpenCSP code development environment is set up to enable collaborative team development of high-quality software, yet OpenCSP welcomes both polished code and rough code-in-progress. The goals of OpenCSP are to accelerate transfer of CSP metrology and analysis tools to industry, provide a resource for businesses supporting CSP, support CSP education, and to provide a community collaborative development environment to enable teams to build new advanced CSP applications more quickly, and to speed their deployment.

In the contemporary landscape of software development, where teams are often geographically dispersed, real-time collaborative code editors have transitioned from being a niche luxury to an absolute necessity. These advanced web-based tools provide a crucial workspace that allows multiple developers to simultaneously edit the same codebase, dramatically boosting overall team productivity, coordination, and efficiency. This project details the creation of a powerful and versatile real-time collaborative code editor. A central feature is its broad support for multiple programming languages, including key languages like JavaScript, Python, Java, C++, HTML, and CSS. This multi-language capability is seamlessly integrated with robust version control capabilities to track changes and manage history, alongside strong authentication mechanisms to ensure secure access. The foundational general methodology for achieving smooth, instant collaboration relies on two critical technologies: Operational Transformation (OT) and WebSockets. WebSockets establish a persistent, low-latency, two-way communication channel between all users and the server, ensuring data flows instantly. The Operational Transformation (OT) algorithm is the intelligence behind the synchronization; it intelligently handles concurrent changes made by different users, guaranteeing that all participants maintain an identical and consistent version of the code without conflicts. Furthermore, we enhance this synchronization by batching multiple small edits into single messages and implementing strategies to minimize data redundancy, which collectively results in a significantly smoother and more responsive collaborative experience.

This paper presents the development and implementation of a Real-Time Collaborative Code Editor (RCE), a comprehensive web-based platform designed to facilitate distributed software development through seamless real-time collaboration. The system utilizes React.js frontend framework with Node.js backend architecture, Socket.IO for real-time communication, and MongoDB for data persistence. Key features include synchronized code editing, conflict resolution mechanisms, integrated chat functionality, and multi-language syntax highlighting. The platform addresses critical challenges in distributed software development by providing instant code synchronization, eliminating version control conflicts, and enabling effective team communication. Performance evaluation demonstrates 99.2% uptime reliability, sub-100ms latency for code synchronization, and 92% user satisfaction in collaborative programming scenarios. The application successfully bridges geographical gaps in software development teams while maintaining code integrity and development workflow efficiency

In the digital age, real-time collaboration tools have become essential for software development, enabling teams to work together seamlessly across geographical boundaries. This paper introduces PeerLink, an innovative real-time collaborative code editor designed to enhance the programming experience by integrating coding, communication, and collaboration into a single platform. Built with modern web technologies such as Vite, React, and Socket.IO, PeerLink offers a responsive and interactive user interface that supports multiple programming languages, real-time code synchronization, and execution. The platform's architecture leverages WebRTC for video communication, allowing users to engage in face-to-face interactions while coding collaboratively. PeerLink’s server-side, developed with Express, manages user connections and synchronizes code changes, ensuring all participants have the latest updates. The system also incorporates state persistence, maintaining language preferences and code across sessions. This paper explores the design and implementation of PeerLink, highlighting its potential to transform collaborative coding practices by providing a comprehensive environment for developers. By addressing challenges in real-time collaboration, such as synchronization and user experience, PeerLink aims to enhance productivity and foster a more connected developer community. The findings and insights from this study contribute to the growing body of research on collaborative software development tools.

With the rapid expansion of remote collaboration tools in education and industry, the need for platforms that combine real-time communication and coding collaboration has become more pressing. Existing video conferencing solutions often lack integrated development environments necessary for technical interactions such as coding interviews or pair programming. "Connect Together" is a unified, full-stack web application that addresses this gap by merging WebRTCbased video conferencing with a collaborative code editor powered by Socket.IO. Built using modern, open-source web technologies—Node.js, Express.js, EJS, and Tailwind CSS—the platform is lightweight, scalable, and intuitive. This paper presents the system architecture, implementation methodology, performance analysis, and user feedback to demonstrate how "Connect Together" enhances the remote collaborative coding experience. Experimental evaluation indicates a significant improvement in usability and efficiency for remote technical tasks.

This study investigates Ukrainian software engineering students’ perceptions of collaborative code refactoring in a “Software Construction” course. Using two Likert scales and multiple-choice questions, 248 students evaluated general course satisfaction and collaborative learning experiences. Results showed lower satisfaction with collaborative tasks compared to general course satisfaction. Students recognized professional relevance and skill development benefits, but faced significant challenges, including reluctance to engage with others’ code and insufficient preparation for the collaborative code refactoring. Correlation analysis revealed strong motivation-growth relationships in collaborative contexts. Findings suggest that addressing technical preparation, cultural adaptation, and process clarity is essential for successful collaborative implementation.

This paper presents our endeavors in developing the large-scale, ultra-high-resolution E3SM Land Model (uELM), specifically designed for exascale computers furnished with accelerators such as Nvidia GPUs. The uELM is a sophisticated code that substantially relies on High-Performance Computing (HPC) environments, necessitating particular machine and software configurations. To facilitate community-based uELM developments employing GPUs, we have created a portable, standalone software environment preconfigured with uELM input datasets, simulation cases, and source code. This environment, utilizing Docker, encompasses all essential code, libraries, and system software for uELM development on GPUs. It also features a functional unit test framework and an offline model testbed for comprehensive numerical experiments. From a technical perspective, the paper discusses GPU-ready container generations, uELM code management, and input data distribution across computational platforms. Lastly, the paper demonstrates the use of environment for functional unit testing, end-to-end simulation on CPUs and GPUs, and collaborative code development.

PurposeThis study aims to develops an interdisciplinary business and computer science pedagogy for teaching and learning computer programming in business schools at higher education institutions and explores its associated benefits, challenges and improvement.Design/methodology/approachBased on a body of theories, an interdisciplinary pedagogy is developed and tested for programming education in a business context. Meanwhile, based on the unified theory of acceptance and use of technology, the authors used observation study and thematic analysis to explore opportunities, challenges and future improvements associated with this interdisciplinary pedagogy.FindingsThe developed pedagogy includes integrating humanism and construction theory, problem-based learning, cognitive development, active instructional strategies, synergy of individual and group programming tasks and creating an encouraging and inclusive learning environment. This study shows that business students perceive this novel pedagogy as highly valuable because it enhances their logical thinking and problem-solving abilities while giving them a sense of accomplishment. Although students face challenges in data preprocessing, error handling and translating theoretical knowledge, they find it useful to review teaching materials, seek peer support and learn independently through online resources. Further improvements in pedagogy include incorporating collaborative code reviews, using shared documents for troubleshooting and grouping students based on their prior programming experience.Practical implicationsThis interdisciplinary pedagogy can guide business schools to improve the quality of programming-related modules, enhance students’ performance and prepare them for future careers.Originality/valueThis is the first interdisciplinary study investigating teaching programming in a business context.

Abstract: The main goal of our project is to provide an online platform especially for group coding interviews. This platform provides a comprehensive environment for seamless communication between interviewers and candidates, with the goal of addressing the challenges faced during remote technical assessments. The creation ofa feature-rich web platform is the goal of our project. Thisincludes an adaptable rich text editor that enables coding in real time, a mechanism for instantaneous code evaluation via execution and compilation, integrated video conferencing for efficient communication, and the abilityto set up interview rooms to hold several interviews at once. We're designing a user intuitive interface using technology and strong programming frameworks. The main objectives of the platform are to ensure real time code execution and a seamless interview process. This is achieved by incorporating code compilation engines implementing editing tools and utilizing WebRTC for video conferencing. By creating a user-friendly and productive environment that benefits both interviewers and candidates, our platform seeks to expedite the remote technical interview process. This means reducing logistical obstacles, making thorough coding evaluations possible, and creating a positive interview environment.

GitHub marketplace for automation and innovation in software production

This project presents a real-time collaborative code editor, uniquely enhanced with a voice chat feature to facilitate seamless communication among team members. Built using Express.js for the backend and Next.js for the frontend, and utilizing a Firebase database for efficient data management, the system offers a user-friendly and interactive interface. Key functionalities include a login page where users can sign up with their name, email ID, and password, and an interactive dashboard for managing projects. Projects can be categorized as public or private, with public projects accessible to anyone and private projects restricted to the owner. Users can invite teammates to collaborate on projects via unique project-specific links. The system supports up to 10 participants in a single room, allowing multiple users to work together effectively. The collaborative environment is powered by WebSockets for real-time communication and incorporates the Gemini API for additional team interaction and query resolution. WebRTC is utilized for the voice chat feature, enabling users to have live audio discussions while working on code. Additionally, users can compile the code directly within the editor, supporting languages such as C, JavaScript, Python, and Go. Overall, this project aims to enhance productivity and teamwork in coding projects by integrating robust real-time collaboration tools and features, providing a comprehensive and interactive platform for developers. KEYWORDS: Collaborative Realtime Code Editor, Next.js, Node.js, Socket.io, Express.js, Web Application.

The French Alternative Energies and Atomic Energy Commission (CEA) has played a substantial role in advancing fourth-generation reactor technologies, including Sodium-cooled Fast Reactors (SFR), which are anticipated to offer enhanced efficiency, adaptability, and sustainability compared to existing nuclear technologies. In the context of safety assessment, it is crucial to precisely simulate accidental scenarios like Unprotected Loss Of Flow (ULOF) transients. These transients entail intricate multi-physics interactions within the reactor, particularly within the core, encompassing thermal-hydraulics, reactor physics, and fuel performance (e.g. changes in densities or temperatures will lead to neutronics effects, thus power, then causing feedbacks onto said densities and temperatures).In order to capture those complex phenomena, a multi-physics coupling approach for SFRs, which combines the CATHARE3 code for system scale thermal-hydraulics, the APOLLO3 code for reactor physics, and the GERMINAL V2 code for nuclear fuel performance has been developed at CEA in the recent years.This paper presents a comprehensive methodology of such coupling and its integration into a Verification, Validation and Uncertainty Quantification (VVUQ) process. The first part of the paper provides an introduction to the simulation tools used for the coupling. The following section explains the multi-physics coupling approach, facilitated by CEA’s Collaborative Code Coupling Platform (C3PO), which enables code integration through a Python interface to create a comprehensive simulation model. A detailed examination of the coupling algorithm and data transfer mechanisms is also provided.The generality and reliability of this approach are demonstrated by simulating two accidental transients: the Unprotected Loss Of Flow (ULOF) in the ASTRID reactor and the Loss Of Flow WithOut Scram (LOFWOS) in the Fast Flux Test Facility (FFTF), both corresponding to a primary pump trip without control rods falling. The results show that the proposed multi-physics coupling scheme is effective and robust for SFR simulations. The coupled model enables a more accurate and realistic representation of the complex phenomena occurring in the reactor during an accident.This research underscores the significance of multi-physics coupling in the analysis of SFRs and serves as a valuable point of reference for future SFR studies. The proposed approach offers an efficient way to investigate SFR responses during accidents or incidents, thereby advancing the development of dependable and precise simulation tools for SFR design and evaluation.

The Collaborative Code Editor is a web application designed to transform the coding experience by facilitating real-time collaboration among multiple programmers. The study aimed to create a feature-rich platform, encompassing user registration, a syntax-highlighting code editor, real-time collaboration using WebSockets, cursor tracking, chat functionality, version control, code execution, error highlighting, file sharing, and responsive design. The systematic development yielded a user-friendly environment supporting various programming languages. Results indicate a significant 30% increase in productivity, attributed to the seamless collaboration, cursor tracking, chat features, and version control. Syntax highlighting, error detection, and code execution further enhanced code quality. The Collaborative Code Editor empowers teams to innovate rapidly, fostering a collaborative space for knowledge exchange. Supporting multiple languages and facilitating realtime communication contributes to its versatility. In conclusion, the study highlights the platform's transformative impact, overcoming solo coding limitations, and emphasizing the need for efficient collaborative tools in modern software development. The findings underscore the significance of such platforms in advancing collaborative coding practices, providing a comprehensive solution for effective team collaboration.

Enhancing Computer Science Education: The Benefits of Real-Time Collaborative Code Editors in Schools and Universities.

NASA's ITS_LIVE project delivers information on global glacier dynamics and provides historical context for climate change with a record of how every glacier in the world has evolved over decades of satellite observation. To handle petabytes of data in the satellite archives and a constant influx of new observations, the project has adopted a cloud-native approach that is scalable, performant, user friendly, and embraces transparent and collaborative code development. As every discipline of Earth science is being transformed by a new era of remote sensing and cloud computing, ITS_LIVE offers a progressive approach to maximizing scientific advancements through open science.

Abstract Source code authorship attribution can be used for many types of intelligence on binaries and executables, including forensics, but introduces a threat to the privacy of anonymous programmers. Previous work has shown how to attribute individually authored code files and code segments. In this work, we examine authorship segmentation, in which we determine authorship of arbitrary parts of a program. While previous work has performed segmentation at the textual level, we attempt to attribute subtrees of the abstract syntax tree (AST). We focus on two primary problems: identifying the primary author of an arbitrary AST subtree and identifying on which edges of the AST primary authorship changes. We demonstrate that the former is a difficult problem but the later is much easier. We also demonstrate methods by which we can leverage the easier problem to improve accuracy for the harder problem. We show that while identifying the author of subtrees is difficult overall, this is primarily due to the abundance of small subtrees: in the validation set we can attribute subtrees of at least 25 nodes with accuracy over 80% and at least 33 nodes with accuracy over 90%, while in the test set we can attribute subtrees of at least 33 nodes with accuracy of 70%. While our baseline accuracy for single AST nodes is 20.21% for the validation set and 35.66% for the test set, we present techniques by which we can increase this accuracy to 42.01% and 49.21% respectively. We further present observations about collaborative code found on GitHub that may drive further research.

A modern online interview platform for recruitment system

Computational methods, coding, and software are important tools for conducting research. In both academic and industry data analytics, open-source software (OSS) has gained massive popularity. Collaborative source code allows students to interact with researchers, code developers, and users from a variety of disciplines. Based on the authors’ experiences as graduate students and coding instructors, this paper provides a unique overview of the obstacles that graduate students face in obtaining the knowledge and skills required to complete their research and in transitioning from an OSS user to a contributor: psychological, practical, and cultural barriers and challenges specific to graduate students including cognitive load in graduate school, the importance of a knowledgeable mentor, seeking help from both the online and local communities, and the ongoing campaign to recognize software as research output in career and degree progression. Specific and practical steps are recommended to provide a foundation for graduate students, supervisors, administrators, and members of the OSS community to help overcome these obstacles. In conclusion, the objective of these recommendations is to describe a possible framework that individuals from across the scientific community can adapt to their needs and facilitate a sustainable feedback loop between graduate students and OSS.

The ongoing era of the Internet of Things is opening up new opportunities towards the integration and interoperation of heterogeneous technologies at different abstraction layers, going from the so-called Edge Computing up to the Cloud and IoT Data Analytics level. With this evolution process the issue of efficient remote reprogramming on the Edge and the Extreme Edge deployments is becoming accentuated, as the amount and diversity of embedded sensing platforms is getting larger. To take advantage of the participation of heterogeneous devices and their in-field dynamic collaboration, in this work a new distributed code dissemination strategy for Edge node reprogramming is proposed, so as to efficiently support the functional reconfiguration, optimization and updating of sensor devices. It combines a partial reprogramming engine integrated into a modular sensor node architecture, with a smart IoT wearable platform for implementing the field collaborative framework. Results show that the proposed solution outperforms other traditional centric dissemination strategies, particularly when expanding the network reprogramming diversity and scale, which is an increasingly common feature in the IoT device deployments and maintenance.