Supporting Adaptable Granularity of Changes for Massive-scale Collaborative Editing

International audienceSince the Web 2.0 era, the Internet is a huge content editing place in which users contribute to the content they browse. Users do not just edit the content but they collaborate on this content. Such shared content can be edited by thousands of people. However, current consistency maintenance algorithms seem not to be adapted to massive collaborative updating. Shared data is usually fragmented into smaller atomic elements that can only be added or removed. Coarse-grained data leads to the possibility of conflicting updates while fine-grained data requires more metadata. In this paper we offer a solution for handling an adaptable granularity for shared data that overcomes the limitations of fixed-grained data approaches. Our approach defines data at a coarse granularity when it is created and refines its granularity only for facing possible conflicting updates on this data. We exhibit three implementations of our algorithm and compare their performances with other algorithms in various scenarios.Depuis l'ère du Web 2.0, les contenus internet sont énormément édités par de nombreux contributeurs. Ils n'éditent pas simplement, mais collaborent sur des contenus partagés, parfois à plusieurs milliers. Toutefois, les algorithmes actuels de maintien de la consistance des données ne semblent pas adaptés à la collaboration en masse. Les données partagées sont souvent découpées en petits éléments atomiques, qui peuvent être ajoutés ou supprimés. Une taille importante de ces atomes peut conduire à des conflits d'édition, tandis qu'une taille minime nécessite plus de métadonnées. Cet article propose un algorithme qui fonctionne avec une granularité adaptable pour pallier à ce problème. Nous commençons avec des éléments de grande taille, et nous les séparons en plus petits pour éviter les conflits quand nécessaire. Nous présentons trois implémentations de cet algorithme et comparons leurs performances avec d'autres, dans différents scénarios

Introducing Selective Undo Features in a Collaborative Editor

Undo is an important functionality of editors. Selective undo is widely regarded as an important feature for collaborative editing. However, even after nearly three decades of active research and development, there is still no practical support of selective undo for collaborative editing. This paper introduces the selective undo features that we have implemented as part of a collaborative editing subsystem in the GNU Emacs text editor

Calculating and Presenting Trust in Collaborative Content

Collaborative functionality is increasingly prevalent in Internet applications. Such functionality permits individuals to add -- and sometimes modify -- web content, often with minimal barriers to entry. Ideally, large bodies of knowledge can be amassed and shared in this manner. However, such software also provides a medium for biased individuals, spammers, and nefarious persons to operate. By computing trust/reputation for participating agents and/or the content they generate, one can identify quality contributions. In this work, we survey the state-of-the-art for calculating trust in collaborative content. In particular, we examine four proposals from literature based on: (1) content persistence, (2) natural-language processing, (3) metadata properties, and (4) incoming link quantity. Though each technique can be applied broadly, Wikipedia provides a focal point for discussion. Finally, having critiqued how trust values are calculated, we analyze how the presentation of these values can benefit end-users and application security

Handling Disturbance and Awareness of Concurrent Updates in a Collaborative Editor

International audienceWhen people work collaboratively on a shared document, they have two contradictory requirements on their editors that may affect the efficiency of their work. On the one hand, they would like to know what other people are currently doing on a particular part of the document. On the other hand, they would like to focus their attention on their own current work, with as little disturbance from the concurrent activities as possible. We present some features that help the user handle disturbance and awareness of concurrent updates. While collabora-tively editing a shared document with other people, a user can create a focus region. The user can concentrate on the work in the region without being interfered with the concurrent updates of the other people. Occasionally, the user can preview the concurrent updates and select a number of these updates to be integrated into the local copy. We have implemented a collaborative editing subsystem in the GNU Emacs 5 text editor with the described features

MUTE: A Peer-to-Peer Web-based Real-time Collaborative Editor

International audienceReal-time collaborative editing allows multiple users to edit shared documents at the same time from different places. Existing real-time collaborative editors rely on a central authority that stores user data which is a perceived privacy threat. In this paper, we present MultiUser Text Editor (MUTE), a peer-to-peer web-based real-time collaborative editor without central authority disadvantages. Users share their data with the collaborators they trust without having to store their data on a central place. MUTE features high scalability and supports offline and ad-hoc collaboration

High Responsiveness for Group Editing CRDTs

International audienceGroup editing is a crucial feature for many end-user applications. It requires high responsiveness, which can be provided only by optimistic replication algorithms, which come in two classes: classical Operational Transformation (OT), or more recent Conflict-Free Replicated Data Types (CRDTs). Typically, CRDTs perform better on downstream operations , i.e., when merging concurrent operations than OT, because the former have logarithmic complexity and the latter quadratic. However, CRDTs are often less responsive, because their upstream complexity is linear. To improve this, this paper proposes to interpose an auxiliary data structure , called the identifier data structure in front of the base CRDT. The identifier structure ensures logarithmic complexity and does not require replication or synchronization. Combined with a block-wise storage approach, this approach improves upstream execution time by several orders of magnitude , with negligeable impact on memory occupation, network bandwidth, and downstream execution performance