Section: New Results
Evaluation and Design of Collaborative Editing Algorithms
Participants : Mehdi Ahmed-Nacer, Luc André, Claudia-Lavinia Ignat, Stéphane Martin, Gérald Oster, Pascal Urso.
Since 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 involving large amount of contributors and a high velocity of changes. This year we continued our work on the evaluation of existing collaborative editing approaches and on the design of new algorithms that overcome limitations of state of the art ones. Moreover, we started to work on experimental user studies for understanding the real-time requirements for collaborative editing and grounding a theory for the effect of real-time constraints in collaborative work  .
We also run experiments to compare the merge automatically obtained by collaborative editing algorithms – CRDTs, OTs and the world-wide used diff3 – to the merge validated by the user. We obtain automatically such results exploiting the massively available distributed version control systems histories of open-source software. We use these results to improve an existing collaborative editing algorithm and obtain result statistically better than the existing ones (including diff3 used in major DVCS systems)  .
In existing collaborative editing algorithms shared data is usually fragmented into fixed granularity 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  we offer a solution for handling an adaptable granularity for shared data that overcomes the limitations of fixed-grained data approaches. Our solution relies on a novel commutative replicated data type (CRDT) for sequences of text that assigns unique identifiers to substrings of variable length contrary to existing CRDTs that assign unique identifiers to fixed size elements of the text (i.e. characters or lines). This offers the possibility to define coarse grained elements when they are created and refine them when needed. This greatly reduces the memory consumption since a smaller memory overhead is needed to store metadata (identifiers). Moreover, we show using simulations that overall performances of our algorithms are superior to existing ones.
We proposed a new concurrency control algorithm, based on conflict-free data types. It is built on the ideas previously developed for synchronous collaboration, extending them to support asynchronous collaboration. Our solution also includes the necessary information for providing comprehensive awareness information to users. The evaluation of our algorithm shows that comparing our solution with traditional solutions in collaborative editing, the conflict resolution strategy proposed in this paper leads to results closer to the ones expected by users  .