Skip to content
Switch branches/tags
Go to file

Latest commit


Git stats


Failed to load latest commit information.
Latest commit message
Commit time


formic - formidable internet collaboration

Build Status Scala.js


formic is a library to enable Operational Transformation (OT) in applications and thus enable collaborative work. The goal is to hide the details of OT and let developers work with data structures as if they were not edited concurrently. All OT data structures are eventually consistent.

You can also check the Wiki for more details.

Why the name formic?

Caution, minor Ender's Game spoiler!

The Formic in Ender's Game by Orson Scott Card are capable of instant, faster-than-light thought communication. Except for the faster-than-light part, this library shall help with non-blocking, instant modification of data.

The library

The library itself was developed as part of a graduation project. It consists of three main modules:

  • common
  • client
  • server

All modules depend on the common module. The server part can run as a standalone server and is based on Scala and Akka. The client part, a ScalaJS implementation, is intended to be intergrated into a larger application, your application! The client part can be used either from JavaScript or from Scala/ScalaJS.

In addition to those modules, three data structures are already supported. The modules provide the classes that can be directly used. It is not necessary to use all of them. Nevertheless, the JSON module depends on the tree module. The concrete data structures are:

  • linear structures
  • trees
  • JSON objects

The data structure modules contain both the implementations for the client and the server. Developers who want like to use formic work mainly with the client part. The server only needs some basic configuration and an Akka route to work.

Client and server are basically independent of each other. The client implementation is not limited to ScalaJS and could be implemented in any other language. The only things that are expected are a WebSocket connection and the Wave OT algorithm (for more information about that one, see here).


Client and server communicate via JSON messages over a WebSocket connection. The messages are sent as plain text messages.

The existing messages for client <-> server communication are defined in FormicMessage and the JSON serialization in FormicJsonProtocol. Internally, uPickle is used for the serialization.

Custom operations

Because the possible operations that can be applied to a data structure shall not be limited up-front, every data structure implementation has to provide an implementation of a FormicJsonDataStructureProtocol and register it at the FormicJsonProtocol. The custom protocol is used to de-/serialize the operations of a data structure.

Adding data structures

In order to add the data structures one needs or custom ones to the client and server, the cake pattern was used. The data structures all provide an implementation of the traits ClientDataStructureProvider and ServerDataStructureProvider. When instantiating the server, it can simply be done with the desired data structures, e.g.:

val server = new FormicServer with ServerDataStructures {
  override val dataStructureProvider: Set[ServerDataStructureProvider] =

For the client the same applies, only the class FormicSystem has to be used.

Running the example

There exist two possibilities to start the example application. The first one is to use Heroku to deploy the application and run it (see the button above). The second one is to download the sources and start the application locally.

In order to start the sample application locally, two environment variables have to be set: PORT and TMPDIR. PORT defines the port on which the web application will run and TMPDIR is used to store the persisted objects. After that, clone the project and start sbt in the root directory. Then switch into the exampleJVM project and then enter reStart:

project exampleJVM

Simply using run might conflict with the main class ScalaJS expects. The webserver then starts on, so you can access it either using your current ip or localhost. The example for strings, trees and basic JSON is present at the root page or index. If you want to play collborative battleship you have to navigate to localhost:PORT/battleship. If another player wants to join the Battleship game he/she has to copy the id into the input field next to start and press it.

The /battleship url is also valid on Heroku.



In order to start the server, create a new instance with the data structures you need (see Adding data structures). When calling start(), an Akka Http.ServerBinding has to be passed to it. This network route tells the server to which addresses it should listen. You can configure the routes any way you want to, but one route has to use the newUserProxy method the server provides. This is necessary to know which users connect and to handle their messages. Your route could look like this:

    path("formic") {
      authenticateBasic[String]("FormicRealm", (creds) => authenticator.authenticate(creds)) {
        identifier =>
          get {


A client connection is easily established. The configuration has to be provided (see Configuration section) and then FormicSystemFactory.create() is called with the config and the data structure provider. Invoking init on the FormicSystem will establish the connection.



The server can be configured like any Akka application. An application.conf has to be placed in the resources directory, so that Akka can find it. For the formic server

-address -port -incomingBufferSize -outgoingBufferSize

can be configured. The log level is controlled via Akka. A configuration could look like this:

akka {
  loglevel = debug
  http.client.idle-timeout = 10 minutes

formic {
  server {
    address = ""
    port = 8080
  client {
    buffersize = 100


Configuration on the client depends on the environment. Within Scala, it is sufficient to provide an application.conf. Within JavaScript this does not work. There, it is the best way to pass the configuration string to the com.typesafe.config.ConfigFactory. The returned object can then be passed to the FormicSystemFactory. The client needs the server address and port to be able to connect. Apart from that, its buffer size can be configured, e.g.:

formic {
  server {
    address = ""
    port = 8080
  client {
    buffersize = 100


formic's performance was evaluated using the simulations in the formic-gatling module and the test you can find in this repository. It was shown that formic can compete with e.g. GoogleDocs and ShareDB.

If you intend to replay the Gatling tests, simply import the de.tu_berlin.formic.gatling.Predef class. It provides you with the entry point by calling formic("foo"). Please note that if you intend to run the tests in a distributed way the data structure instance ids have to be generated up front. If all virtual users are on a single computer, a simple feeder will suffice.


All data structures can be persisted on the server. Persistence is completely based on Akka Persistence. The configuration has to be placed in the application.conf of the server. A configuration could look like this:

akka {
  loglevel = info
  http.server.idle-timeout = 10 minutes

  persistence {
    journal {
      plugin = "akka.persistence.journal.leveldb"
      leveldb {
        dir = ${TMPDIR}"/persistence/journal"
        native = on
    snapshot-store {
      plugin = akka.persistence.snapshot-store.local
      local.dir = ${TMPDIR}"/persistence/snapshots"

where TMPDIR must be set in the environment, e.g. .bashrc.

Final thoughts

Suggestions about how to improve formic are appreciated.

Next to its functional intention, formic can also be seen as an example application for Scala, ScalaJS, Akka and AkkaJS. The example application also contains some Selenium based tests.


formic - formidable internet collaboration





No releases published


No packages published