#agent #state #finite-state-machine #state-machine #validation #configuration #model

nightly total-space

Explore the total space of states of communicating finite state machines

1 unstable release

0.1.1 Mar 29, 2021
0.1.0 Mar 29, 2021

#403 in Visualization

28 downloads per month

GPL-3.0 license

5.5K SLoC

total-space Build Status codecov Docs

Investigate the total state space of communicating finite state machines. Specifically, given a model of a system comprising of multiple agents, where each agent is a non-deterministic state machine, which responds to either time or receiving a message with one of some possible actions, where each such action can change the agent state and/or send messages to other agents; Then the code here will generate the total possible configurations space of the overall system, validate the model for completeness, validate each system configuration for additional arbitrary correctness criteria, and visualize the model in various ways.


To install:

cargo install total-space


To use this, you need to create your own main program:

use total_space;

fn main() {
    let arg_matches = total_space::add_clap(
        ... add your own command line arguments to control the model ...
    let mut model = ... Use your command line arguments to create the model ...;
    let mut output = BufWriter::new(stdout());
    model.do_clap(&arg_matches, &mut output);

The trick, of course, is in creating the model. Having done so, you get an executable program which allows computing the model (that is, collecting all the possible configurations that can be reached by the model) and generating all sorts of outputs from it (statistics, lists, and diagrams).


You can look at the API reference for details about a specific function. That is of no use at all to get started, though. For that, see examples/simple.rs for a complete simple model example. See tests/expected/example_simple for the expected results of running various commands. The svg files were generated from the dot and uml files using GraphViz and PlantUML.

That said, to understand the code, the following will help.


  • We have a finite collection of Agents.

  • Each Agent is an Instance of some Type. The Instance is a small unsigned integer (0..).

  • Each Agent has an Index in the overall system. The Index is a small unsigned integer (0..).

  • An Agent may be a Container of some Part Agents (there's also support for an agent containing two types of Parts).

  • Each Agent has a State. The type of the State is the same for all Instances of the same Type of Agent.

  • Agents can send and receive Messages between them.

  • Each Message carries a Payload from a Source Agent to a Target Agent.

  • Messages are delivered as follows:

    • Immediate - are delivered before any non-Immediate messages. This is typically used to model a Container modifying the state of a Part by sending a Message to it.

    • Unordered - may be delivered in any order.

    • Ordered - may be delivered only after delivering all previously sent messages from the same Source to the same Target.

  • A Message may Replace (overwrite) an existing Message from the same Source to the same Target. For example, this can be used to model writing to a "mailbox" memory address, where writing a new message may overwrite the previous one before it has been delivered.

  • An Agent can also trigger an Activity regardless of Messages.

  • An Activity carries a Payload, as if it was a Message from the agent to itself.

  • An Activity is delivered before any of the messages.

  • When an Agent is delivered a Payload, from either a Message or an Activity, it computes a Reaction. Computing such Reactions is the focus of the model.

  • An Agent can only consider its own State when computing a Reaction, except for Containers which can also consider the State of their Parts.

  • A Reaction may be:

    • Ignore - the Payload is discarded and no other changes are made to the system.

    • Defer - the Agent indicates the Message should only be delivered only after it changes its State. Only Messages can be Deferred. An Agent needs to explicitly identify its State as "deferring" to allow it to Defer while in that State. This is used to highlight such States in diagrams.

    • One or more Actions. If more than one Action is given, these are possible alternatives, where each one leads to a different possible flow.

  • An Action may:

    • Change the State or the Agent. This is the only way to modify the State of an Agent. Note that Containers may not directly change the state of their Parts. Instead, they need to send an appropriate (typically Immediate) Message to them that will cause them to change their State.

    • Emit zero or more Messages to other Agent(s). The total number of Messages sent by each Agent may be bounded by some limit which may be different for each Instance.

  • A system Configuration is the collection of all the States of all the Agents, all the in-flight Messages, and optionally an indication that some Invalid condition occurred.

  • An Invalid condition may occur due to a specific invalid Agent State, Message or Activity Payload, or as a result of some combinations of these in some Configuration.

  • An Action results in a Transition between Configurations.

  • The code computes the total space (graph) of Configurations and the Transitions that connect them.


The code allows applying a validation function to each State and overall Configuration. Thus, simply computing the total Configurations space can ensure arbitrary validation conditions.

The Reaction logic in each agent will typically match some combinations of its State and the Payload, which will include a catch-all Reaction::Unexpected clause. Thus computing the model verifies that no unexpected message is received while in a state that does not expect to see it.

The code also verifies the number of sent in-flight Messages from each Agent does not exceed the specified threshold. This ensures that no Agent is sending an unbounded number of Messages.

In addition, the code allows verifying that there is a path from every Configurations back to the initial Configuration, which ensures there are no deadlock Configurations or a cycle of livelock Configurations.

Finally, the code allows for generating Transition paths leading to Configurations that satisfy arbitrary conditions, which can be used to ensure that any Configuration of interest is actually reachable from the initial Configuration.

Another way to ensure the model is covered is to collect coverage information for the model (see grcov) and looking at the output to ensure that all the code was reached. Uncovered match clauses will indicate that that specific flow is not reachable from the initial Configuration, which could indicate a bug in the model or that a simpler model may suffice.


The code allows simply listing all Configurations and Transitions. This has limited usefulness, mainly for debugging.

In addition, the code can generate two types of diagrams:

  • A GraphViz diagram of all the States of some Agent and the Actions that moved the Agent between these States. This is used to visualize the behavior of each Agent in isolation.

  • A UML sequence diagram of all the Transitions between Configurations along the shortest path between Configurations that satisfy arbitrary conditions. This is used to visualize complete system scenarios.


total-space is distributed under the GNU General Public License (Version 3.0). See the LICENSE for details.


~80K SLoC