Learning Extended Finite State Machine Models within Google Colab

Now it is even easier to use flexfringe (read our tool paper here), reproduce our experiments, or play with the flexible state-merging framework to learn extended variants of finite state machines, Mealy machines, or other regular/memory free automata thanks to Google Colab(oratory). Google Colab is a cloud-hosted Jupyter notebook environment (read more about Colab here). The notebooks run on a virtual machine powered by Ubuntu and allow to install new packages and dependencies.

I prepared a notebook that installs all dependencies, wraps the resulting binaries in Python functions (view on githubview on Google Colab) and provides some short usage examples using the Stamina competition data. Due to recent changes in the boost.Python library it is not yet possible to compile the Python package (as described in this paper).

If you run into any problems with flexfringe on Colab, contact me.

Screenshot of the Colab notebook showing a call to flexfringe and the (inline) visualization of the output using graphviz.

By Chris Hammerschmidt

I am a postdoctorial researcher in the SEDAN group at the Interdisciplinary Centre for Security, Reliability and Trust in Luxembourg.

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