Fingerprint Extraction and implementation identification

[ntua-el21001]

Overview

This PR implements the Adaptive Distinguish Graph (ADG) for fingerprint extraction and implementation identification.
The ADG is a decision tree with alternating inputs and outputs in edges. A leaf contains the possible models if the path leading to them is followed.

New fingerprint classes

FingerprintLTS: A Labelled Transition System (LTS)
FingerprintGenerateLTS.CombinedLTS: An LTS created from combining Mealy Machines with the metadata
FingerprintAutomaton: Wraps the combined LTS with the intermediate results of the algorithm
FingerprintCCSExpression: Class of a CSS Expression F := 0 | μ.F | F + F
FingerprintSplittingGraph: The splitting graph of an LTS. Contains CSS expressions that partition sets of states
FingerprintNode: A node of the returned ADG

FingerprintAdgWriter: Prints and ADG to a dot file
FingerprintGenerateLTS: Generates a CombinedLTS from MealyMachines, which includes a FingerprintLTS and its metadata
FingerprintParser: Turn dot files to Mealy Machines

FingerprintComputeCompatibility: Contains the functions to calculate the Compatibility relation of state pairs in a FingerprintLTS
FingerprintSplittingGraphExtraction: Extracts the splitting graph of an LTS
FingerprintExtractDecisionTree: Uses a splitting graph and a compatibility relation of a combined LTS to create a decision tree (ADG) that differentiates between the Mealy Machines used for the LTS

New identifier classes

IdentifierAdg: Holds the ADG to be used for identification
IdentifierAutomatonProvider: Holds hypotheses to be used for conformanceTest
IdentifierParser: Reads a dot file of the ADG and turns it into a IdentifierADG

Tests

FingerprintTest: contains unit tests for fingerprintExtraction