This module contains a more general approach to construct
		AlignmentAlgorithms by relying on the theoretical concept of Algebraic
		Dynamic Programming (ADP) as developed by Giegerich et al.
 
		ADP defines four ingredients for an alignment algorithm:
		1.) A signature that defines the permitted alignment operations.
		Operations are just function templates with an associated arity, meaning
		the number of arguments it takes from the left sequence and from the
		right sequence.
		In the TCSAlignmentToolbox we have a fixed signature with the following
		operations:
		REPLACEMENT(1, 1), DELETION(1, 0), INSERTION(0, 1), SKIPDELETION(1, 0)
		and SKIPINSERTION(0, 1)
		2.) A regular tree grammar that produces alignments, that is: sequences
		of operations, in a restricted fashion.
		3.) An algebra that can translate such trees to a cost. In the
		TCSAlignmentToolbox this is a Comparator.
		4.) A choice function, in case of the TCSAlignmentToolbox: the strict
		minimum or the soft minimum.
 
		An alignment algorithm in the TCSAlignmentToolbox sense of the word then
		is the combination of choice function and grammar. While we provide
		hardcoded versions of these combinations in the main package, the adp
		package allows you to create your own grammars. You can combine them with
		a choice function by instantiating one of the Algorithm classes provided
		in this package with a grammar of your choice.
 
		For example:
 
		AlignmentAlgorithm algo = new SoftADPScoreAlgorithm(my_grammar, comparator);
 
		creates an alignment algorithm that implicitly produces all possible
		alignments your grammar can construct with the given input, translates them
		to a cost using the algebra/comparator you provided and applies the
		soft minimum to return the score. This all gets efficient by dynamic
		programming.
 
		Note that there is runtime overhead when using this method in comparison
		with the hardcoded algorithms. But for complicated grammars this is a much
		easier way to go.
  
		For more information on the theory, please refer to my master's thesis:
  
		"Adaptive Affine Sequence Alignment using Algebraic Dynamic Programming"

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