UCC PAC verifier#738
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Change `using Destructor = std::function<void(std::byte*)>` to `using Destructor = std::function<void(std::byte const*)>` in model::Type, because a) all currently implemented destructors work with const pointer; b) GetDestructor() is not used anywhere, except for implementations of pac::model::IDomain; c) implementations of pac::model::IDomain work with const pointers.
Implement TupleType class to calculate distances between fixed-sized tuples of values. Implement IDomain class to represent an ordered domain in a metric space of values. Implement default domain classes: Ball and Parallelepiped. Implement PAC and DomainPAC classes.
Add option names and descriptions required by PAC verifier
Implement base class for PAC-Man based PAC verifiers
Implement verifier for Domain Probabilistic Approximate Constraints
Implement unit tests for Domain PAC veririfier.
Implement Python bindigns for Domain PAC verifier
Implement Python examples for Domain PAC verifier
Move "validation mode" from FindEpsilonDelta into a separate function
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Move min_delta and max_delta options to concrete PAC type verifiers, since some algorithms need only min_delta option, whereas others need max_delta
Implement verifier for Functional Dependency Probabilistic Approximate Constraints
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Implement verification algorithm for Unique Column Combination Probabilistic Approximate Constraints
Implement tests for UCC PAC verification algorithm
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Probabilistic Approximate Constraint is a primitve intoduced in "Checks and Balances: Monitoring Data Quality Problems in Network Traffic Databases" by Flip Korn et al. PAC with parameters epsilon and delta means that Probability that approximate constraint with error=epsilon holds is greater than delta.
Implement UCC PAC verifier.
An UCC PAC on column set X means that Pr(dist(t_i[A_l], t_j[A_l]) <= eps) <= delta
(note that this definition differs a little from the one given in "Checks and Balances")
Add UCC PAC verifier bindings and examples.
A script to build ECDF and visually validate the results given by algorithm (and, maybe, better understand the PAC-Man algorithm) can be found here (note: there are different links in three PAC PRs).