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Fuzzy Testing is your Swiss Knife (Was: Performance of Mercio’s Total Order)

From Mild Shock <janburse@fastmail.fm>
Newsgroups sci.math
Subject Fuzzy Testing is your Swiss Knife (Was: Performance of Mercio’s Total Order)
Date 2025-08-15 23:54 +0200
Message-ID <107oa9r$3c8m$1@solani.org> (permalink)
References <106p0ct$3b6se$3@solani.org> <107lai9$1hn9$2@solani.org> <107oa45$3c0p$3@solani.org>

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 > I see it as fuzzy testing of the community.
 > It is certainly beneficial if used correctly

Fuzzy Testing goes also by the name QuickCheck.
You can use Fuzzy Testing also for benchmarking.
Mathematically it uses the Law of Large Numbers:

Law of large numbers
https://en.wikipedia.org/wiki/Law_of_large_numbers

Means you even don’t need a random generator
with a programmable seed, so that a comparison
involves the exact same random number sequences.

Just assume that your results have a variation σ.
Then most likely the overall variation decreases
proportionally to the number n of experiments,
i.e. gets washed out:

VAR(X) = σ^2 / n

A third use case of Fuzzy Testing is to determine
frequentist probabilities . Like when I determined
that 25% of a variant of @kuniaki.mukai compare/3
triples are not transitive.

Mild Shock schrieb:
> You can use Fuzzy Testing also for
> benchmarking. Not only to find faults.
> For example when I benchmark mercio/3 via
> fuzzy/1, I find it doesn’t fare extremly bad:
> 
> ?- time((between(1,100,_), mercio, fail; true)).
> % 4,386,933 inferences, 0.375 CPU in 0.376 seconds (100% CPU, 11698488 
> Lips)
> true.
> 
> And I am not using some of the optimization
> that @kuniaki.mukai posted elsewhere and that
> I posted 06.08.2025 on comp.lang.prolog. Fact is,
> it only ca. 20% slower than SWI-Prologs compare/3:
> 
> ?- time((between(1,100,_), swi, fail; true)).
> % 3,786,880 inferences, 0.312 CPU in 0.325 seconds (96% CPU, 12118016 Lips)
> true.
> 
> The test harness was:
> 
> swi :-
>      between(1,1000,_),
>      fuzzy(X), fuzzy(Y),
>      swi(_, X, Y), fail; true.
> 
> mercio :-
>      between(1,1000,_),
>      fuzzy(X), fuzzy(Y),
>      mercio(_, X, Y), fail; true.
> 
> The difficulty was to find a 100% Prolog compare/3
> that corresponds to SWI-Prolog. But you find a
> fresh implementation in 100% Prolog using a Union
> Find structure in the below:
> 
> % swi(-Atom, +Term, +Term)
> swi(C, X, Y) :-
>     swi(X, Y, C, [], _).
> 
> % swi( -Atom, +Term, +Term,+List, -List)
> swi(C, X, Y, L, R) :- compound(X), compound(Y), !,
>     sys_union_find(X, L, Z),
>     sys_union_find(Y, L, T),
>     swi_found(C, Z, T, L, R).
> swi(X, Y, C, L, L) :- compare(C, X, Y).
> 
> % swi_found(-Atom, +Term, +Term, +List, -List)
> swi_found(C, X, Y, L, L) :-
>     same_term(X, Y), !, C = (=).
> swi_found(C, X, Y, _, _) :-
>     functor(X, F, N),
>     functor(Y, G, M),
>     compare(D, N/F, M/G),
>     D \== (=), !, C = D.
> swi_found(C, X, Y, L, R) :-
>     X =.. [_|P],
>     Y =.. [_|Q],
>     foldl(swi(C), P, Q, [X-Y|L], R).
> 
> % sys_union_find(+Term, +List, -Term)
> sys_union_find(X, L, T) :-
>     member(Y-Z, L),
>     same_term(X, Y), !,
>     sys_union_find(Z, L, T).
> sys_union_find(X, _, X).

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Thread

Mercio’s Algorithm for Rational Tree Compare in Prolog Mild Shock <janburse@fastmail.fm> - 2025-08-04 02:54 +0200
  The Original Ganster (OG) of Gameification: IEEE 1044.1-1995 (Re: Mercio’s Algorithm for Rational Tree Compare in Prolog) Mild Shock <janburse@fastmail.fm> - 2025-08-04 13:50 +0200
    The Bitrot called Math Stack Exchange (Re: The Original Ganster (OG) of Gameification: IEEE 1044.1-1995) Mild Shock <janburse@fastmail.fm> - 2025-08-04 13:57 +0200
      I guess its back to Hopcroft and Karp (Re: The Bitrot called Math Stack Exchange) Mild Shock <janburse@fastmail.fm> - 2025-08-04 14:12 +0200
  Szpilrajn Theorem and Suzumura Consistency (Re: Mercio’s Algorithm for Rational Tree Compare in Prolog Mild Shock <janburse@fastmail.fm> - 2025-08-06 01:53 +0200
    The good thing is we have at least Mercio’s Algorithm (Re: Szpilrajn Theorem and Suzumura Consistency) Mild Shock <janburse@fastmail.fm> - 2025-08-06 08:09 +0200
      Hopcroft and Karp’s is just Contraction (Re: The good thing is we have at least Mercio’s Algorithm) Mild Shock <janburse@fastmail.fm> - 2025-08-06 08:16 +0200
        Re: Hopcroft and Karp’s is just Contraction (Re: The good thing is we have at least Mercio’s Algorithm) Mild Shock <janburse@fastmail.fm> - 2025-08-06 08:23 +0200
  Mercios decidability was already attested in 2012 (Re: Mercio’s Algorithm for Rational Tree Compare in Prolog) Mild Shock <janburse@fastmail.fm> - 2025-08-14 20:40 +0200
    Performance of Mercio’s Total Order (Re: Mercios decidability was already attested in 2012) Mild Shock <janburse@fastmail.fm> - 2025-08-15 23:51 +0200
      Fuzzy Testing is your Swiss Knife (Was: Performance of Mercio’s Total Order) Mild Shock <janburse@fastmail.fm> - 2025-08-15 23:54 +0200
        Yeah, we have another name! (Re: Fuzzy Testing is your Swiss Knife) Mild Shock <janburse@fastmail.fm> - 2025-08-16 12:40 +0200
          Monte Carlo sampling the frontier version (Re: Yeah, we have another name!) Mild Shock <janburse@fastmail.fm> - 2025-08-16 12:44 +0200
  An NPU could give 1000x more LIPS (Re: Mercio’s Algorithm for Rational Tree Compare in Prolog) Mild Shock <janburse@fastmail.fm> - 2025-11-27 14:23 +0100
    Zeus: A Language for Expressing Algorithms in Hardware (Re: Neural Network based dif/2 respectively (#\=)/2) Mild Shock <janburse@fastmail.fm> - 2025-11-27 15:02 +0100
    100% serious Giga Logical Inferences per Second (GLIPS) (Re: An NPU could give 1000x more LIPS (Re: Mercio’s Algorithm for Rational Tree Compare in Prolog) Mild Shock <janburse@fastmail.fm> - 2025-11-28 14:53 +0100

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