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Estimated hours taken: 2 The following change was made by Peter Moulder <pmoulder@csse.monash.edu.au>. extras/quickcheck/tutes/*.html: Many HTML fixes. (Previously there were enough problems that it made more sense to read them as plain text files than with a web browser.) The files now pass through weblint (cleanly) and tidy (only `table lacks "summary" attribute' warnings remain). A small number of textual changes, and also a couple of <!-- XXX ... --> comments where I suspect the text should be changed.
151 lines
4.3 KiB
HTML
151 lines
4.3 KiB
HTML
<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 3.2//EN">
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<html>
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<head>
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<title>QuickCheck</title>
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</head>
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<body>
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<p>
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Files:
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<a href="use81.m">use81.m</a>
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<br>
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<a href="index.html">Back to main</a>
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<h1>QuickCheck Tutorial 8</h1>
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<h2>Generators - Random Functions</h2>
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<p>
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Currently Quickcheck only has default generators for random functions that
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have 0 to 10 inputs, 1 output, and is in forward mode. This generated function
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can run on any type of inputs, but the output must be a type for which there is
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a custom/default generator.
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<p>
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The output may be indepedent of zero or more of the input arguments.
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By this we mean that the value of an input argument may have no bearing upon the
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calculation of the output. There is a 5% chance per argument of this occurring.
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<p>
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An example (use81.m)
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<table border=0 width="100%" bgcolor="#eeeee0"><tr><td><pre>
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:- module use81.
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:- interface.
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:- use_module io.
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:- pred main(io__state, io__state).
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:- mode main(di, uo) is det.
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%---------------------------------------------------------------------------%
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:- implementation.
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:- import_module int, char, std_util, list.
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:- import_module qcheck, rnd.
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:- type strange(T1, T2)
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---> wierd(T1, T2, T1).
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main -->
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qcheck(qcheck__f(prop1), "prop1", 1000, [], []),
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qcheck(qcheck__f(prop2), "prop2", 1000, [], []),
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qcheck(qcheck__f(prop3), "prop3", 1000, [], []),
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qcheck(qcheck__f(prop4), "prop4", 1000, [], []).
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:- func prop1( func(strange(int, char), int) = list(int) ) = property.
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:- mode prop1( in( func(in,in)=out is det) ) = out is det.
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prop1(FFF) =
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FFF(wierd(1, '0', 2), 999) `===` FFF(wierd(1, '0', 2), 999).
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:- func prop2(func(strange(int, char), int) = list(int)) = property.
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prop2(FFF) =
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(if FFF(wierd(1, '0', 2), 999) = FFF(wierd(1, '0', 2), 888)
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then
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[ info(univ("equal")) | [yes] ]
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else
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[ info(univ("not equal")) | [yes] ]
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).
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:- func prop3(func(int) = int) = property.
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prop3(FFF) =
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(if FFF(1) = FFF(0)
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then
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[ info(univ("equal")) | [yes] ]
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else
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[ info(univ("not equal")) | [yes] ]
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).
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:- func prop4(func(int, int) = int) = property.
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prop4(FFF) =
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(if FFF(101, 10) = FFF(11, 15)
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then
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[ info(univ("equal")) | [yes] ]
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else
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[ info(univ("not equal")) | [yes] ]
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).
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</pre></tr></table>
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<p>
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A sample output:
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<pre>
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Test Description : prop1
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Number of test cases that succeeded : 1000
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Number of trivial tests : 0
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Number of tests cases which failed the pre-condition : 0
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Distributions of selected argument(s) :
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Test Description : prop2
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Number of test cases that succeeded : 1000
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Number of trivial tests : 0
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Number of tests cases which failed the pre-condition : 0
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Distributions of selected argument(s) :
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256 "equal"
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744 "not equal"
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Test Description : prop3
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Number of test cases that succeeded : 1000
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Number of trivial tests : 0
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Number of tests cases which failed the pre-condition : 0
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Distributions of selected argument(s) :
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60 "equal"
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940 "not equal"
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Test Description : prop4
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Number of test cases that succeeded : 1000
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Number of trivial tests : 0
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Number of tests cases which failed the pre-condition : 0
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Distributions of selected argument(s) :
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1 "equal"
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999 "not equal"
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</pre>
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<p>
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prop1/1 just shows that given the same input, the output of the
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sample function is the same.
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<p>
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prop3/1 shows that given different input, the random function will
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usually give different output (940/1000 cases). For the rest 60/1000
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cases, either the output is independent of input (most likely). Or
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it just so happens the output is the same for FFF(0) and FFF(1).
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(Note 60/1000 is roughly 5%)
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<p>
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prop2/1 shows 256/1000 cases shows that the random function returned the
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same output for different inputs. The real differenct between prop3/1 and
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prop2/1 is that the output of prop2/1 is list(int), which means the chance
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of generating [] is high (50% chance), and that's where 256/1000 cases come
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from.
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<p>
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prop4/1's random function takes two inputs, the chance of both inputs being
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independent of output is less compare to a random function which only takes
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1 input. e.g.:<br>
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FFF(in) = out, out independent of in is 5% chance<br>
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FFF(in, in) = out, out independent of in is 5% * 5% chance
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</body>
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</html>
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