summaryrefslogtreecommitdiffstats
path: root/vendor/proptest/src/strategy/shuffle.rs
blob: b94a73c3bfd957d21e4bbadebd99bcc79432f3de (plain)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
//-
// Copyright 2017 Jason Lingle
//
// Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
// http://www.apache.org/licenses/LICENSE-2.0> or the MIT license
// <LICENSE-MIT or http://opensource.org/licenses/MIT>, at your
// option. This file may not be copied, modified, or distributed
// except according to those terms.

use crate::std_facade::{Cell, Vec, VecDeque};

use rand::Rng;

use crate::num;
use crate::strategy::traits::*;
use crate::test_runner::*;

/// `Strategy` shuffle adaptor.
///
/// See `Strategy::prop_shuffle()`.
#[derive(Clone, Debug)]
#[must_use = "strategies do nothing unless used"]
pub struct Shuffle<S>(pub(super) S);

/// A value which can be used with the `prop_shuffle` combinator.
///
/// This is not a general-purpose trait. Its methods are prefixed with
/// `shuffle_` to avoid the compiler suggesting them or this trait as
/// corrections in errors.
pub trait Shuffleable {
    /// Return the length of this collection.
    fn shuffle_len(&self) -> usize;
    /// Swap the elements at the given indices.
    fn shuffle_swap(&mut self, a: usize, b: usize);
}

macro_rules! shuffleable {
    ($($t:tt)*) => {
        impl<T> Shuffleable for $($t)* {
            fn shuffle_len(&self) -> usize {
                self.len()
            }

            fn shuffle_swap(&mut self, a: usize, b: usize) {
                self.swap(a, b);
            }
        }
    }
}

shuffleable!([T]);
shuffleable!(Vec<T>);
shuffleable!(VecDeque<T>);
// Zero- and 1-length arrays aren't usefully shuffleable, but are included to
// simplify external macros that may try to use them anyway.
shuffleable!([T; 0]);
shuffleable!([T; 1]);
shuffleable!([T; 2]);
shuffleable!([T; 3]);
shuffleable!([T; 4]);
shuffleable!([T; 5]);
shuffleable!([T; 6]);
shuffleable!([T; 7]);
shuffleable!([T; 8]);
shuffleable!([T; 9]);
shuffleable!([T; 10]);
shuffleable!([T; 11]);
shuffleable!([T; 12]);
shuffleable!([T; 13]);
shuffleable!([T; 14]);
shuffleable!([T; 15]);
shuffleable!([T; 16]);
shuffleable!([T; 17]);
shuffleable!([T; 18]);
shuffleable!([T; 19]);
shuffleable!([T; 20]);
shuffleable!([T; 21]);
shuffleable!([T; 22]);
shuffleable!([T; 23]);
shuffleable!([T; 24]);
shuffleable!([T; 25]);
shuffleable!([T; 26]);
shuffleable!([T; 27]);
shuffleable!([T; 28]);
shuffleable!([T; 29]);
shuffleable!([T; 30]);
shuffleable!([T; 31]);
shuffleable!([T; 32]);

impl<S: Strategy> Strategy for Shuffle<S>
where
    S::Value: Shuffleable,
{
    type Tree = ShuffleValueTree<S::Tree>;
    type Value = S::Value;

    fn new_tree(&self, runner: &mut TestRunner) -> NewTree<Self> {
        let rng = runner.new_rng();

        self.0.new_tree(runner).map(|inner| ShuffleValueTree {
            inner,
            rng,
            dist: Cell::new(None),
            simplifying_inner: false,
        })
    }
}

/// `ValueTree` shuffling adaptor.
///
/// See `Strategy::prop_shuffle()`.
#[derive(Clone, Debug)]
pub struct ShuffleValueTree<V> {
    inner: V,
    rng: TestRng,
    /// The maximum amount to move any one element during shuffling.
    ///
    /// This is `Cell` since we can't determine the bounds of the value until
    /// the first call to `current()`. (We technically _could_ by generating a
    /// value in `new_tree` and checking its length, but that would be a 100%
    /// slowdown.)
    dist: Cell<Option<num::usize::BinarySearch>>,
    /// Whether we've started simplifying `inner`. After this point, we can no
    /// longer simplify or complicate `dist`.
    simplifying_inner: bool,
}

impl<V: ValueTree> ShuffleValueTree<V>
where
    V::Value: Shuffleable,
{
    fn init_dist(&self, dflt: usize) -> usize {
        if self.dist.get().is_none() {
            self.dist.set(Some(num::usize::BinarySearch::new(dflt)));
        }

        self.dist.get().unwrap().current()
    }

    fn force_init_dist(&self) {
        if self.dist.get().is_none() {
            self.init_dist(self.current().shuffle_len());
        }
    }
}

impl<V: ValueTree> ValueTree for ShuffleValueTree<V>
where
    V::Value: Shuffleable,
{
    type Value = V::Value;

    fn current(&self) -> V::Value {
        let mut value = self.inner.current();
        let len = value.shuffle_len();
        // The maximum distance to swap elements. This could be larger than
        // `value` if `value` has reduced size during shrinking; that's OK,
        // since we only use this to filter swaps.
        let max_swap = self.init_dist(len);

        // If empty collection or all swaps will be filtered out, there's
        // nothing to shuffle.
        if 0 == len || 0 == max_swap {
            return value;
        }

        let mut rng = self.rng.clone();

        for start_index in 0..len - 1 {
            // Determine the other index to be swapped, then skip the swap if
            // it is too far. This ordering is critical, as it ensures that we
            // generate the same sequence of random numbers every time.
            let end_index = rng.gen_range(start_index..len);
            if end_index - start_index <= max_swap {
                value.shuffle_swap(start_index, end_index);
            }
        }

        value
    }

    fn simplify(&mut self) -> bool {
        if self.simplifying_inner {
            self.inner.simplify()
        } else {
            // Ensure that we've initialised `dist` to *something* to give
            // consistent non-panicking behaviour even if called in an
            // unexpected sequence.
            self.force_init_dist();
            if self.dist.get_mut().as_mut().unwrap().simplify() {
                true
            } else {
                self.simplifying_inner = true;
                self.inner.simplify()
            }
        }
    }

    fn complicate(&mut self) -> bool {
        if self.simplifying_inner {
            self.inner.complicate()
        } else {
            self.force_init_dist();
            self.dist.get_mut().as_mut().unwrap().complicate()
        }
    }
}

#[cfg(test)]
mod test {
    use std::borrow::ToOwned;
    use std::collections::HashSet;
    use std::i32;

    use super::*;
    use crate::collection;
    use crate::strategy::just::Just;

    static VALUES: &'static [i32] = &[
        0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19,
    ];

    #[test]
    fn generates_different_permutations() {
        let mut runner = TestRunner::default();
        let mut seen = HashSet::<Vec<i32>>::new();

        let input = Just(VALUES.to_owned()).prop_shuffle();

        for _ in 0..1024 {
            let mut value = input.new_tree(&mut runner).unwrap().current();

            assert!(
                seen.insert(value.clone()),
                "Value {:?} generated more than once",
                value
            );

            value.sort();
            assert_eq!(VALUES, &value[..]);
        }
    }

    #[test]
    fn simplify_reduces_shuffle_amount() {
        let mut runner = TestRunner::default();

        let input = Just(VALUES.to_owned()).prop_shuffle();
        for _ in 0..1024 {
            let mut value = input.new_tree(&mut runner).unwrap();

            let mut prev_dist = i32::MAX;
            loop {
                let v = value.current();
                // Compute the "shuffle distance" by summing the absolute
                // distance of each element's displacement.
                let mut dist = 0;
                for (ix, &nominal) in v.iter().enumerate() {
                    dist += (nominal - ix as i32).abs();
                }

                assert!(
                    dist <= prev_dist,
                    "dist = {}, prev_dist = {}",
                    dist,
                    prev_dist
                );

                prev_dist = dist;
                if !value.simplify() {
                    break;
                }
            }

            // When fully simplified, the result is in the original order.
            assert_eq!(0, prev_dist);
        }
    }

    #[test]
    fn simplify_complicate_contract_upheld() {
        check_strategy_sanity(
            collection::vec(0i32..1000, 5..10).prop_shuffle(),
            None,
        );
    }
}