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* sort: extract partition from quicksort Extract the partition logic from quicksort into a macro. This allows to reuse the partition logic for, e.g., the quickselect algorithm. * sort: implement quickselect implement Hoare's selection algorithm (quickselect) on the basis of the already implemented quicksort. Quickselect allows to find the kth smallest element in a unordered list with an average time complexity of O(N) (worst case: O(N^2)). * add quicksort benchmark Create a top-level benchmarks folder. Add the benchmark implementation for the quicksort algorithm. Benchmarks can then be run in the same way as unit tests from the root folder with: c3c compile-benchmarks benchmarks/stdlib/sort
64 lines
779 B
Plaintext
64 lines
779 B
Plaintext
module sort_test @test;
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import std::sort;
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struct TestCase @local
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{
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int[] list;
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isz k;
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int want;
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}
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fn void! quickselect()
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{
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TestCase[] tcases = {
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{
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.list = {3, 4, 1},
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.k = 0,
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.want = 1,
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},
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{
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.list = {3, 4, 1},
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.k = 1,
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.want = 3,
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},
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{
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.list = {3, 4, 1},
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.k = 2,
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.want = 4,
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},
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{
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.list = {3, 2, 4, 1},
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.k = 1,
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.want = 2,
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},
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{
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.list = {3, 2, 1, 2},
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.k = 1,
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.want = 2,
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},
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{
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.list = {3, 2, 1, 2},
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.k = 2,
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.want = 2,
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},
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{
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.list = {3, 2, 1, 2},
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.k = 3,
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.want = 3,
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},
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};
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foreach (i, tc : tcases)
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{
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if (try got = sort::quickselect(tc.list, tc.k))
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{
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assert(got == tc.want, "got: %d, want %d", got, tc.want);
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}
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else
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{
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assert(false, "test %d failed", i);
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}
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}
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}
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