Product Promotion
0x5a.live
for different kinds of informations and explorations.
GitHub - Morwenn/cpp-sort: Sorting algorithms & related tools for C++14
Sorting algorithms & related tools for C++14. Contribute to Morwenn/cpp-sort development by creating an account on GitHub.
Visit SiteGitHub - Morwenn/cpp-sort: Sorting algorithms & related tools for C++14
Sorting algorithms & related tools for C++14. Contribute to Morwenn/cpp-sort development by creating an account on GitHub.
Powered by 0x5a.live 💗
It would be nice if only one or two of the sorting methods would dominate all of the others, regardless of application or the computer being used. But in fact, each method has its own peculiar virtues. [...] Thus we find that nearly all of the algorithms deserve to be remembered, since there are some applications in which they turn out to be best. — Donald Knuth, The Art Of Computer Programming, Volume 3
cpp-sort is a generic C++14 header-only sorting library. It revolves around one main generic sorting interface and provides several small tools to pick and/or design sorting algorithms. Using its basic sorting features should be trivial enough:
#include <array>
#include <iostream>
#include <cpp-sort/sorters/smooth_sorter.h>
int main()
{
std::array<int, 5> arr = { 5, 8, 3, 2, 9 };
cppsort::smooth_sort(arr);
// prints 2 3 5 8 9
for (int val: arr) {
std::cout << val << ' ';
}
}
The main features & the extra features
cpp-sort provides a full set of sorting-related features. Here are the main building blocks of the library:
- Every sorting algorithm exists as a function object called a sorter
- Sorters can be wrapped in sorter adapters to augment their behaviour
- The library provides a sorter facade to easily build sorters
- Fixed-size sorters can be used to efficiently sort tiny fixed-size collections
- Measures of presortedness can be used to evaluate the disorder in a collection
Here is a more complete example of what can be done with the library:
#include <algorithm>
#include <cassert>
#include <forward_list>
#include <functional>
#include <vector>
#include <cpp-sort/adapters.h>
#include <cpp-sort/sorters.h>
int main()
{
struct wrapper { int value; };
std::forward_list<wrapper> li = { {5}, {8}, {3}, {2}, {9} };
std::vector<wrapper> vec = { {5}, {8}, {3}, {2}, {9} };
// When used, this sorter will use a pattern-defeating quicksort
// to sort random-access collections, and a mergesort otherwise
cppsort::hybrid_adapter<
cppsort::pdq_sorter,
cppsort::merge_sorter
> sorter;
// Sort li and vec in reverse order using their value member
sorter(li, std::greater<>{}, &wrapper::value);
sorter(vec, std::greater<>{}, &wrapper::value);
assert(std::equal(
li.begin(), li.end(),
vec.begin(), vec.end(),
[](const auto& lhs, const auto& rhs) { return lhs.value == rhs.value; }
));
}
Even when the sorting functions are used without the extra features, they still provide some interesting guarantees (ideas often taken from the Ranges TS):
- They provide both an iterator and a range interface
- When possible, they accept a custom comparator parameter
- Most of them accept a projection parameter
- They correctly handle proxy iterators with
iter_swap
anditer_move
- They also work when iterators don't provide post-incrementation nor post-decrementation
- The value types of the collections to be sorted need not be default-constructible
- The value types of the collections to be sorted need not be copyable (only movable)
- Stateless sorters can be converted to a function pointer for each overloaded
operator()
- Sorters are function objects: they can directly be passed as "overload sets" to other functions
You can read more about all the available tools and find some tutorials about using and extending cpp-sort in the wiki.
Benchmarks
The following graph has been generated with a script found in the benchmarks
directory. It shows the time needed for heap_sort
to sort one
million elements without being adapted, then when it is adapted with either
drop_merge_adapter
or split_adapter
.
As can be seen above, wrapping heap_sort
with either of the adapters makes it
adaptive to the number of inversions in a non-intrusive
manner. The algorithms used to adapt it have different pros and cons, it is up
to you to use either.
This benchmark is mostly there to show the possibilities offered by the library. You can find more such commented benchmarks in the dedicated wiki page.
Compiler support & tooling
cpp-sort requires C++14 support, and should work with the following compilers:
- g++7 or more recent.
- clang++6.0 or more recent (with both libstdc++ and libc++).
- The versions of MinGW-w64 and AppleClang equivalent to the compilers mentioned above.
- Visual Studio 2019 version 16.8.3 or more recent, only with
/permissive-
. A few features are unavailable. - clang-cl corresponding the the Visual Studio version above.
The compilers listed above are the ones used by the CI pipeline, and the library is also tested with the most recent versions of those compilers on a regular basis. All the other compiler versions in-between are untested, but should also work. Feel free to open an issue if it isn't the case.
The features in the library might differ depending on the C++ version used and on the compiler extensions enabled. Those changes are documented in the wiki.
The main repository contains additional support for standard tooling such as CMake or Conan. You can read more about those in the wiki.
Thanks
I got a new car. I just need to put it together. They’re easier to steal piece by piece. — Jarod Kintz, $3.33
Even though some parts of the library are original research and some others correspond to custom and rather naive implementations of standard sorting algorithms, cpp-sort also reuses a great deal of code and ideas from open-source projects, often altered to integrate seamlessly into the library. Here is a list of the external resources used to create this library. I hope that the many different licenses are compatible. If it is not the case, please contact me (or submit an issue) and we will see what can be done about it:
-
Some of the algorithms used by
insertion_sorter
andpdq_sorter
come from Orson Peters' pattern-defeating quicksort. Some parts of the benchmarks come from there as well. -
The algorithm used by
tim_sorter
comes from Goro Fuji's (gfx) implementation of a Timsort. -
The three algorithms used by
spread_sorter
come from Steven Ross Boost.Sort module. -
The algorithm used by
d_ary_spread_sorter
comes from Tim Blechmann's Boost.Heap module. -
The algorithm used by
spin_sorter
comes from the eponymous algorithm implemented in Boost.Sort. by Francisco Jose Tapia. -
utility::as_function
,utility::static_const
, and several projection-enhanced helper algorithms come from Eric Niebler's Range v3 library. Several ideas such as proxy iterators, customization points and projections, as well as a few other utility functions also come from that library or from the related articles and standard C++ proposals. -
The algorithm used by
ska_sorter
comes from Malte Skarupke's implementation of his own ska_sort algorithm. -
The algorithm used by
drop_merge_sorter
comes from Adrian Wielgosik C++ reimplementation of Emil Ernerfeldt's drop-merge sort. -
Many enhanced standard algorithms are directly adapted from their counterparts in libc++, enhanced to handle both projections and proxy iterators.
-
The library internally uses an
inplace_merge
function that works with forward iterators. Its implementation uses a merge algorithm proposed by Dudziński and Dydek, and implemented by Alexander Stepanov and Paul McJones in their book Elements of Programming. -
The
inplace_merge
overload for random-access iterators uses the Symmerge algorithm proposed by Pok-Son Kim and Arne Kutzner in Stable Minimum Storage Merging by Symmetric Comparisons when there isn't enough memory available to perform an out-of-place merge. -
The implementation of Dijkstra's smoothsort used by
smooth_sorter
has been directly adapted from Keith Schwarz's implementation of the algorithm. -
The algorithm used by
wiki_sorter
has been adapted from BonzaiThePenguin's WikiSort. -
The algorithm used by
grail_sorter
has been adapted from Mrrl's GrailSort. -
The algorithm used by
indirect_adapter
with forward or bidirectional iterators is a slightly modified version of Matthew Bentley's indiesort. -
The implementation of the random-access overload of
nth_element
used by some of the algorithms comes from Danila Kutenin's miniselect library and uses Andrei Alexandrescu's AdaptiveQuickselect algorithm. -
The sorting networks used by
sorting_network_sorter
all come from this list maintained by Bert Dobbelaere. The page has references to the sources of all of the sorting networks it lists. -
Some of the optimizations used by
sorting_network_sorter
come from this discussion on StackOverflow and are backed by the article Applying Sorting Networks to Synthesize Optimized Sorting Libraries. -
The test suite reimplements random number algorithms originally found in the following places:
-
The LaTeX scripts used to draw the sorting networks are modified versions of kaayy's
sortingnetwork.tex
, slightly adapted to be 0-based and draw the network from top to bottom. -
The CMake tools embedded in the projects include scripts from RWTH-HPC/CMake-codecov and Crascit/DownloadProject.
-
Some of the benchmarks use a colorblind-friendly palette developed by Thøger Rivera-Thorsen.
C++ Programming Resources
are all listed below.
Made with ❤️
to provide different kinds of informations and resources.