Frozen

Header-only library that provides 0 cost initialization for immutable containers, fixed-size containers, and various algorithms.

Frozen provides:

• immutable (a.k.a. frozen), constexpr-compatible versions of std::set, std::unordered_set, std::map and std::unordered_map.
• fixed-capacity, constinit-compatible versions of std::map and std::unordered_map with immutable, compile-time selected keys mapped to mutable values.
• 0-cost initialization version of std::search for frozen needles using Boyer-Moore or Knuth-Morris-Pratt algorithms.

The unordered_* containers are guaranteed perfect (a.k.a. no hash collision) and the extra storage is linear with respect to the number of keys.

Once initialized, the container keys cannot be updated, and in exchange, lookups are faster. And initialization is free when constexpr or constinit is used :-).

Stable Version

The Frozen library is pretty stable now, have been so for years, so:

1. The master version can be used as the default stable version.
2. It is in maintenance mode. I still accept commits that make the code cleaner | faster | more modern, but expect some latency in the review process.

Installation

Just copy the include/frozen directory somewhere and points to it using the -I flag. Alternatively, using CMake:

> mkdir build
> cd build
> cmake -D CMAKE_BUILD_TYPE=Release ..
> make install

Installation via CMake populates configuration files into the /usr/local/share directory which can be consumed by CMake's find_package instrinsic function.

Requirements

A C++ compiler that supports C++14. Clang version 5 is a good pick, GCC version 6 lags behind in terms of constexpr compilation time (At least on my setup), but compiles correctly. Visual Studio 2017 also works correctly!

Note that gcc 5 isn't supported. (Here's an old compat branch where a small amount of stuff was ported.)

Usage

Compiled with -std=c++14 flag:

#include <frozen/set.h>

constexpr frozen::set<int, 4> some_ints = {1,2,3,5};

constexpr bool letitgo = some_ints.count(8);

extern int n;
bool letitgoooooo = some_ints.count(n);

As the constructor and some methods are constexpr, it's also possible to write weird stuff like:

#include <frozen/set.h>

template<std::size_t N>
std::enable_if_t< frozen::set<int, 3>{{1,11,111}}.count(N), int> foo();

String support is built-in:

#include <frozen/unordered_map.h>
#include <frozen/string.h>

constexpr frozen::unordered_map<frozen::string, int, 2> olaf = {
    {"19", 19},
    {"31", 31},
};
constexpr auto val = olaf.at("19");

The associative containers have different functionality with and without constexpr. With constexpr, frozen maps have immutable keys and values. Without constexpr, the values can be updated in runtime (the keys, however, remain immutable):

#include <frozen/unordered_map.h>
#include <frozen/string.h>

static constinit frozen::unordered_map<frozen::string, frozen::string, 2> voice = {
    {"Anna", "???"},
    {"Elsa", "???"}
};

int main() {
    voice.at("Anna") = "Kristen";
    voice.at("Elsa") = "Idina";
}

You may also prefer a slightly more DRY initialization syntax:

#include <frozen/set.h>

constexpr auto some_ints = frozen::make_set<int>({1,2,3,5});

There are similar make_X functions for all frozen containers.

Exception Handling

For compatibility with STL's API, Frozen may eventually throw exceptions, as in frozen::map::at. If you build your code without exception support, or define the FROZEN_NO_EXCEPTIONS macro variable, they will be turned into an std::abort.

Extending

Just like the regular C++14 container, you can specialize the hash function, the key equality comparator for unordered_* containers, and the comparison functions for the ordered version.

It's also possible to specialize the frozen::elsa structure used for hashing. Note that unlike std::hash, the hasher also takes a seed in addition to the value being hashed.

template <class T> struct elsa {
  // in case of collisions, different seeds are tried
  constexpr std::size_t operator()(T const &value, std::size_t seed) const;
};

Ideally, the hash function should have nice statistical properties like pairwise-independence:

If x and y are different values, the chance that elsa<T>{}(x, seed) == elsa<T>{}(y, seed) should be very low for a random value of seed.

Note that frozen always ultimately produces a perfect hash function, and you will always have O(1) lookup with frozen. It's just that if the input hasher performs poorly, the search will take longer and your project will take longer to compile.

Troubleshooting

If you hit a message like this:

[...]
note: constexpr evaluation hit maximum step limit; possible infinite loop?

Then either you've got a very big container and you should increase Clang's thresholds, using -fconstexpr-steps=1000000000 for instance, or the hash functions used by frozen do not suit your data, and you should change them, as in the following:

struct olaf {
  constexpr std::size_t operator()(frozen::string const &value, std::size_t seed) const { return seed ^ value[0];}
};

constexpr frozen::unordered_set<frozen::string, 2, olaf/*custom hash*/> hans = { "a", "b" };

Tests and Benchmarks

Using hand-written Makefiles crafted with love and care:

> # running tests
> make -C tests check
> # running benchmarks
> make -C benchmarks GOOGLE_BENCHMARK_PREFIX=<GOOGLE-BENCHMARK_INSTALL_DIR>

Using CMake to generate a static configuration build system:

> mkdir build
> cd build
> cmake -D CMAKE_BUILD_TYPE=Release \
        -D frozen.benchmark=ON \
        -G <"Unix Makefiles" or "Ninja"> ..
> # building the tests and benchmarks...
> make                               # ... with make
> ninja                              # ... with ninja
> cmake --build .                    # ... with cmake
> # running the tests...
> make test                          # ... with make
> ninja test                         # ... with ninja
> cmake --build . --target test      # ... with cmake
> ctest                              # ... with ctest
> # running the benchmarks...
> make benchmark                     # ... with make
> ninja benchmark                    # ... with ninja
> cmake --build . --target benchmark # ... with cmake

Using CMake to generate an IDE build system with test and benchmark targets

> mkdir build
> cd build
> cmake -D frozen.benchmark=ON -G <"Xcode" or "Visual Studio 15 2017"> ..
> # using cmake to drive the IDE build, test, and benchmark
> cmake --build . --config Release
> cmake --build . --target test
> cmake --build . --target benchmark

Credits

The perfect hashing is strongly inspired by the blog post Throw away the keys: Easy, Minimal Perfect Hashing.

Thanks a lot to Jérôme Dumesnil for his high-quality reviews, and to Chris Beck for his contributions on perfect hashing.

Contact

Serge sans Paille <serge.guelton@telecom-bretagne.eu>