Tag Archives: C++11

Higher-Order functions in C++

The other day, I was writing some C++ and found that I was thinking about how to manipulate the data I had as if I was writing F#. It would have been convenient to turn a std::map into an array of tuples, which I could do in F# like this:

let f (xs : map<int,string) =
  let xs = xs |> Map.toArray
  // now treat xs as array of tuples...

There’s no function in STL to do this off the bat – instead, you have to roll your own (not that it’s much code, but it does break your through processes if you have to stop to code this sort of thing every time).

Of course, this is just one of many helpful F# higher-order functions that are provided in the F# Map module – and there are counterparts for each of the collection classes i.e. Array, Set, List etc. In C++, the nearest equivalent is the STL which provides both collection classes and a number of algorithms that operate on them. Better still, from C++11 onwards we have lambdas, which make using STL algorithms much easier. Even so, in most cases, the F# operations seem much more tailored to the sort of data transformation I see at work – our codebase is littered with map/filter/fold operations as people transform/select and accumulate data. Conversely, our C++ codebase is full of … for loops, evidence in my eyes that STL algorithms aren’t as immediately applicable. In fact, the ease of use of higher-order functions was one of the reasons that F# was quickly adopted in my workplace (along with immutability, strong-typing, conciseness, type inference and syntax checking).

I’ve written one-to-one C++ equivalents of the F# module functions that I use the most for Map and Vector – see below. Interestingly, I found that I really did have to ‘engage brain’ to write some of these, particularly Map.filter. For that one, you can’t use the erase-remove idiom because map keys are both const and strictly ordered (whereas for Vector, erase-remove_if implements filter neatly). A library of functions as per my code below would definitely be a productivity boost.

First, I’ve factored some common utilities into namespace Collection:

namespace MusingStudio
{
    namespace Collection
    {
        template <typename C, typename F>
        C& filter( C& collection, F keep_predicate )
        {
            auto erase_predicate = [&pred=keep_predicate]( auto&& x ){ return !pred( std::forward<decltype(x)>(x) ); };
            collection.erase( std::remove_if( collection.begin(), collection.end(), erase_predicate ), collection.end() );
            return collection;
        }
        
        // This form of filter always takes a copy and applies the filter to it
        // - sometimes you want to preserve the original collection
        template <typename C, typename F>
        C filter_copy( const C& collection, F keep_predicate )
        {
            C target;
            std::copy_if( collection.begin(), collection.end(), std::inserter( target, target.end() ), keep_predicate );
            return target;
        }
        
        template <typename C, typename F, typename A>
        A fold( const C& items, F f, A&& init )
        {
            A acc{ std::forward<A>(init) };
            for ( const auto& item : items )
            {
                f( acc, item );
            }
            return acc;
        }
                
        // F( T ) -> T and collection C is mutated
        template <typename C, typename F>
        C& transform( C& items, F f )
        {
            for ( auto& t : items )
            {
                t = f( t );
            }
            
            return items;
        }

    }
}

Next, here are the higher-order functions that I use for Map:

namespace MusingStudio
{
    namespace Map
    {
        // filter_copy takes a copy of the original collection then applies the filter
        template< typename K, typename V, typename F>
        std::map<K,V> filter_copy( const std::map<K,V>& items, F predicate )
        {
            return Collection::filter_copy( items, predicate );
        }
        
        template< typename K, typename V, typename F>
        std::map<K,V>& filter( std::map<K,V>& items, F predicate )
        {
            // NB the erase-remove_if idiom does not work for std::map
            // because the nodes must remain ordered by key.  This is enforced
            // by std::map<K,V> holding keys as const K.  So any assignment
            // to the key (to effecfively re-order the binary tree) fails to compile.
            // http://stackoverflow.com/questions/9515357/map-lambda-remove-if
            
            // instead, manually iterate over the collection, erasing items
            // for which predicate() returns false
            for ( auto it = items.begin(), itEnd = items.end(); it != itEnd; )
            {
                if ( predicate( *it ) )
                {
                    ++it; // ok - keep this item
                }
                else
                {
                    it = items.erase( it );
                }
            }
            
            return items;
        }
        
        template <typename K, typename V>
        auto to_vector( const std::map<K,V>& collection )
        {
            std::vector< std::pair<K,V> > items;
            
            for ( const auto& item : collection )
            {
                items.push_back( std::make_pair( item.first, item.second ) );
            }
            
            return items;
        }
        
        template <typename K, typename V>
        auto keys( const std::map<K,V>& collection )
        {
            std::set< K > items;
            
            for ( const auto& item : collection )
            {
                items.insert( item.first );
            }
            
            return items;
        }
        
        template <typename K, typename V>
        auto values( const std::map<K,V>& collection )
        {
            std::vector< V > items;
            
            for ( const auto& item : collection )
            {
                items.push_back( item.second );
            }
            
            return items;
        }
        
        template<typename K, typename V, typename F, typename A>
        A fold( const std::map<K,V>& items, F f, A&& init )
        {
            return Collection::fold( items, f, std::forward<A>(init) );
        }
        
        // F( std::pair<K,V> ) -> std::pair< L, U >
        // Construct a new std::map<L,U> mapping from (K,V) to (L,U)
        template <typename K, typename V, typename F>
        auto map( const std::map<K,V>& items, F f )
        {
            using KVP = typename std::map<K,V>::value_type;
            using RVP = decltype( f( KVP() ) );
            
            std::map< decltype( RVP().first ), decltype( RVP().second ) > result;
            
            for ( const KVP& kvp : items )
            {
                result.insert( f( kvp ) );
            }
            
            return result;
        }
        
        // F( K, V ) -> V and std::map<K,V> is mutated
        template <typename K, typename V, typename F>
        std::map<K,V>& transform( std::map<K,V>& items, F f )
        {
            using KVP = typename std::map<K,V>::value_type;
            
            for ( const KVP& kvp : items )
            {
                items[kvp.first] = f( kvp.first, kvp.second );
            }
            
            return items;
        }
    }
}

And here are the higher-order functions that I use for Vector:

namespace MusingStudio
{
    namespace Vector
    {
        template< typename T, typename F>
        std::vector<T>& filter( std::vector<T>& items, F predicate )
        {
            Collection::filter( items, predicate );
            return items;
        }
        
        template< typename T, typename F>
        std::vector<T> filter_copy( const std::vector<T>& items, F predicate )
        {
            return Collection::filter_copy( items, predicate );
        }
        
        // Requires F to have signature void( A&, T )
        template< typename T, typename F, typename A>
        A fold( const std::vector<T>& items, F f, A&& init )
        {
            return Collection::fold( items, f, std::forward<A>(init) );
        }
        
        template< typename T, typename P = std::less<T> >
        std::vector<T>& sort( std::vector<T>& items, P compare = P() )
        {
            std::sort( items.begin(), items.end(), compare );
            return items;
        }
        
        template< typename T, typename P = std::less<T> >
        std::vector<T> sort_copy( const std::vector<T>& items, P compare = P() )
        {
            std::vector<T> result( items );
            std::sort( result.begin(), result.end(), compare );
            return result;
        }
        
        // F( T ) -> U, construct a new vector<U>, mapping from T to U
        template <typename T, typename F>
        auto map( const std::vector<T>& items, F f )
        {
            using U = decltype( f(T()) );
            
            std::vector< U > result;
            std::transform( items.begin(), items.end(), std::inserter( result, result.end() ), f );
            return result;
        }
        
        // F( T ) -> T and std::vector<T> is mutated
        template <typename T, typename F>
        std::vector<T>& transform( std::vector<T>& items, F f )
        {
            return Collection::transform( items, f );
        }
    }
}

Here are some unit tests that show how much easier it is to use the Map/Vector functions instead of going directly to STL – I’d argue that this code is comparable to F# for conciseness (although F# code would still benefit from pipelining subsequent operations).

#include <iostream>

#include <gmock/gmock.h>
#include <Vector.hpp>
#include <Map.hpp>

using namespace testing;
using namespace MusingStudio;

TEST( Map, to_vector )
{
    using Mapped = std::map<int, std::string>;
    using Tuples = std::vector<std::pair<int,std::string> >;
    
    Mapped items{ { 1, "Hi" }, { 2, "Bye" } };
    
    EXPECT_EQ( (Tuples{ { 1, "Hi" }, { 2, "Bye" } }), 
      Map::to_vector( items ) );
}

TEST( Map, keys )
{
    using Mapped = std::map<int, std::string>;
    using Keys = std::set<int>;
    
    Mapped items{ { 1, "Hi" }, { 2, "Bye" } };
    
    EXPECT_EQ( (Keys{ 1, 2 }), 
      Map::keys( items ) );
}

TEST( Map, values )
{
    using Mapped = std::map<int, std::string>;
    using Values = std::vector<std::string>;
    
    Mapped items{ { 1, "Hi" }, { 2, "Bye" } };
    
    EXPECT_EQ( (Values{ "Hi", "Bye" }), 
      Map::values( items ) );
}

TEST( Map, filter )
{
    using Mapped = std::map<int, int>;
    
    Mapped items{ {1,1}, {2,4}, {3,9}, {4,16} };
    
    Mapped even_keys{ {2,4},{4,16} };
    auto lambda = []( const auto& keyvaluepair ){ return keyvaluepair.first % 2 == 0; };
    
    // Map::filter will mutate parameter 'items'
    EXPECT_EQ( even_keys, 
      Map::filter( items, lambda ) );
    EXPECT_EQ( 2, items.size() );
}

TEST( Map, filter_copy )
{
    using Mapped = std::map<int, int>;
    
    Mapped items{ {1,1}, {2,4}, {3,9}, {4,16} };
    
    Mapped even_keys{ {2,4},{4,16} };
    auto lambda = []( const auto& keyvaluepair ){ return keyvaluepair.first % 2 == 0; };
    
    // Map::filter_copy creates a copy, so parameter 'items' is untouched
    EXPECT_EQ( even_keys, 
      Map::filter_copy( items, lambda ) );
    EXPECT_EQ( 4, items.size() );
}

TEST( Map, fold )
{
    using Mapped = std::map<int, int>;
    
    Mapped items{ {1,2}, {3,4}, {5,6} };
    
    // Map::fold takes F( A&, pair<K,V> ) -> void
    EXPECT_EQ( 21, 
      Map::fold( items, 
        []( int& acc, const auto& kvp ){ acc += kvp.first + kvp.second; }, 0 ) );
}

TEST( Map, transform_mutable_values_only )
{
    using Transformed = std::map<int, int>;

    // Map::transform over the values, mutating them
    // Takes F(K,V) -> V i.e. the type of the return value must be V
    // "items" must be a named variable because parameter is non-const
    // (we will mutate it)
    Transformed items = { {1,1}, {2,2}, {3,3} };
    
    EXPECT_EQ( (Transformed{ {1,1}, {2,4}, {3,9} }),
      Map::transform( items, 
        []( int _, int v ){ return v*v; } ) );
}

TEST( Map, map_keys_and_values )
{
    using Mapped = std::map<int,double>;
    
    // Map::map over the pairs<key,value>
    // Takes F( pair<K,V> ) -> pair<K',V'> 
    // i.e. both key and value types can change
    auto lambda =
        []( const auto& kvp )
        {
            return std::make_pair( kvp.first + kvp.second,
                                   (double)kvp.second / (double)kvp.first );
        };
    
    // Map::map - new keys and values, not mutating the original collection, 
    // can be passed as unnamed temporary
    EXPECT_EQ( (Mapped{ {2,1}, {6,2} }),
      Map::map( std::map<int,int>{ {1,1}, {2,4} }, lambda ) );
}

TEST( Vector, filter )
{
    std::vector<int> items{ 1,2,3,4,5,4,3,2,1 };

    // Vector::filter will mutate the input collection
    EXPECT_EQ( (std::vector<int>{1,2,2,1}),
      Vector::filter( items,
        [](int i){ return 0 <= i && i <= 2; } ) );
    EXPECT_EQ( 4, items.size() );
}

TEST( Vector, filter_copy )
{
    std::vector<int> items{ 1,2,3,4,5,4,3,2,1 };
    auto untouched_size = items.size();
    
    // Vector::filter_copy creates a copy, so parameter 'items' is untouched
    EXPECT_EQ( (std::vector<int>{1,2,2,1}),
      Vector::filter_copy( items,
        [](int i){ return 0 <= i && i <= 2; } ) );
    EXPECT_EQ( untouched_size, items.size() );
}

TEST( Vector, fold )
{
    std::vector<int> items{ 1, 2, 3, 4, 5, -4, -6, -2, -1 };
    // Vector::fold takes F( A&, T ) -> void
    auto accumulate_squares = []( std::set<int>& acc, int i ){ acc.insert(i*i); };
    std::set<int> expected{1, 4, 9, 16, 25, 36};
    EXPECT_EQ( expected, 
      Vector::fold( items, accumulate_squares, std::set<int>{} ) );
}

TEST( Vector, sort )
{
    // Vector::sort mutates the input, hence input is non-const reference
    std::vector<int> items{1,2,1,3};
    EXPECT_EQ( (std::vector<int>{1,1,2,3}), 
      Vector::sort( items ) );
}

TEST( Vector, sort_copy )
{
    // Vector::sort_copy copies the input collection,
    // so collection parameter is const& (and can be an unnamed temporary)
    EXPECT_EQ( (std::vector<int>{1,1,2,3}), 
      Vector::sort_copy( std::vector<int>{1,2,1,3} ) );
}

TEST( Vector, map )
{
    // Vector::map takes F(T) -> U
    // Input collection is const and a new collection is returned
    EXPECT_EQ( (std::vector<double>{ 1.1, 2.1, 3.1 }),
      Vector::map( std::vector<int>{ 1,2,3 },
        []( int i ){ return (double)i + 0.1; } ) );
}

TEST( Vector, transform )
{
    // Vector::transform takes F(T) -> T
    // Input collection is mutated
    std::vector<int> items{ 1, 2, 3 };
    EXPECT_EQ( (std::vector<int>{ 2, 4, 6 }),
      Vector::transform( items, []( int i ){ return 2*i; } ) );
}

int main(int argc, char* argv[]) 
{    
    InitGoogleMock( &argc, argv );
    return RUN_ALL_TESTS();   
}

Notice that we can bypass immutability in C++, so whereas in F# Map::filter would always create a copy, it could be preferable in C++ to filter in-place. With that in mind, I’ve written both filter and filter_copy variations. There’s a similar dilemma for map operations – if you want free rein over the output types, then use Map::map or Vector::map. But if you want to transform the data in place (sticking to the existing types), use Map::transform or Vector::transform.

That covers the most popular functions for just Map and Vector, but it would be straight-forward to extend the library to cover List, Set and others. Similarly, I’d like to extend it to include higher-order functions like Choose, but I’ll need C++17’s std::optional for that.

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How to approximate Pi using C++11 random number generators

The other day I learnt a method to approximate Pi if you have a random number generator for the range [0,1]. Consider a unit circle centred on (0,0) in 2D coordinates. Then one quarter of the area of the circle lies in the quadrant formed by x and y in range [0,1]. The area of the quarter circle is Pi * R^2/4, and here, R = 1 (it’s a unit circle). So we can generate a bunch of random 2D points, calculate the ratio between those that fall inside the circle and those in the outer unit square, then multiply by 4 to approximate Pi.
approximatepi
That sounds like a neat test case for the C++11 random number generators, so I thought I’d try it out. It turns out to work pretty well, if you’re prepared to use a sufficiently large number of random values.

    double approxPi( size_t points )
    {
        std::random_device rand_device;
        
        // mersenne_twister_engine is a random number engine 
        // based on Mersenne Twister algorithm.
        std::mt19937 generator( rand_device() );
        
        // We want random values uniformly distributed in [0,1]
        std::uniform_real_distribution<> unif_zero_one(0, 1);
        
        size_t points_inside{0};
        
        for (int i = 0; i < points; ++i )
        {
            auto x = unif_zero_one( generator );
            auto y = unif_zero_one( generator );
            double d = std::sqrt( x*x + y*y );
            
            if ( d <= 1.0 )
                ++points_inside;
        }
                
        return 4.0 * (static_cast<double>(points_inside) / static_cast<double>(points));
    }
}

void testApproximatePi()
{
    SHOULD_BE_APPROX( 3.14159, 0.3, approxPi( 100 ) );
    SHOULD_BE_APPROX( 3.14159, 0.1, approxPi( 1000 ) );
    SHOULD_BE_APPROX( 3.14159, 0.01, approxPi( 100000 ) );
    SHOULD_BE_APPROX( 3.14159, 0.001, approxPi( 10000000 ) );
    
    std::cout << "\n";
}

A typical run gives reasonable approximations once you get over 100,000 points:
screen-shot-2016-09-16-at-13-30-26

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How to efficiently find the n’th biggest element in a collection

Looking at std::nth_element the other day, I noticed that it’s complexity is O(n) for a collection of size n, and wondered how that was achieved. A basic implementation of an algorithm to find the ith-biggest element might start by sorting the collection and index to the ith afterwards – complexity O(n*log(n)):

int ith_element_by_sorting( std::vector<int> input, int i )
{
    std::sort( std::begin(input), std::end(input) );
    return input[i];
}

It’s a small step to realise then that you don’t need to sort all n elements of the collection – only the first i elements, so complexity O(n*log(i)):

int ith_element_by_partial_sort( std::vector<int> input, int i )
{
    std::partial_sort( std::begin( input ), std::begin( input ) + i + 1, std::end( input ) );
    return input[i];
}

But the real trick is that you don’t need to do any sorting at all. That’s the approach taken by quickselect, which is the selection sibling to quicksort, and achieves O(n) complexity on average:

int partition( std::vector<int>& values, int left, int right, int pivot )
{
     auto pivotValue = values[ pivot ];

     std::swap( values[pivot], values[right] ); // Move pivot to end
     auto store_pos = left;

     for ( int j = left; j < right; ++j )
     {
         if ( values[j] < pivotValue )
         {
             std::swap( values[ store_pos ], values[j] );
             ++store_pos;
         }
     }

     std::swap( values[right], values[ store_pos ] );  // Move pivot to its final place

     return store_pos;
}

int quickselect( std::vector<int> values, int left, int right, int i )
{
    // Unordered - no need to sort values at all, 
    // instead we recursively partition only the subset of values
    // containing the i'th element, until we have either
    // a) trivial subset of 1
    // b) pivot is moved to exactly the location we wanted 
    while( 1 )
    {
         if ( left == right )
         {
             return values[left];
         }

         // Pick a pivot from middle of values.
         // Better options are a random pivot or median of 3
         auto pivot = (left + right)/2; 

         // Move anything smaller than values[pivot] to the left of pivot,
         // and return updated position of pivot
         pivot = partition( values, left, right, pivot );

         if ( pivot == i )
         {
             return values[i];
         }
         else if ( i < pivot )
         {
             right = pivot - 1;
         }
         else
         {
             left = pivot + 1;
         }
    }
}

int ith_element_by_quickselect( const std::vector<int>& input, int i )
{
    return quickselect( input, 0, input.size()-1, i );
}

int ith_element( const std::vector<int>& input, int i )
{
    if ( i < 0 || i >= input.size() )
    {
        std::ostringstream ss;
        ss << "Input '" << i << "' outside range [0," << input.size() << ")";
        throw std::out_of_range( ss.str() );
    }

    return ith_element_by_quickselect( input, i );
}

Here’s some test code to check that the implementation works:

template <typename F, typename T>
void should_be( T t, F f, const std::string& message )
{
    try
    {
        std::ostringstream ss;

        auto got = f();
        if ( got != t )
        {
            ss << message << " got " << got << ", expected " << t;
            throw std::runtime_error( ss.str() );
        }
        else
        {
            ss << "OK: " << message << ": got " << got;
            std::cout << ss.str() << "\n";
        }
    }
    catch( const std::exception& ex )
    {
        // Report error if either f() threw or we found unexpected value
        std::cout << "ERROR: " << ex.what() << "\n";
    }
}

template <typename F>
void should_throw( F f, const std::string& message )
{
    try
    {
        f();
    }
    catch( const std::exception& ex )
    {
        std::cout << "OK: " << message << ": threw \"" << ex.what() << "\"\n";
        return;
    }

    std::cout << "ERROR: " << message << " should have thrown\n";
}

#define SHOULD_BE( t, expr ) should_be( t, [](){ return expr; }, #expr )
#define SHOULD_THROW( expr ) should_throw( [](){ expr; }, #expr )

void testIthElement()
{
    SHOULD_THROW( ith_element( {}, 0 ) );
    SHOULD_THROW( ith_element( {1,2}, -1 ) );
    SHOULD_THROW( ith_element( {1,2,3}, 3 ) );

    SHOULD_BE( 1, ith_element( {1}, 0 ) );
    SHOULD_BE( 0, ith_element( {0,1,2,3,4,5,6,7,8}, 0 ) );
    SHOULD_BE( 2, ith_element( {0,1,2,3,4,5,6,7,8}, 2 ) );
    SHOULD_BE( 6, ith_element( {5,4,7,6,1,2,0,8,3}, 6 ) );
    SHOULD_BE( 8, ith_element( {5,4,7,6,1,2,0,8,3}, 8 ) );
    SHOULD_BE( 5, ith_element( {5,5,5,5,5,5}, 1 ) );
}

Here’s the output:
QuickSelect

In fact, reviewing old posts on this blog, I found this link that dates back to 2013, when std::nth_element was only required by the standard to have worst-case O(N^2) complexity, with O(N) on average – precisely what you’d get from quickselect. Now though, thanks to introselect, O(N) is possible.

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Video: Herb Sutter Back to the Basics at Cpp Con 2014

Herb Sutter’s Back to the Basics video is hardly an introduction to C++ as the name suggests. Rather, it clarifies his default choices when faced with some basic tasks like parameter passing, in the light of modern C++ techniques.

Don’t pass owning choices down the call stack – use non-owning raw pointers and references when you don’t need ownership transfer down the call stack, e.g. when callee parameter’s lifetime entirely nested within the called method. If the called method doesn’t participate in ownership, it should be agnostic to the lifetime of the object, whether on the stack, the heap, global, shared_ptr or unique_ptr.
image

Another reason to use auto is performance – it guarantees no implicit conversion because there’s no explicit declared type.
20150326-120815.jpg

Reviewing parameter passing choices, established rules of thumb still apply, they just got better.
20150326-121118.jpg
This is especially true for pass-by-value, which experts considered to be the new default choice for a while for moveable types, but is now only recommended for constructors that wish to retain a copy.

There was a bonus slide on returning multiple values using std::tie, which I’ve been doing for a while.
image

Finally, it seems that there’s a new term for Universal References – “Forwarding References”. I agree that this states the intention of T&& parameters better that Scott Meyer’s original name, although my eBook of Effective Modern C++ still uses the old name.

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cpplinq – functional style for C++ using lambdas

I’ve just tried out CppLinq, a C++11 library that brings LINQ-style syntax into scope for C++ programmers that are used to writing code in a functional style. I’ve been using C++11 lambdas with STL algorithms like foreach, transform, accumulate – but this syntax using where, for_each, sum and ‘>>’ to chain commands together is so much neater. In fact, it brings C++11 style very close to the succinct F# piping style that is so popular.

To use cpplinq, you can just download a single header file and include it in your code. Awesome – having just battled for hours to use some other 3rd party library which required multiple libs, source files and compiler switches, this is so easy by comparison.

This Dr Dobbs article has several code examples which act as an simple tutorial.

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How to emulate C++11’s ‘enum class’ in C++03

One of many neat features in C++11 is the introduction of ‘enum class’ – this addresses problems arising from enum declarations such as scoping (the enum cases leak in the same scope as the enum type) and implicit conversion to integer. See Stroustrup’s C++11 FAQ for more details.

However, in the papers that motivated the new language feature (N1513 and N2347) they discuss the current workarounds for C++03. One such workaround is to define a class to represent the enum type – it’s much more verbose than the new C++11 feature, but it solves the scoping and conversion issues.

// Header file
class Weekday
{
private:
  // Note that the private enum cases have underscores to differentiate
  // from the public cases
  typedef enum Weekday_ { Mon_, Tues_, Wed_, Thurs_, Fri_, Sat_, Sun_ };
  Weekday_ value_;

public:
  static const Weekday Mon, Tues, Wed, Thurs, Fri, Sat, Sun;
  explicit Weekday( const Weekday_& value ) : value_( value ){}

  bool operator<( const Weekday& rhs ) const { return this->value_ < rhs.value_; }
  bool operator==( const Weekday& rhs ) const { return this->value_ == rhs.value_; }
  bool operator!=( const Weekday& rhs ) const { return !(this->operator==(rhs)); }
};

// Source file
// Definitions for the public Weekday instances 
// in terms of the private enum
const Weekday Weekday::Mon( Mon_ );
const Weekday Weekday::Tues( Tues_ );
const Weekday Weekday::Wed( Wed_ );
const Weekday Weekday::Thurs( Thurs_ );
const Weekday Weekday::Fri( Fri_ );
const Weekday Weekday::Sat( Sat_ );
const Weekday Weekday::Sun( Sun_ );

That’s it – I’ve been using this recently and it works pretty well. I also added a “to_int()” member and a static “from_int()” member to explicitly convert bewteen the enum class and integers – the implementation is simply a switch over the enum cases.

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Going Native 2013 – Don’t Help the Compiler, Stephan Lavavej

This presentation from Stephan Lavavej could have been entitled “Compiler Knows Best” – he rockets through numerous examples where the advice is to write less code and let the compiler do the right thing.

Here’s a slide of one of the key messages:

20140207-183930.jpg

Other highlights for me:

  • decltype(auto) coming in C++14 looks very cool (eliminates duplicate code when using auto with decltype for late-specified return values)
  • Don’t call std::make_pair( x, y ) – the T, U are inferred by template argument deduction, so should always be left out (unless you want to force a type conversion when T != typeof(x) e.g. short -> long
  • Use nullptr because it is convertable to all pointer types, but 0 and NULL are always type int

I love the new features of C++11 and couldn’t have written some of the cool libraries I’m working on without them. But – presentations like this make me concerned for the complexity of the language and the steep learning curve that even experienced C++ hires will have to climb.

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