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Boost C++ Application Development Cookbook

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Over 80 practical, task-based recipes to create applications using Boost libraries with this book and ebook

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by Antony Polukhin | September 2013 | Cookbooks Open Source

In this article by Antony Polukhin, the author of the book Boost C++ Application Development Cookbook, we will cover:

  • Working with graphs
  • Visualizing graphs
  • Using a true random number generator
  • Using portable math functions
  • Writing test cases
  • Combining multiple test cases in one test module
  • Manipulating images

Boost is a huge collection of libraries. Some of those libraries are small and meant for everyday use and others require a separate article to describe all of their features. This article is devoted to some of those big libraries and to give you some basics to start with. The first two recipes will explain the usage of Boost.Graph. It is a big library with an insane number of algorithms. We'll see some basics and probably the most important part of it visualization of graphs.

We'll also see a very useful recipe for generating true random numbers. This is a very important requirement for writing secure cryptography systems.

Some C++ standard libraries lack math functions. We'll see how that can be fixed using Boost. But the format of this article leaves no space to describe all of the functions.

Writing test cases is described in the Writing test cases and Combining multiple test cases in one test module recipes. This is important for any production-quality system.

The last recipe is about a library that helped me in many courses during my university days. Images can be created and modified using it. I personally used it to visualize different algorithms, hide data in images, sign images, and generate textures.

Unfortunately, even this article cannot tell you about all of the Boost libraries. Maybe someday I'll write another book... and then a few more.

Working with graphs

Some tasks require a graphical representation of data. Boost.Graph is a library that was designed to provide a flexible way of constructing and representing graphs in memory. It also contains a lot of algorithms to work with graphs, such as topological sort, breadth first search, depth first search, and Dijkstra shortest paths.

Well, let's perform some basic tasks with Boost.Graph!

Getting ready

Only basic knowledge of C++ and templates is required for this recipe.

How to do it...

In this recipe, we'll describe a graph type, create a graph of that type, add some vertexes and edges to the graph, and search for a specific vertex. That should be enough to start using Boost.Graph.

  1. We start with describing the graph type:

    #include <boost/graph/adjacency_list.hpp> #include <string> typedef std::string vertex_t; typedef boost::adjacency_list< boost::vecS , boost::vecS , boost::bidirectionalS , vertex_t > graph_type;

  2. Now we construct it:

    graph_type graph;

  3. Let's use a non portable trick that speeds up graph construction:

    static const std::size_t vertex_count = 5; graph.m_vertices.reserve(vertex_count);

  4. Now we are ready to add vertexes to the graph:

    typedef boost::graph_traits<graph_type> ::vertex_descriptor descriptor_t; descriptor_t cpp = boost::add_vertex(vertex_t("C++"), graph); descriptor_t stl = boost::add_vertex(vertex_t("STL"), graph); descriptor_t boost = boost::add_vertex(vertex_t("Boost"), graph); descriptor_t guru = boost::add_vertex(vertex_t("C++ guru"), graph); descriptor_t ansic = boost::add_vertex(vertex_t("C"), graph);

  5. It is time to connect vertexes with edges:

    boost::add_edge(cpp, stl, graph); boost::add_edge(stl, boost, graph); boost::add_edge(boost, guru, graph); boost::add_edge(ansic, guru, graph);

  6. We make a function that searches for a vertex:

    template <class GraphT> void find_and_print(const GraphT& g, boost::string_ref name) {

  7. Now we will write code that gets iterators to all vertexes:

    typedef typename boost::graph_traits<graph_type> ::vertex_iterator vert_it_t; vert_it_t it, end; boost::tie(it, end) = boost::vertices(g);

  8. It's time to run a search for the required vertex:

    typedef boost::graph_traits<graph_type>::vertex_descriptor desc_t; for (; it != end; ++ it) { desc_t desc = *it; if (boost::get(boost::vertex_bundle, g)[desc] == name.data()) { break; } } assert(it != end); std::cout << name << '\n'; } /* find_and_print */

How it works...

In step 1, we are describing what our graph must look like and upon what types it must be based. boost::adjacency_list is a class that represents graphs as a two-dimensional structure, where the first dimension contains vertexes and the second dimension contains edges for that vertex. boost::adjacency_list must be the default choice for representing a graph; it suits most cases.

The first template parameter, boost::adjacency_list, describes the structure used to represent the edge list for each of the vertexes; the second one describes a structure to store vertexes. We can choose different STL containers for those structures using specific selectors, as listed in the following table:

Selector

STL container

boost::vecS

std::vector

boost::listS

std::list

boost::slistS

std::slist

boost::setS

std::set

boost::multisetS

std::multiset

boost::hash_setS

std::hash_set

The third template parameter is used to make an undirected, directed, or bidirectional graph. Use the boost::undirectedS, boost::directedS, and boost::bidirectionalS selectors respectively.

The fifth template parameter describes the datatype that will be used as the vertex. In our example, we chose std::string. We can also support a datatype for edges and provide it as a template parameter.

Steps 2 and 3 are trivial, but at step 4 you will see a non portable way to speed up graph construction. In our example, we use std::vector as a container for storing vertexes, so we can force it to reserve memory for the required amount of vertexes. This leads to less memory allocations/deallocations and copy operations during insertion of vertexes into the graph. This step is non-portable because it is highly dependent on the current implementation of boost::adjacency_list and on the chosen container type for storing vertexes.

At step 4, we see how vertexes can be added to the graph. Note how boost::graph_traits<graph_type> has been used. The boost::graph_traits class is used to get types that are specific for a graph type. We'll see its usage and the description of some graph-specific types later in this article. Step 5 shows what we need do to connect vertexes with edges.

If we had provided a datatype for the edges, adding an edge would look as follows:

boost::add_edge(ansic, guru, edge_t(initialization_parameters), graph)

Note that at step 6 the graph type is a template parameter. This is recommended to achieve better code reusability and make this function work with other graph types.

At step 7, we see how to iterate over all of the vertexes of the graph. The type of vertex iterator is received from boost::graph_traits. The function boost::tie is a part of Boost.Tuple and is used for getting values from tuples to the variables. So calling boost::tie(it, end) = boost::vertices(g) will put the begin iterator into the it variable and the end iterator into the end variable.

It may come as a surprise to you, but dereferencing a vertex iterator does not return vertex data. Instead, it returns the vertex descriptor desc, which can be used in boost::get(boost::vertex_bundle, g)[desc] to get vertex data, just as we have done in step 8. The vertex descriptor type is used in many of the Boost.Graph functions; we saw its use in the edge construction function in step 5.

As already mentioned, the Boost.Graph library contains the implementation of many algorithms. You will find many search policies implemented, but we won't discuss them in this article. We will limit this recipe to only the basics of the graph library.

There's more...

The Boost.Graph library is not a part of C++11 and it won't be a part of C++1y. The current implementation does not support C++11 features. If we are using vertexes that are heavy to copy, we may gain speed using the following trick:

vertex_descriptor desc = boost::add_vertex(graph); boost::get(boost::vertex_bundle, g_)[desc] = std::move(vertex_data);

It avoids copy constructions of boost::add_vertex(vertex_data, graph) and uses the default construction with move assignment instead.

The efficiency of Boost.Graph depends on multiple factors, such as the underlying containers types, graph representation, edge, and vertex datatypes.

Visualizing graphs

Making programs that manipulate graphs was never easy because of issues with visualization. When we work with STL containers such as std::map and std::vector, we can always print the container's contents and see what is going on inside. But when we work with complex graphs, it is hard to visualize the content in a clear way: too many vertexes and too many edges.

In this recipe, we'll take a look at the visualization of Boost.Graph using the Graphviz tool.

Getting ready

To visualize graphs, you will need a Graphviz visualization tool. Knowledge of the preceding recipe is also required.

How to do it...

Visualization is done in two phases. In the first phase, we make our program output the graph's description in a text format; in the second phase, we import the output from the first step to some visualization tool. The numbered steps in this recipe are all about the first phase.

  1. Let's write the std::ostream operator for graph_type as done in the preceding recipe:

    #include <boost/graph/graphviz.hpp> std::ostream& operator<<(std::ostream& out, const graph_type& g) { detail::vertex_writer<graph_type> vw(g); boost::write_graphviz(out, g, vw); return out; }

  2. The detail::vertex_writer structure, used in the preceding step, must be defined as follows:

    namespace detail { template <class GraphT> class vertex_writer { const GraphT& g_; public: explicit vertex_writer(const GraphT& g) : g_(g) {} template <class VertexDescriptorT> void operator()(std::ostream& out, const VertexDescriptorT& d) const { out << " [label=\"" << boost::get(boost::vertex_bundle, g_)[d] << "\"]"; } }; // vertex_writer } // namespace detail

That's all. Now, if we visualize the graph from the previous recipe using the std::cout << graph; command, the output can be used to create graphical pictures using the dot command-line utility:

$ dot -Tpng -o dot.png digraph G { 0 [label="C++"]; 1 [label="STL"]; 2 [label="Boost"]; 3 [label="C++ guru"]; 4 [label="C"]; 0->1 ; 1->2 ; 2->3 ; 4->3 ; }

 

The output of the preceding command is depicted in the following figure:

We can also use the Gvedit or XDot programs for visualization if the command line frightens you.

How it works...

The Boost.Graph library contains function to output graphs in Graphviz (DOT) format. If we write boost::write_graphviz(out, g) with two parameters in step 1, the function will output a graph picture with vertexes numbered from 0. That's not very useful, so we provide an instance of the vertex_writer class that outputs vertex names.

As we can see in step 2, the format of output must be DOT, which is understood by the Graphviz tool. You may need to read the Graphviz documentation for more info about the DOT format.

If you wish to add some data to the edges during visualization, we need to provide an instance of the edge visualizer as a fourth parameter to boost::write_graphviz.

There's more...

C++11 does not contain Boost.Graph or the tools for graph visualization. But you do not need to worry—there are a lot of other graph formats and visualization tools and Boost.

Graph can work with plenty of them.

Using a true random number generator

I know of many examples of commercial products that use incorrect methods for getting random numbers. It's a shame that some companies still use rand() in cryptography and banking software.

Let's see how to get a fully random uniform distribution using Boost.Random that is suitable for banking software.

Getting ready

Basic knowledge of C++ is required for this recipe. Knowledge of different types of distributions will also be helpful. The code in this recipe requires linking against the boost_random library.

How to do it...

To create a true random number, we need some help from the operating system or processor. This is how it can be done using Boost:

  1. We'll need to include the following headers:

    #include <boost/config.hpp> #include <boost/random/random_device.hpp> #include <boost/random/uniform_int_distribution.hpp>

  2. Advanced random number providers have different names under different platforms:

    static const std::string provider = #ifdef BOOST_WINDOWS "Microsoft Strong Cryptographic Provider" #else "/dev/urandom" #endif ;

  3. Now we are ready to initialize the generator with Boost.Random:

    boost::random_device device(provider);

  4. Let's get a uniform distribution that returns a value between 1000 and 65535:

    boost::random::uniform_int_distribution<unsigned short> random(1000);

That's it. Now we can get true random numbers using the random(device) call.

How it works...

Why does the rand() function not suit banking? Because it generates pseudo-random numbers, which means that the hacker could predict the next generated number. This is an issue with all pseudo-random number algorithms. Some algorithms are easier to predict and some harder, but it's still possible.

That's why we are using boost::random_device in this example (see step 3). That device gathers information about random events from all around the operating system to construct an unpredictable hardware-generated number. The examples of such events are delays between pressed keys, delays between some of the hardware interruptions, and the internal CPU random number generator.

Operating systems may have more than one such type of random number generators. In our example for POSIX systems, we used /dev/urandom instead of the more secure /dev/random because the latter remains in a blocked state until enough random events have been captured by the OS. Waiting for entropy could take seconds, which is usually unsuitable for applications. Use /dev/random to create long-lifetime GPG/SSL/SSH keys.

Now that we are done with generators, it's time to move to step 4 and talk about distribution classes. If the generator just generates numbers (usually uniformly distributed), the distribution class maps one distribution to another. In step 4, we made a uniform distribution that returns a random number of unsigned short type. The parameter 1000 means that distribution must return numbers greater or equal to 1000. We can also provide the maximum number as a second parameter, which is by default equal to the maximum value storable in the return type.

There's more...

Boost.Random has a huge number of true/pseudo random generators and distributions for different needs. Avoid copying distributions and generators; this could turn out to be an expensive operation.

C++11 has support for different distribution classes and generators. You will find all of the classes from this example in the <random> header in the std:: namespace. The Boost.Random libraries do not use C++11 features, and they are not really required for that library either. Should you use Boost implementation or STL? Boost provides better portability across systems; however, some STL implementations may have assembly-optimized implementations and might provide some useful extensions.

Using portable math functions

Some projects require specific trigonometric functions, a library for numerically solving ordinary differential equations, and working with distributions and constants. All of those parts of Boost.Math would be hard to fit into even a separate book. A single recipe definitely won't be enough. So let's focus on very basic everyday-use functions to work with float types.

We'll write a portable function that checks an input value for infinity and not-a-number (NaN) values and changes the sign if the value is negative.

Getting ready

Basic knowledge of C++ is required for this recipe. Those who know C99 standard will find a lot in common in this recipe.

How to do it...

Perform the following steps to check the input value for infinity and NaN values and change the sign if the value is negative:

  1. We'll need the following headers:

    #include <boost/math/special_functions.hpp> #include <cassert>

  2. Asserting for infinity and NaN can be done like this:

    template <class T> void check_float_inputs(T value) { assert(!boost::math::isinf(value)); assert(!boost::math::isnan(value));

  3. Use the following code to change the sign:

    if (boost::math::signbit(value)) { value = boost::math::changesign(value); } // ... } // check_float_inputs

That's it! Now we can check that check_float_inputs(std::sqrt(-1.0)) and check_float_inputs(std::numeric_limits<double>::max() * 2.0) will cause asserts.

How it works...

Real types have specific values that cannot be checked using equality operators. For example, if the variable v contains NaN, assert(v!=v) may or may not pass depending on the compiler.

For such cases, Boost.Math provides functions that can reliably check for infinity and NaN values.

Step 3 contains the boost::math::signbit function, which requires clarification. This function returns a signed bit, which is 1 when the number is negative and 0 when the number is positive. In other words, it returns true if the value is negative.

Looking at step 3 some readers might ask, "Why can't we just multiply by -1 instead of calling boost::math::changesign?". We can. But multiplication may work slower than boost::math::changesign and won't work for special values. For example, if your code can work with nan, the code in step 3 will be able to change the sign of -nan and write nan to the variable.

The Boost.Math library maintainers recommend wrapping math functions from this example in round parenthesis to avoid collisions with C macros. It is better to write (boost::math::isinf)(value) instead of boost::math::isinf(value).

There's more...

C99 contains all of the functions described in this recipe. Why do we need them in Boost? Well, some compiler vendors think that programmers do not need them, so you won't find them in one very popular compiler. Another reason is that the Boost.Math functions can be used for classes that behave like numbers.

Boost.Math is a very fast, portable, reliable library.

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Writing test cases

This recipe and the next one are devoted to auto-testing the Boost.Test library, which is used by many Boost libraries. Let's get hands-on with it and write some tests for our own class.

#include <stdexcept> struct foo { int val_; operator int() const; bool is_not_null() const; void throws() const; // throws(std::logic_error) };

Getting ready

Basic knowledge of C++ is required for this recipe. The code of this recipe requires linking against the static version of the boost_unit_test_framework library.

How to do it...

To be honest, there is more than one test library in Boost. We'll take a look at the most functional one.

  1. To use it, we'll need to define the macro and include the following header:

    #define BOOST_TEST_MODULE test_module_name #include <boost/test/unit_test.hpp>

  2. Each set of tests must be written in the test case:

    BOOST_AUTO_TEST_CASE(test_no_1) {

  3. Checking some function for the true result is done as follows:

    foo f1 = {1}, f2 = {2}; BOOST_CHECK(f1.is_not_null());

  4. Checking for nonequality is implemented in the following way:

    BOOST_CHECK_NE(f1, f2);

  5. Checking for an exception being thrown will look like this:

    BOOST_CHECK_THROW(f1.throws(), std::logic_error); } // BOOST_AUTO_TEST_CASE(test_no_1)

That's it! After compilation and linking, we'll get an executable file that automatically tests foo and outputs test results in a human-readable format.

How it works...

Writing unit tests is easy; you know how the function works and what result it should produce in specific situations. So you just check if the expected result is the same as the function's actual output. That's what we did in step 3. We know that f1.is_not_null() will return true and we checked it. At step 4, we know that f1 is not equal to f2, so we checked it too. The call to f1.throws() will produce the std::logic_error exception and we check that an exception of the expected type is thrown.

At step 2, we are making a test case – a set of checks to validate correct behavior of the foo structure. We can have multiple test cases in a single source file. For example, if we add the following code:

BOOST_AUTO_TEST_CASE(test_no_2) { foo f1 = {1}, f2 = {2}; BOOST_REQUIRE_NE(f1, f2); // ... } // BOOST_AUTO_TEST_CASE(test_no_2)

This code will run along with the test_no_1 test case. The parameter passed to the BOOST_AUTO_TEST_CASE macro is just a unique name of the test case that will be shown in case of error.

Running 2 test cases... main.cpp(15): error in "test_no_1": check f1.is_not_null() failed main.cpp(17): error in "test_no_1": check f1 != f2 failed [0 == 0] main.cpp(19):error in "test_no_1": exception std::logic_error is expected main.cpp(24): fatal error in "test_no_2": critical check f1 != f2 failed [0 == 0] *** 4 failures detected in test suite "test_module_name"

There is a small difference between the BOOST_REQUIRE_* and BOOST_CHECK_* macros. If the BOOST_REQUIRE_* macro check fails, the execution of the current test case will stop and Boost.Test will run the next test case. However, failing BOOST_CHECK_* won't stop the execution of the current test case.

Step 1 requires additional care. Note the BOOST_TEST_MODULE macro definition. This macro must be defined before including the Boost.Test headers, otherwise linking of the program will fail.

There's more...

Some readers may wonder, "Why did we write BOOST_CHECK_NE(f1, f2) in step 4 instead of BOOST_CHECK(f1 != f2)?". The answer is simple: the macro at step 4 provides a more readable and verbose output.

C++11 lacks support for unit testing. However, the Boost.Test library can be used to test C++11 code. Remember that the more tests you have, the more reliable code you get!

Combining multiple test cases in one test module

Writing auto tests is good for your project. But managing test cases is hard when the project is large and many developers are working on it. In this recipe, we'll take a look at how to run individual tests and how to combine multiple test cases in a single module.

Let's pretend that two developers are testing the foo structure declared in the foo.hpp header and we wish to give them separate source files to write a test to. In that way, the developers won't bother each other and can work in parallel. However, the default test run must execute the tests of both developers.

Getting ready

Basic knowledge of C++ is required for this recipe. This recipe partially reuses code from the previous recipe and it also requires linking against the static version of the boost_unit_test_framework library.

How to do it...

This recipe uses the code from the previous one. This is a very useful recipe for testing large projects; do not underestimate it.

  1. Of all the headers in main.cpp from the previous recipe, leave only these two lines:

    #define BOOST_TEST_MODULE test_module_name #include <boost/test/unit_test.hpp>

  2. Let's move the tests cases from the previous example into two different source files:

    // developer1.cpp #include <boost/test/unit_test.hpp> #include "foo.hpp" BOOST_AUTO_TEST_CASE(test_no_1) { // ... } /////////////////////////////////////////////////////////// // developer2.cpp #include <boost/test/unit_test.hpp> #include "foo.hpp" BOOST_AUTO_TEST_CASE(test_no_2) { // ... }

That's it! Thus compiling and linking all of the sources and both test cases will work on program execution.

How it works...

All of the magic is done by the BOOST_TEST_MODULE macro. If it is defined before <boost/test/unit_test.hpp>, Boost.Test thinks that this source file is the main one and all of the helper testing infrastructure must be placed in it. Otherwise, only the test macro will be included from <boost/test/unit_test.hpp>.

All of the BOOST_AUTO_TEST_CASE tests are run if you link them with the source file that contains the BOOST_TEST_MODULE macro. When working on a big project, each developer may enable compilation and linking of only their own sources. That gives independence from other developers and increases the speed of development—no need to compile alien sources and run alien tests while debugging.

There's more...

The Boost.Test library is good because of its ability to run tests selectively. We can choose which tests to run and pass them as command-line arguments. For example, the following command will run only the test_no_1 test case:

./testing_advanced –run=test_no_1

 

The following command will run two test cases:

./testing_advanced –run=test_no_1,test_no_2

 

Unfortunately, C++11 standard does not have built-in testing support and it looks like C++1y won't adopt the classes and methods of Boost.Test either.

Manipulating images

I've left you something really tasty for dessert – Boost's Generic Image Library (GIL), which allows you to manipulate images and not care much about image formats.

Let's do something simple and interesting with it; let's make a program that negates any picture.

Getting ready

This recipe requires basic knowledge of C++, templates, and Boost.Variant. The example requires linking against the PNG library.

How to do it...

For simplicity, we'll be working with only PNG images.

  1. Let's start with including the header files:

    #include <boost/gil/gil_all.hpp> #include <boost/gil/extension/io/png_dynamic_io.hpp> #include <string>

  2. Now we need to define the image types that we wish to work with:

    typedef boost::mpl::vector< boost::gil::gray8_image_t, boost::gil::gray16_image_t, boost::gil::rgb8_image_t, boost::gil::rgb16_image_t > img_types;

  3. Opening an existing PNG image can be implemented like this:

    std::string file_name(argv[1]); boost::gil::any_image<img_types> source; boost::gil::png_read_image(file_name, source);

  4. We need to apply the operation to the picture as follows:

    boost::gil::apply_operation( view(source), negate() );

  5. The following code line will help you to write an image:

    boost::gil::png_write_view("negate_" + file_name, const_view(source));

  6. Let's take a look at the modifying operation:

    struct negate { typedef void result_type; // required template <class View> void operator()(const View& source) const { // ... } }; // negate

  7. The body of operator() consists of getting a channel type:

    typedef typename View::value_type value_type; typedef typename boost::gil::channel_type<value_type>::type channel_t;

  8. It also iterates through pixels:

    const std::size_t channels = boost::gil::num_channels<View>::value; const channel_t max_val = (std::numeric_limits<channel_t>::max)(); for (unsigned int y = 0; y < source.height(); ++y) { for (unsigned int x = 0; x < source.width(); ++x) { for (unsigned int c = 0; c < channels; ++c) { source(x, y)[c] = max_val - source(x, y)[c]; } } }

Now let's see the results of our program:

The previous picture is the negative of the one that follows:

How it works...

In step 2, we are describing the types of images we wish to work with. Those images are gray images with 8 and 16 bits per pixel and RGB pictures with 8 and 16 bits per pixel.

The boost::gil::any_image<img_types> class is a kind of Boost.Variant that can hold an image of one of the img_types variable. As you may have already guessed, boost::gil::png_read_image reads images into image variables.

The boost::gil::apply_operation function at step 4 is almost equal to boost::apply_visitor from the Boost.Variant library. Note the usage of view(source). The boost::gil::view function constructs a light wrapper around the image that interprets it as a two-dimensional array of pixels.

Do you remember that for Boost.Variant we were deriving visitors from boost::static_visitor? When we are using GIL's version of variant, we need to make a result_type typedef inside visitor. You can see it in step 6.

A little bit of theory: images consist of points called pixels. Single images have pixels of the same type. However, pixels of different images can differ in channel count and color bits for a single channel. A channel represents a primary color. In the case of an RGB image, we'll have a pixel consisting of three channels—red, green, and blue. In the case of a gray image, we'll have a single channel representing gray.

Back to our image. In step 2, we described the types of images we wish to work with. In step 3, one of those image types is read from file and stored in the source variable. In step 4, the operator() method of the negate visitor is instantiated for all image types.

In step 7, we can see how to get the channel type from the image view.

In step 8, we iterate through pixels and channels and negate them. Negation is done via max_val - source(x, y)[c] and the result is written back to the image view.

We write an image back in step 5.

There's more...

C++11 has no built-in methods for working with images.

The Boost.GIL library is fast and efficient. The compilers optimize its code very well and we can even help the optimizer using some of the Boost.GIL methods to unroll loops. But this article talks about only some of the library basics, so it is time to stop.

Summary

This article was devoted to some of the big libraries of Boost to give you some basics to start with. The first two recipes explained the usage of Boost.Graph. It is a big library with an insane number of algorithms. We saw some basics and probably the most important part of its visualization of graphs.

We also saw a very useful recipe for generating true random numbers. This is a very important requirement for writing secure cryptography systems.

Some C++ standard libraries lack math functions. We saw how that could be fixed using Boost. But the format of this article leaves no space to describe all of the functions.

Writing test cases was described in the Writing test cases and Combining multiple test cases in one test module recipes. This is important for any production-quality system.

The last recipe was about a library that helped me in many courses during my university days. Images could be created and modified using it. I personally used it to visualize different algorithms, hide data in images, sign images, and generate textures.

Unfortunately, even this article cannot tell you about all of the Boost libraries. Maybe someday I'll write another book... and then a few more.

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About the Author :


Antony Polukhin

Antony Polukhin was born in Russia. As a child, he could speak the Russian and Hungarian languages and learned English at school. Since his school days, he was participating in different mathematics, physics, and chemistry competitions and winning them.

He was accepted into University twice: once for taking part in a city mathematics competition and again for gaining high score in an internal Universities mathematics and physics challenge. In his university life, there was not a year when he did not participate in an exam: he gained 'A's in all disciplines by writing highly difficult programs for each teacher. He met his future wife in university and graduated with honors.

For more than three years, he worked in a VoIP company developing business logic for a commercial alternative to Asterisc. During those days he started contributing to Boost and became a maintainer of the Boost.LexicalCast library. He also started making translations to Russian for Ubuntu Linux at that time.

Today, he develops a query engine for graph-oriented databases and continues to contribute to the open source. You may find his code in Boost libraries such as Any, LexicalCast, TypeTraits, Variant, and others.

He has been happily married for a year now.

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Android Native Development Kit Cookbook

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Boost.Asio C++ Network Programming

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Microsoft Visual C++ Windows Applications by Example

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Instant Windows 8 C++ Application Development How-to

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Mastering Windows 8 C++ App Development

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C Programming for Arduino


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