Category Archives: Programming languages

Exponential growth policy of std::vector

Once std::vector is filled (size() equals to capacity()), a subsequent push_back(…) results in an exponential expansion of the vector capacity. The following table shows that the expansion happens when the index reaches a power of two:

index: 0, capacity: 1, address: 0x1fa6c20
index: 1, capacity: 2, address: 0x1fa6c40
index: 2, capacity: 4, address: 0x1fa6c20
index: 4, capacity: 8, address: 0x1fa6c60
index: 8, capacity: 16, address: 0x1fa6c90
index: 16, capacity: 32, address: 0x1fa6ce0
index: 32, capacity: 64, address: 0x1fa6d70
index: 64, capacity: 128, address: 0x1fa6e80
index: 128, capacity: 256, address: 0x1fa7090
index: 256, capacity: 512, address: 0x1fa74a0
index: 512, capacity: 1024, address: 0x1fa7cb0
index: 1024, capacity: 2048, address: 0x1fa8cc0
index: 2048, capacity: 4096, address: 0x1faacd0
index: 4096, capacity: 8192, address: 0x1faece0
index: 8192, capacity: 16384, address: 0x1fb6cf0
index: 16384, capacity: 32768, address: 0x1fc6d00
index: 32768, capacity: 65536, address: 0x1fe6d10
index: 65536, capacity: 131072, address: 0x2026d20
index: 131072, capacity: 262144, address: 0x20a6d30
index: 262144, capacity: 524288, address: 0x21a6d40
index: 524288, capacity: 1048576, address: 0x23a6d50
index: 1048576, capacity: 2097152, address: 0x27a6d60
index: 2097152, capacity: 4194304, address: 0x2fa6d70
index: 4194304, capacity: 8388608, address: 0x7f8e9225f010
index: 8388608, capacity: 16777216, address: 0x7f8e8e25e010
index: 16777216, capacity: 33554432, address: 0x7f8e8625d010
index: 33554432, capacity: 67108864, address: 0x7f8e7625c010
index: 67108864, capacity: 134217728, address: 0x7f8e5625b010
index: 134217728, capacity: 268435456, address: 0x7f8e1625a010
index: 268435456, capacity: 536870912, address: 0x7f8d96259010
index: 536870912, capacity: 1073741824, address: 0x7f8c96258010

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How to erase an element with a reverse iterator from C++ container

The following C++ code demonstrates how to erase an element a reverse iterator points to:

#include <iostream>
#include <set>
#include <vector>
#include <assert.h>

int main()
{
	std::set<int> set;

	set.insert(15);

	std::cout << set.size() << " ";

	auto ri = set.rbegin();

	auto i1 = --ri.base();

	auto i2 = --set.end();

	assert(i1 == i2);

	set.erase(i1);

	std::cout << set.size() << std::endl;
}

The output is ‘0 1’. The key point here is that the reverse iterator is an adaptor for reverse-order traversal that can be created from forward iterator with std::make_reverse_iterator.

An example of how GCC thread sanitizer works.

The following simple code C++ example can be used for investigation of how GCC thread sanitizer works:

#include <mutex>
#include <atomic>
#include <iostream>
#include <thread>

std::mutex mutex;
int a = 3;
const size_t size = 1000 * 1000;
std::atomic<int> b(1);

void testA()
{
	for (size_t counter = 0; counter < size; counter++)
	{
		++b;
		std::unique_lock<std::mutex> lock(mutex);
		++a;
	}
}

void testB()
{
	for (size_t counter = 0; counter < size; counter++)
	{
		--b;
		std::unique_lock<std::mutex> lock(mutex);
		--a;
	}
}

int main()
{
	std::thread t1(testA);
	std::thread t2(testB);
	t1.join();
	t2.join();
}

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Multiple views with OsgQtQuick

I wrote a sample application using OsgQtQuick that shows the Earth in two views:

with the following QML, that I copied from OsgQtQuick samples:

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A sample C++ code demonstrating why int is not atomic

The code below demonstrates why it is not guaranteed that 4-byte value being written by another thread is read either as original or final, but it can be read “partially written”:

static constexpr int offset=2;
alignas(64) char vars[64+4-offset];
static volatile unsigned * const p = reinterpret_cast<unsigned *>(&vars[64-offset]);

unsigned getVar()
{
    return *p;
}

void loop()
{
    while(true)
    {
        *p = -1;
        *p = 0;
    }
}

#include <thread>
#include <iostream>
#include <iomanip>
#include <cstdlib>
#include <map>

int main()
{
    std::thread thread(loop);
    std::map<unsigned,int> xs;
    for(int i=0;i<10000000;++i)
    {
        const auto x=getVar();
        ++xs[x];
    }
    for(const auto& x : xs)
        std::cout << std::setfill('0') << std::setw(8) << std::hex << x.first << ": " << std::dec << x.second << " times\n";
    std::exit(0); // exit, killing the thread without abnormal termination via std::terminate
}

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Qt Quick Controls 2 does not support TableView

Qt Quick Controls 2 does not support TableView and looks like they are not going to support it, some notable missing features from Qt Quick Controls 1 also are Action, SplitView and TreeView, so the following QML code would not work:

TableView {

    TableViewColumn {
        role: "time"
        title: qsTr("date/time:")
        width: parent.width - 30
    }

    TableViewColumn {
        role: "score"
        title: qsTr("result:")
        width: 30
    }

    model: boardModel.list

    ScrollIndicator.vertical: ScrollIndicator { }
}

But there is a solution with ListView, so there can be something like this:

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Numeric promotions and conversions in C++

In the following C++ code the values of ‘z’ and ‘n’ are undefined, because they are the result of an operation with signed integer arithmetic overflow (‘x’ and ‘y’ are first implicitly converted to signed int). The value of ‘w’ is implementation defined, because it is the result of a conversion:

#include <iostream>
#include <bitset>

int main(int argc, char *argv[])
{
    unsigned short x = 65535, y = x;
    unsigned short z = x * y;
    unsigned int n = x * y;
    std::cerr << "z = " << std::bitset<16>(z) << ", n = " << std::bitset<32>(n) << ", sizeof(int) = " << sizeof(int) << std::endl;

    short w = 0x80000000;
    
    return 0;
}

see Numeric conversions section of Implicit conversions article.

Comparison of std::mutex and std::atomic performance

The following C++ code compares the performance of std::atomic and std::mutex:

#include <atomic>
#include <mutex>
#include <iostream>
#include <chrono>
#include <thread>

const size_t size = 100000000;
std::mutex mutex;
bool var = false;

typedef std::chrono::high_resolution_clock Clock;

void testA()
{
    std::atomic<bool> sync(true);
    const auto start_time = Clock::now();
    for (size_t counter = 0; counter < size; counter++)
    {
        var = sync.load();
        //sync.store(true);
        //sync.exchange(true);
    }
    const auto end_time = Clock::now();
    std::cout << 1e-6*std::chrono::duration_cast<std::chrono::microseconds>(end_time - start_time).count() << " s\n";
}

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Detecting memory leaks of C++ application in Ubuntu

First, I tried Valgrind tool using the following command:

valgrind --tool=memcheck --leak-check=yes ./app

With some large QT application started for some short period I got the following output:

==7090== HEAP SUMMARY:
==7090==     in use at exit: 5,623,365 bytes in 36,268 blocks
==7090==   total heap usage: 32,454,680 allocs, 32,418,412 frees, 12,822,939,874 bytes allocated
…………………………..
==7090== LEAK SUMMARY:
==7090== definitely lost: 20,163 bytes in 74 blocks
==7090== indirectly lost: 60,053 bytes in 1,273 blocks
==7090== possibly lost: 396,167 bytes in 2,169 blocks
==7090== still reachable: 4,834,822 bytes in 31,576 blocks
==7090== suppressed: 0 bytes in 0 blocks
==7090== Reachable blocks (those to which a pointer was found) are not shown.
==7090== To see them, rerun with: –leak-check=full –show-leak-kinds=all
==7090==
==7090== For counts of detected and suppressed errors, rerun with: -v
==7090== Use –track-origins=yes to see where uninitialised values come from
==7090== ERROR SUMMARY: 20905 errors from 1583 contexts (suppressed: 15 from 2)

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QML DropShadow is very slow

QML DropShadow is an interesting effect that acts in a very simple way. It works fine in my application and produces the following result:

QML DropShadow is very slow

The only disadvantage of DropShadow effect is that is slows down my application from 60 FPS to 30 FPS on Android Phone. The following code demonstrates how I use it with StackView:

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