Should non-QObject derived classes "always" be put on the stack? - qt

Coming from the Symbian world, I'm used to using the heap as much as possible to avoid running out of stack space, especially when handling descriptors. CBase derived classes were always dynamically allocated on the heap, since if they were not, their member variables would stay uninitialized. Does the same convention apply to QObject-derived classes?
In Qt it seems to be common to put, for example QString, on the stack. Are the string contents put on the heap while QString acts as a container on the stack, or is everything put on the stack?

As sje397 said: It's idiomatic to put QString and containers on the stack, as they are implicitly shared. Their internals (pimpl idiom "d" pointer) are created on the heap. There is no point in creating the object itself on the heap, too. Just causes memory-management hassles and you lose the intended copy-on-write properties when passing pointers to strings/containers around.
QObjects on the other hand you want to create on the heap in almost all cases, as otherwise they would be destructed again right away. They can't be copied or assigned (well, one can enforce it for own subclasses, but the QObject semantics are broken then), and usually they are supposed to survive the method body they are created in.
Exception is QDialog, which is often created on the stack, followed by QDialog::exec, which blocks until the dialog is closed. But even that is strictly spoken unsafe, as external events (RPC calls, background operations) could cause the dialog to be deleted by its parent (if the parent itself is deleted) before exec returns.
Then having the dialog created on the stack will cause double deletion when unwinding the stack -> crash.

QString, and many other Qt classes, use implicit data sharing. That implies that memory is generally allocated on the heap.

Related

How does operator delete work in qt5 with qObjects

In c++ when u allocate memory, u should always delete them (in Destructors for example). But in qt u often don't worry about deleting objects. Qt does it for u. IDE does not correctly show all the memory leaks. I saw code somewhere like this:
anyLayout->addWidget(new QLabel(QString("text")));
will this QLabel be truly memory leak?
The same question about adding the same way QListString to QComboBox.
No, QWidgets added to a layout will be automatically parented to the layout. This is explained here.
Note: The ownership of item is transferred to the layout, and it's the layout's responsibility to delete it.
When the parents are cleaned up, so will the children. I would encourage you to read about Object Trees & Ownership in Qt.

Qt containers with object

When using a Qt container as Qlist, Qvector etc to hold some class (say a complex class with many data members and logics) and calling insert/append/push_back will the object added to the container be inserted to the container or it will be copied (cctor) ?
Suppose it is copied then If I dynamically allocate it and pass a pointer then only the pointer will be copied? And if I pass the object itself then I need to free the memory I've allocated before because the object is copied ?
I could some official documentation so I'm asking here...
Thanks
In the case of QObject derived objects, you have to use dynamic allocation and just put pointers in the container, because such objects have unique identities and as such are prohibited from copying. In that case only the pointer is copied around, which is just an integer, the copying of which has no effect on the actual object it points to. With dynamically allocated objects you have to either manage lifetime manually or use Qt's parent/child functionality to have objects "collected" by their parent objects.
The values stored in the various containers can be of any assignable data type. To qualify, a type must provide a default constructor, a
copy constructor, and an assignment operator. This covers most data
types you are likely to want to store in a container, including basic
types such as int and double, pointer types, and Qt data types such as
QString, QDate, and QTime, but it doesn't cover QObject or any QObject
subclass (QWidget, QDialog, QTimer, etc.). If you attempt to
instantiate a QList, the compiler will complain that
QWidget's copy constructor and assignment operators are disabled.
As the quoted text above indicates, when placing the actual instances in a container, copying of the object will occur. In this case you don't have to manually delete anything, since the source of the copy would typically be a local object and often a temporary, of which the compiler will take care.
"Placement new" is a C++ feature you can use to specify the place the object is constructed in memory, but it comes at complexity of managing it and some limitations. The advantages of placement new and memory pools rarely outweigh the increase of complexity and loss of flexibility.

Multitasking using setjmp, longjmp

is there a way to implement multitasking using setjmp and longjmp functions
You can indeed. There are a couple of ways to accomplish it. The difficult part is initially getting the jmpbufs which point to other stacks. Longjmp is only defined for jmpbuf arguments which were created by setjmp, so there's no way to do this without either using assembly or exploiting undefined behavior. User level threads are inherently not portable, so portability isn't a strong argument for not doing it really.
step 1
You need a place to store the contexts of different threads, so make a queue of jmpbuf stuctures for however many threads you want.
Step 2
You need to malloc a stack for each of these threads.
Step 3
You need to get some jmpbuf contexts which have stack pointers in the memory locations you just allocated. You could inspect the jmpbuf structure on your machine, find out where it stores the stack pointer. Call setjmp and then modify its contents so that the stack pointer is in one of your allocated stacks. Stacks usually grow down, so you probably want your stack pointer somewhere near the highest memory location. If you write a basic C program and use a debugger to disassemble it, and then find instructions it executes when you return from a function, you can find out what the offset ought to be. For example, with system V calling conventions on x86, you'll see that it pops %ebp (the frame pointer) and then calls ret which pops the return address off the stack. So on entry into a function, it pushes the return address and frame pointer. Each push moves the stack pointer down by 4 bytes, so you want the stack pointer to start at the high address of the allocated region, -8 bytes (as if you just called a function to get there). We will fill the 8 bytes next.
The other thing you can do is write some very small (one line) inline assembly to manipulate the stack pointer, and then call setjmp. This is actually more portable, because in many systems the pointers in a jmpbuf are mangled for security, so you can't easily modify them.
I haven't tried it, but you might be able to avoid the asm by just deliberately overflowing the stack by declaring a very large array and thus moving the stack pointer.
Step 4
You need exiting threads to return the system to some safe state. If you don't do this, and one of the threads returns, it will take the address right above your allocated stack as a return address and jump to some garbage location and likely segfault. So first you need a safe place to return to. Get this by calling setjmp in the main thread and storing the jmpbuf in a globally accessible location. Define a function which takes no arguments and just calls longjmp with the saved global jmpbuf. Get the address of that function and copy it to your allocated stacks where you left room for the return address. You can leave the frame pointer empty. Now, when a thread returns, it will go to that function which calls longjmp, and jump right back into the main thread where you called setjmp, every time.
Step 5
Right after the main thread's setjmp, you want to have some code that determines which thread to jump to next, pulling the appropriate jmpbuf off the queue and calling longjmp to go there. When there are no threads left in that queue, the program is done.
Step 6
Write a context switch function which calls setjmp and stores the current state back on the queue, and then longjmp on another jmpbuf from the queue.
Conclusion
That's the basics. As long as threads keep calling context switch, the queue keeps getting repopulated, and different threads run. When a thread returns, if there are any left to run, one is chosen by the main thread, and if none are left, the process terminates. With relatively little code you can have a pretty basic cooperative multitasking setup. There are more things you probably want to do, like implement a cleanup function to free the stack of a dead thread, etc. You can also implement preemption using signals, but that is much more difficult because setjmp doesn't save the floating point register state or the flags registers, which are necessary when the program is interrupted asynchronously.
It may be bending the rules a little, but GNU pth does this. It's possible, but you probably shouldn't try it yourself except as an academic proof-of-concept exercise, use the pth implementation if you want to do it seriously and in a remotely portable fashion -- you'll understand why when you read the pth thread creation code.
(Essentially it uses a signal handler to trick the OS into creating a fresh stack, then longjmp's out of there and keeps the stack around. It works, evidently, but it's sketchy as hell.)
In production code, if your OS supports makecontext/swapcontext, use those instead. If it supports CreateFiber/SwitchToFiber, use those instead. And be aware of the disappointing truth that one of the most compelling use of coroutines -- that is, inverting control by yielding out of event handlers called by foreign code -- is unsafe because the calling module has to be reentrant, and you generally can't prove that. This is why fibers still aren't supported in .NET...
This is a form of what is known as userspace context switching.
It's possible but error-prone, especially if you use the default implementation of setjmp and longjmp. One problem with these functions is that in many operating systems they'll only save a subset of 64-bit registers, rather than the entire context. This is often not enough, e.g. when dealing with system libraries (my experience here is with a custom implementation for amd64/windows, which worked pretty stable all things considered).
That said, if you're not trying to work with complex external codebases or event handlers, and you know what you're doing, and (especially) if you write your own version in assembler that saves more of the current context (if you're using 32-bit windows or linux this might not be necessary, if you use some versions of BSD I imagine it almost definitely is), and you debug it paying careful attention to the disassembly output, then you may be able to achieve what you want.
I did something like this for studies.
https://github.com/Kraego/STM32L476_MiniOS/blob/main/Usercode/Concurrency/scheduler.c
The context/thread switching is done by setjmp/longjmp. The difficult part was to get the allocated stack correct (see allocateStack()) this depends on your platform.
This is just a demonstration how this could work, I would never use this in production.
As was already mentioned by Sean Ogden,
longjmp() is not good for multitasking, as
it can only move the stack upward and can't
jump between different stacks. No go with that.
As mentioned by user414736, you can use getcontext/makecontext/swapcontext
functions, but the problem with those is that
they are not fully in user-space. They actually
call the sigprocmask() syscall because they switch
the signal mask as part of the context switching.
This makes swapcontext() much slower than longjmp(),
and you likely don't want the slow co-routines.
To my knowledge there is no POSIX-standard solution to
this problem, so I compiled my own from different
available sources. You can find the context-manipulating
functions extracted from libtask here:
https://github.com/dosemu2/dosemu2/tree/devel/src/base/lib/mcontext
The functions are:
getmcontext(), setmcontext(), makemcontext() and swapmcontext().
They have the similar semantic to the standard functions with similar names,
but they also mimic the setjmp() semantic in that getmcontext()
returns 1 (instead of 0) when jumped to by setmcontext().
On top of that you can use a port of libpcl, the coroutine library:
https://github.com/dosemu2/dosemu2/tree/devel/src/base/lib/libpcl
With this, it is possible to implement the fast cooperative user-space
threading. It works on linux, on i386 and x86_64 arches.

C++/CLI - Help with pin_ptr

I'm writing a wrapper app that uses some unmanaged functions and I'm using a lot of pin_ptr.
My question is, most of the time I use pin_ptr inside a method call, and the pin_ptr variable is declared also inside the method call. When the code goes our of the method, can I have any problem because it's no longer pinned? Should I move the declaration to a class scope?
thanks!
The only time you need to pin an object on the managed heap is when an unmanaged function or unmanaged code directly accesses the object in memory (such as through a pointer). If when your method exits, nothing is currently accessing the object's memory, it can be unpinned (as long as you pin it again before directly accessing it the next time).

Execution speed of references vs pointers

I recently read a discussion regarding whether managed languages are slower (or faster) than native languages (specifically C# vs C++). One person that contributed to the discussion said that the JIT compilers of managed languages would be able to make optimizations regarding references that simply isn't possible in languages that use pointers.
What I'd like to know is what kind of optimizations that are possible on references and not on pointers?
Note that the discussion was about execution speed, not memory usage.
In C++ there are two advantages of references related to optimization aspects:
A reference is constant (refers to the same variable for its whole lifetime)
Because of this it is easier for the compiler to infer which names refer to the same underlying variables - thus creating optimization opportunities. There is no guarantee that the compiler will do better with references, but it might...
A reference is assumed to refer to something (there is no null reference)
A reference that "refers to nothing" (equivalent to the NULL pointer) can be created, but this is not as easy as creating a NULL pointer. Because of this the check of the reference for NULL can be omitted.
However, none of these advantages carry over directly to managed languages, so I don't see the relevance of that in the context of your discussion topic.
There are some benefits of JIT compilation mentioned in Wikipedia:
JIT code generally offers far better performance than interpreters. In addition, it can in some or many cases offer better performance than static compilation, as many optimizations are only feasible at run-time:
The compilation can be optimized to the targeted CPU and the operating system model where the application runs. For example JIT can choose SSE2 CPU instructions when it detects that the CPU supports them. With a static compiler one must write two versions of the code, possibly using inline assembly.
The system is able to collect statistics about how the program is actually running in the environment it is in, and it can rearrange and recompile for optimum performance. However, some static compilers can also take profile information as input.
The system can do global code optimizations (e.g. inlining of library functions) without losing the advantages of dynamic linking and without the overheads inherent to static compilers and linkers. Specifically, when doing global inline substitutions, a static compiler must insert run-time checks and ensure that a virtual call would occur if the actual class of the object overrides the inlined method.
Although this is possible with statically compiled garbage collected languages, a bytecode system can more easily rearrange memory for better cache utilization.
I can't think of something related directly to the use of references instead of pointers.
In general speak, references make it possible to refer to the same object from different places.
A 'Pointer' is the name of a mechanism to implement references. C++, Pascal, C... have pointers, C++ offers another mechanism (with slightly other use cases) called 'Reference', but essentially these are all implementations of the general referencing concept.
So there is no reason why references are by definition faster/slower than pointers.
The real difference is in using a JIT or a classic 'up front' compiler: the JIT can data take into account that aren't available for the up front compiler. It has nothing to do with the implementation of the concept 'reference'.
Other answers are right.
I would only add that any optimization won't make a hoot of difference unless it is in code where the program counter actually spends much time, like in tight loops that don't contain function calls (such as comparing strings).
An object reference in a managed framework is very different from a passed reference in C++. To understand what makes them special, imagine how the following scenario would be handled, at the machine level, without garbage-collected object references: Method "Foo" returns a string, which is stored into various collections and passed to different pieces of code. Once nothing needs the string any more, it should be possible to reclaim all memory used in storing it, but it's unclear what piece of code will be the last one to use the string.
In a non-GC system, every collection either needs to have its own copy of the string, or else needs to hold something containing a pointer to a shared object which holds the characters in the string. In the latter situation, the shared object needs to somehow know when the last pointer to it gets eliminated. There are a variety of ways this can be handled, but an essential common aspect of all of them is that shared objects need to be notified when pointers to them are copied or destroyed. Such notification requires work.
In a GC system by contrast, programs are decorated with metadata to say which registers or parts of a stack frame will be used at any given time to hold rooted object references. When a garbage collection cycle occurs, the garbage collector will have to parse this data, identify and preserve all live objects, and nuke everything else. At all other times, however, the processor can copy, replace, shuffle, or destroy references in any pattern or sequence it likes, without having to notify any of the objects involved. Note that when using pointer-use notifications in a multi-processor system, if different threads might copy or destroy references to the same object, synchronization code will be required to make the necessary notification thread-safe. By contrast, in a GC system, each processor may change reference variables at any time without having to synchronize its actions with any other processor.

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