Debugging strategy to find the cause of bad_alloc_问答_开发者

I have a fairly serious bug in my program - occasional calls to new() throw a bad_alloc.

From the documentation开发者_如何学Python I can find on bad_alloc, it seems to be thrown for these reasons:

When the computer runs out of memory (which definitely isn't happening, I have 4GB of RAM, program throws bad_alloc when using less than 5MB (checked in taskmanager) with nothing serious running in the background).
If the memory becomes too fragmented to allocate new blocks (which, again, is unlikely - the largest sized block I ever allocate would be about 1KB, and that doesn't get done more than 100 times before the crash occurs).

Based on these descriptions, I don't really have anywhere in which a bad_alloc could be thrown.

However, the application I am running runs more than one thread, which could possibly be contributing to the problem. By testing all of the objects on a single thread, everything seems to be working smoothly. The only other thing that I can think of that is going on here could be some kind of race-condition caused by calling new() in more than one place at the same time, but I've tried adding mutexes to prevent that behaviour to no effect.

Because the program is several hundred lines and I have no idea where the problem actually lies, I'm not sure of what, if any, code snippets to post. Instead, I was wondering if there were any tools that will help me test for this kind of thing, or if there are any general strategies that can help me with this problem.

I'm using Microsoft Visual Studio 2008, with Poco for threading.

bad_alloc can also be thrown when you have a bug that is overwriting the pointers that the heap uses to manage the pool of memory that it uses to allocate from.

The most common cause of that is that you are writing past the end of an allocated block of memory, (or before the start, but that's less common). Almost as common is writing to a memory block after it has been freed. This is called heap corruption.

Also, I should note, a 32 bit process in Windows has at most 2GB of address space (3GB for large-address-aware programs). This is regardless of how much RAM you have installed, the memory is virtual, and allocations don't fail until you run out of address space, even if you only have 1GB of RAM.

Here is a good discussion of memory corruption in C++ http://www.eventhelix.com/RealtimeMantra/Basics/debugging_software_crashes_2.htm

Another possible problem is that, while you mention that the program is using less than 5MB, you don't mention how much space it's trying to allocate. You could have some race condition that's corrupting the value that you use to determine the allocation size, and it could be trying to allocate 37TB or somesuch nonsense.

Not particularly likely, I suppose, but worth checking.

Few clarifications:

Every process in windows gets 4GB virtual memory, out of which 2GB is for user space and remaining for kernel space. The 4GB of RAM won't contribute to the virtual memory but it is for physical memory.

In the 2GB memory, all EXE, DLL gets loaded and hardly 1.6 - 1.7GB available for memory allocation. In this memory if there is no contiguous memory for allocation then the memory allocation fails.

bad_alloc can be thrown by other code as well.

I've seen it used by a limiting memory pool designed for use with STL containers. When the size limit was hit, it threw bad_alloc and the software just had to handle it.

I've actually had this problem before and it was fixed by cleaning and rebuilding the project. Always worth a try when you have weird behaviour (unless it is a huge project that takes hours to compile).

A strategy for debugging this would be to set a catchpoint in the debugger. In gdb one would say “catch throw” to ask the debugger you stop whenever the program throws an exception. You can refine that to catch only std::bad_alloc if the program throws and catches lots of exceptions in its normal course of business. The debugger will stop inside whichever allocation function generates std::bad_alloc, allowing you to poke around. In this case, you would quickly learn that number of bytes requested is not what you expect.