Using Memory Profilers Memory profilers are tools that can monitor memory usage and help detect memory leaks in an application. Profilers can also help with analyzing how resources are allocated within an application, for example how much memory and CPU time is being used by each method.
The best approach to checking for the existence of a memory leak in your application is by looking at your RAM usage and investigating the total amount of memory been used versus the total amount available. Evidently, it is advisable to obtain snapshots of your memory's heap dump while in a production environment.
If you have implemented a very long-running or infinite running thread that is not doing anything and it holds on to objects, you can cause a memory leak as these objects will never be collected. The fix for this is to be very careful with long-running threads and not hold on to objects not needed.
I use Scitech's MemProfiler when I suspect a memory leak.
So far, I have found it to be very reliable and powerful. It has saved my bacon on at least one occasion.
The GC works very well in .NET IMO, but just like any other language or platform, if you write bad code, bad things happen.
Just for the forgetting-to-dispose problem, try the solution described in this blog post. Here's the essence:
public void Dispose ()
{
// Dispose logic here ...
// It's a bad error if someone forgets to call Dispose,
// so in Debug builds, we put a finalizer in to detect
// the error. If Dispose is called, we suppress the
// finalizer.
#if DEBUG
GC.SuppressFinalize(this);
#endif
}
#if DEBUG
~TimedLock()
{
// If this finalizer runs, someone somewhere failed to
// call Dispose, which means we've failed to leave
// a monitor!
System.Diagnostics.Debug.Fail("Undisposed lock");
}
#endif
We've used Ants Profiler Pro by Red Gate software in our project. It works really well for all .NET language-based applications.
We found that the .NET Garbage Collector is very "safe" in its cleaning up of in-memory objects (as it should be). It would keep objects around just because we might be using it sometime in the future. This meant we needed to be more careful about the number of objects that we inflated in memory. In the end, we converted all of our data objects over to an "inflate on-demand" (just before a field is requested) in order to reduce memory overhead and increase performance.
EDIT: Here's a further explanation of what I mean by "inflate on demand." In our object model of our database we use Properties of a parent object to expose the child object(s). For example if we had some record that referenced some other "detail" or "lookup" record on a one-to-one basis we would structure it like this:
class ParentObject
Private mRelatedObject as New CRelatedObject
public Readonly property RelatedObject() as CRelatedObject
get
mRelatedObject.getWithID(RelatedObjectID)
return mRelatedObject
end get
end property
End class
We found that the above system created some real memory and performance problems when there were a lot of records in memory. So we switched over to a system where objects were inflated only when they were requested, and database calls were done only when necessary:
class ParentObject
Private mRelatedObject as CRelatedObject
Public ReadOnly Property RelatedObject() as CRelatedObject
Get
If mRelatedObject is Nothing
mRelatedObject = New CRelatedObject
End If
If mRelatedObject.isEmptyObject
mRelatedObject.getWithID(RelatedObjectID)
End If
return mRelatedObject
end get
end Property
end class
This turned out to be much more efficient because objects were kept out of memory until they were needed (the Get method was accessed). It provided a very large performance boost in limiting database hits and a huge gain on memory space.
You still need to worry about memory when you are writing managed code unless your application is trivial. I will suggest two things: first, read CLR via C# because it will help you understand memory management in .NET. Second, learn to use a tool like CLRProfiler (Microsoft). This can give you an idea of what is causing your memory leak (e.g. you can take a look at your large object heap fragmentation)
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