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Category: Memory

Monitoring memory use in a JNI DLL called from Java

By , May 8, 2010 1:35 pm

Java is a garbage collected language that allows you to extend the language with code written in C and C++.

Given that the extensions are written in C or C++ the normal tools for monitoring Java memory usage will not report the C/C++ memory usage. So how do you monitor the memory usage of these JNI extensions when called from Java? This article is going to explain how to do this task.

Building an example JNI test

The first thing to do is to create an example to work with. The post Creating a JNI example for testing describes how to create a JNI example (both Java code and JNI C/C++ code, with downloadable source and project files). Please download the example code and build the example.

Monitoring JNI Memory

Monitoring memory in JNI extensions is straightforward. Java programs are executed by running a Java Virtual Machine (JVM). These are typically named java.exe, javaw.exe, jre.exe, jrew.exe. We can just launch java.exe with a C/C++ memory leak detection software tool and monitor the results. For this example we are going to monitor java with C++ Memory Validator. The image below shows the launch dialog (note if you are using Memory Validator for the first time you will be using the launch wizard, which is slightly different)

Memory Validator launch dialog showing launch of Java application

Items to note:

  • Application is set to the path to java.exe. C:\Program Files (x86)\Java\jdk1.5.0_07\bin\java.exe
  • Arguments is set to the name of the class to execute. Main
  • Startup directory is set to the directory containing the class to execute (and the native DLL to monitor). E:\om\c\memory32\testJavaJNI
  • If you wish to set the CLASSPATH you can set it in the Environment Variables part of the launch dialog. If you do not set the CLASSPATH here (as in this example) the CLASSPATH will be taken from the inherited environment variables of Memory Validator’s environment. For this example CLASSPATH is set in the global environment variables and thus does not need to be set on the launch dialog.

Click Go! to start the Java program. Java is started, Memory Validator monitors the application and records all memory allocations and deallocations. Any memory not deallocated by the end of the program is a leak.

JNI Leaks with no filtering

As you can see from the screenshot above, there is a quite a bit of memory left over after a simple run of this example Java program which does very little except load a native extension that prints Hello World! twice and deliberately leaks one 20 byte chunk of memory. The example image indicates there are 857 items, some of which are handles, the remainder C/C++ memory allocations. There are 3493 events. The memory leak we are interested in occurs at event 2985.

Clearly this is inefficient. To find memory leaks in your code you are going to have to wade through all the noise of the memory allocations made by Java and the JVM. There must be a better way!

There is. We’ll focus only on the native DLL that prints the Hello World! messages. Open the settings dialog and go to the Hooked DLLs section.

Setting up DLL filters to focus on the JNI DLL

  • Select the second radio box to indicate that only the DLLs we list will be monitored.
  • Now click Add Module… and select the HelloWorldImp.dll.
  • Click OK.

Memory Validator is now configured to monitor only HelloWorldImp.dll for memory and handle allocations.
Relauch the java application with these new settings.

JNI Leaks with DLL filtering

As you can see from the picture above much less data is collected. A total of 54 events compared to the previous session’s 3493 events. This is much more managable.

The list of items Memory Validator reports for this run contains only 11 events. This reduced amount makes it very easy to identify errors in the DLL.

  • 8 events are DLL loads (MV always reports DLL loads regardless of settings)
  • A one time, per-thread, buffer allocation inside printf
  • A memory leak that is deliberately present in the example JNI code
  • The final event is the status information for the application at the end of its run

If you don’t wish to see the DLL loads you can filter them out with a global, session or local filter.

Detail view of source code of memory leak in JNI code

The image above shows the source code of the location of the leaking memory in the JNI extension.


Monitoring memory allocations in JNI Dlls called from Java is a straightforward task.

Things to remember:

  • Ensure your JNI DLL is compiled with debugging information and linked with debugging information.
  • Ensure your JNI DLL debug information is present (put the PDB file in the same directory as the DLL).
  • Ensure your CLASSPATH is set correctly so that when Memory Validator starts your Java application the correct CLASSPATH is used.

What is the difference between a page and a paragraph?

By , March 8, 2010 11:40 am

In the real world we all know that pages contain paragraphs and that paragraphs are full of sentences created from words.

In the world of Microsoft Windows Operating Systems it is somewhat different – paragraphs contain pages!

In this article I’m to going to explain what a page is and what a paragraph is and how they relate to each other and why this information can be useful helping to identify and resolve certain memory related bugs.

Virtual Memory Pages
A virtual memory page is the smallest unit of memory that can be mapped by the CPU. In the case of 32 bit x86 processors such as the Intel Pentium and AMD Athlon, a page is 4Kb. When you make a call to VirtualProtect() or VirtualQuery() you will be setting or querying the memory protection for sizes that are multiples of a page.

The size of a page may vary from CPU type to CPU type. For example a 64 bit x86 CPU will have a page size of 8Kb.

You can determine the size of a page by calling GetSystemInfo() and reading the SYSTEM_INFO.dwPageSize value.

Virtual Memory Paragraphs
A virtual memory paragraph is the minimum amount of memory that can be commited/reserved using the VirtualAlloc() call. On 32 bit x86 CPUs this value is 64Kb (0x00010000). If you have ever used the debugger and looked at the load addresses of DLLs in the Modules list you may have noticed that DLLs always load on 64Kb boundaries. This is the reason – the area a DLL is loaded into is initialised by a call to VirtualAlloc to reserve the memory prior to the DLL being loaded.

Loaded Modules

You can determine the size of a paragraph by calling GetSystemInfo() and reading the SYSTEM_INFO.dwAllocationGranularity value.

Given these values, you can see that (on 32 bit 86 systems) a virtual memory paragraph is composed of 16 virtual memory pages.

How can I use this information?
If you are using VirtualAlloc() it is important to know the granularity at which the allocations will be returned. This is the size of a paragraph. This information is fundamental in deciding how you would implement a custom heap. You know there are fixed boundaries at which your data can exist. You can enumerate the list of possible paragraph locations very quickly (there are 32,768 possible locations in a 2GB space, as opposed to 2 billion locations if the paragraph could start anywhere).

Custom heaps
If you are writing a custom heap, a key indicator to keep track of is memory fragmentation and memory utilisation. Knowing your paragraph and page sizes you can inspect how each page and each paragraph of memory are used by the application and the custom heap to determine if there is wastage, what wastage there is and what form the wastage takes. This information could lead you to modify your heap algorithm to use pages differently to reduce fragmentation. See Delete memory 5 times faster for one simple technique, using HeapAlloc, the same principles apply here.

Loading large data files
Another use for this information is finding out why a certain large file will not load into memory despite Task Manager saying that you have 2GB of free memory. It is not uncommon to find a forum posting somewhere from someone that has a large image file (a satellite phote, MRI scan, etc) that is about 1GB in size. They wish to load it into memory, do in-memory processing on it, save the results, discard the memory then repeat the process, often for numerous images.
Typically on the third attempt to load a large file, the file will not load and the forum poster is left very confused.

The typical implementation is to allocate space for the large file using a call such as malloc() or operator new(). Both of which use the C runtime heap to allocate the memory.

The principle seems fine, but the problem is caused by memory fragmentation which results in a less accessible, totally usable, free space because the remaining free space blocks are separated into a many smaller regions, most of which are smaller than any forthcoming large allocation required by the application. Without the information about where pages and paragraphs are situated, how big they are and what their status is, identifying the cause of this failure could be very time consuming. Once you know the cause, you can think about allocating and managing your memory differently and prevent the bug from happening in the first place.

For situations like these, using HeapAlloc() with a dedicate heap (created using HeapCreate()) or even just directly using VirtualAlloc() will most likely lead to superior results than using the C runtime heap.

A first step in understanding such bugs is to be able to visualize the memory and to also inspect the various page and paragraph information.

To aid in these tasks we have just added a VM Pages view and VM Paragraphs view to VM Validator to make identifying such issues easier. VM Validator is a free download.

Memory Validator will also be updated with a VM Paragraphs view in the next release (Memory Validator already has a more detailed VM Pages view).

Thank you to Blake Miller of Invensys for suggesting an alternative wording for one paragraph of this article.

Delete memory 5 times faster

By , March 2, 2010 12:56 pm

Memory management in C and C++ is typically done using either the malloc/realloc/free C runtime functions or the C++ operators new and delete. Typically the C++ operators call down to the underlying malloc/free implementation to do the actual memory allocations.

This is great, its useful, it works, BUT it puts all the allocations in the same heap. So when you come around to deallocating the heap manager will need to take into account all the other objects and allocations that are also in the heap but unrelated to the data you are deallocating. That adds overhead to the heap manager, causing memory fragmentation and slower heap management.

There is a different way you can handle this situation – you can use your own heap for a given group of allocations.

	HANDLE	hHeap;

	hHeap = HeapCreate(0, 0x00010000, 0); // 64K growable heap

The downside to this is that you have to remember to use the correct allocators and deallocators for these objects and not to use malloc/free etc. You can mitigate this in C++ by overriding new/delete to use your own heap.

void *myClass::operator new(size_t size)
	return HeapAlloc(hHeap, 0, size);

void myClass::operator delete(void *ptr)
	HeapFree(hHeap, 0, ptr);

The upside to this technique is that you can delete all your deallocations in one call by deleting the heap and not bothering with deleting individual allocations. This is also about 5 times faster.

Old style:

	for(i = 0; i < count; i++)
		HeapFree(hHeap, 0, ptrs[i]);

New style:

	hHeap = NULL;

There is another benefit to this technique: By deleting the heap and then re-creating a heap for new allocations you remove all fragmentation from the heap and start the new heap with 0% fragmentation.

HeapDestroy timing demonstration

Download the source of the demonstration application. Project and solution files for Visual Studio 6.0 and Visual Studio 2008 are provided.

We use this technique for some of our tools where we want a high performance heap and zero fragmentation.

You will also want to ensure that whatever software tool you are using to monitor memory allocations will mark all entries in a heap that is destroyed as deallocated.

Support for MinGW and QtCreator

By , December 4, 2009 5:01 pm

Everyone uses Visual Studio to write C and C++ software don’t they? Yes! you all chorus. Apart from some guys at the back who like to use gcc and g++. They use MinGW when working on Windows. And they may even use Emacs, or perish the thought, vi!

Up until now we haven’t been able to cater to the needs of gcc and g++ users. We’d get email every month asking when we were going to support MinGW or if we supported QtCreator. It was frustrating admitting we couldn’t support that environment. Even more so as the founders of Software Verification wrote large GIS applications using gcc and g++ back in the early 1990s.

During October we integrated support for MinGW and QtCreator into Coverage Validator, Memory Validator, Performance Validator and Thread Validator. Both COFF and STABS debug formats are supported, which provides some flexibility in how you choose to handle your symbols.

We’ll continue to add support for additional compilers to our tools as long as there is interest from you, the kind people that use our software tools.

Got a crash with a strange pointer value?

By , December 4, 2009 5:00 pm

Ever had a crash with a pointer value of 0xcdcdcdcd or 0xdddddddd or 0xfeeefeee?

You have? Sooner or later when you work with C or C++ you’ll bump into one of these crashes. You will no doubt try to reproduce the crash and thats when you’ll probably notice this unusual value has repeated itself. Perhaps the value is significant, perhaps it is telling you something?

I’ve has just written an article about the unusual bit patterns you can find in variables on the stack or in the various Win32 heaps or in the CRT heap. The article closes with some suggestions on how to prevent these errors from occurring.

A few minutes spent reading about the bit patterns may help you see these bit patterns less frequently and dig you out of any 0xfeeefeee hole you may have fallen into.

New .Net software tools

By , January 22, 2007 5:14 pm

We’ve spent the last few years creating our software tools for C++, Java and all the funky scripting languages that are now getting the recognition they deserve (Python, Ruby, JavaScript, etc).

During all this time we’ve have been asked if we have .Net versions of our tools, nearly always a question related to C#. We had to answer “No, but we will have .Net versions at some time in the future.”. That time has come. We now have .Net versions of Memory Validator and Performance Validator available as beta products.

Users of our popular Memory Validator software tool (for C++, Delphi…) will notice that the UI for .Net is quite different. This is because detecting memory leaks in garbage collected environments requires different approaches to collecting and analysing data. We have some innovative ideas in .Net Memory Validator, including the Allocations view, which provides a breakdown of objects allocated per function name; the Objects view, which provides a breakdown of objects allocated per object type; the Generations view, which provides an easy to read display of how many objects allocated per generation per object type. You can easily spot the trend graph of object usage and determine which objects are climbing or falling. A reference view allows you to view the object heap as a graph. The hotspots, memory, analysis, virtual and diagnostic tabs will be familiar to users of the original Memory Validator for C++.

.Net Memory Validator has the same user interface features you will find on our other Memory Validator products for other garbage collected languages (Java, JavaScript, Python, Ruby, etc) making ease of use when switching languages a doddle. As with all our products the .Net version, although different under the hood has the same team behind it. You are probably familiar with the case of a company creating a software tool for language X and then porting it support language Y, but the language Y version is lacking because it was a ground up rewrite, often by people unfamiliar with the language X version. This leads to incompatiblities, differnt UI behaviour, new bugs. That isn’t how we create our new language versions. Each version has its own code base, which allows for the radical under the hood changes to accomodate each language. But it has the same team and keeps the same user interface elements where applicable. So even if the code under the hood changes you get the same experience regardless of language.

This also allows our bug fixing to be improved. Many bugs from one version of a product apply to our other language versions. Thus if we find and fix a bug in say Java Memory Validator that bug fix can often be applied to JavaScript Memory Validator, Python Memory Validator, Ruby Memory Validator and .Net Memory Validator, etc. And our customers usually get the bug fix the very next day. This development method has been carried into the .Net line of software tools.

.Net Performance Validator continues this trend of the same user interface. If you know how to use any of our Performance Validator products (including the C++ version) you will know how to use .Net Performance Validator. Its that easy.

The callstack view provides a real time insight onto where a particular thread is running. Raw Statistics lets you inspect the raw data collected about performance and Statistics lets you inspect this data in a more orderly fashion. Relations provides the same information but allows you to view which function was called from which function. Call Tree provides the a call tree which you can expand and contract to view the performance data. Call Graph provides this information as a graph with each function listed as infrequently as possible. Call Graph is a very useful way to find an expensive function, then right click, choose goto Call Tree Node and the first node in the call tree that relates to the same node in the Call Graph expands with the node highlighted and source code displayed if available. Analysis allows complex queries onto the data and the diagnostic tab provides information about the instrumentation process.

Cheers for now, we have more .Net tools to work on.

Linux? MacOS X? Not right now, but some time in the future. Where have you read that before? 🙂

Ruby Memory Tracking API

By , December 1, 2006 5:15 pm

To provide the memory tracking, heap dump and object referencing facilities in Ruby Memory Validator we had to reverse engineer some hooks into the Ruby executable. This is not the easiest task in the world and beyond the abilities of anyone with less than a cursory knowledge of x86 assembly and Win32 hooking techniques.

To make it easier for this work to be done, to make it more reliable and to make these hooks available for those that just want to mainly work with Ruby and write a little C (as opposed to getting immersed in PE formats, x86 assembly and so on) we have created an extension to Ruby that provides for memory allocation and deallocation tracking, heap dumping and object reference determination. The extension is in the form of a simple C API.

You can read about this work, download the source code and download a working Ruby DLL with the extra code here.

If you have any comments, please contact support at the usual address.

Firefox 2.0 support

By , November 8, 2006 5:29 pm

We’ve just released the latest versions of all our JavaScript tools for flow tracing, code coverage, performance profiling and memory profiling. The latest versions support Firefox 2.0 as well as Firefox 1.5 and 1.0 and Flock 0.7.

Another improvement is that the JavaScript tools automatically prevent any installed debuggers from overriding the hooks required to make the JavaScript tool work. This should remove a regular source of confusion for those trying to use our tools when they have a JavaScript debugger installed.

Finally we’ve improved the JavaScript parsing and also the source code colouring.

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