Isolating Memory Leaks

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A memory leak in software, including Gramps, is like a little drip in a faucet that you can't turn off.

When a program runs, it needs a place to store information temporarily, called memory. A memory leak happens when the program doesn't clean up after itself and keeps using more and more memory but never gives it back when it's done. Over time, this can slow down the program or even make it crash because it's using up too much memory. It is like a room filling up with water slowly because of a leaky faucet.

It is important to fix these leaks to keep the program running smoothly.

Imagine if you're using a bucket to collect water from a leaky roof - if you don't empty the bucket, it will fill up. In this case, the "bucket" is the computer's memory, and if Gramps has a memory leak, it's like the "roof" is leaking and filling up that "bucket" more than it should.

So, spotting memory leaks in tools like "Uncollected Objects" or in Task Manager involves watching for signs that Gramps isn't cleaning up memory properly, causing it to use more and more memory as you use the program. It's important to fix these leaks to keep Gramps running smoothly.

Memory Leak Isolation Workflow

Reproduce the Issue

Consistently replicate the memory leak by identifying specific actions or conditions leading to increased memory usage.

Using Gramps tools

In Gramps, the "Uncollected Objects" plugin is designed to help find potential memory leaks. (Superficially described in the Wiki's internal Gramplet page at Uncollected Objects) If there are memory leaks in Gramps or any software, this tool could show them.

When using the "Uncollected Objects" plugin, it might show certain parts of Gramps that are not being properly cleaned up in the computer's memory. These could be like hints that there might be a memory leak. It's like finding spots where water might be leaking in your roof.

Using system tools

You might notice Gramps using more and more memory over time if there's a memory leak.

• In MS Windows, use Task Manager (accessible via Ctrl + Shift + Esc or Ctrl + Alt + Delete, then select 'Task Manager').
• For Linux, use the Linux system monitor (e.g., 'htop' command in the terminal or 'gnome-system-monitor' from the applications menu).
• For macOS, use the Activity Monitor found in the 'Utilities' folder within 'Applications'.

Use Profiling Tools

Utilize memory profiling tools like <a href="#memory-profiler">Python's memory_profiler</a> to monitor memory usage during program execution.

Memory Profiler

Memory profiler is a tool to monitor memory usage in Python programs, helping to identify memory leaks and performance bottlenecks.

Analyze the Code

Review the code in the areas where the memory leak is suspected. Look for instances where memory is allocated (e.g., object creation) and ensure that there are corresponding deallocations (e.g., object destruction or garbage collection).

Check for Cycles and References

In languages with manual memory management or cyclic reference possibilities (e.g., Python), investigate if there are circular references or objects holding references to each other, preventing proper deallocation.

Inspect Resource Release

Pay close attention to any resources like file handles, database connections, or network sockets that might not be properly released. Ensure that these resources are being closed or released after use.

Monitor Event Subscriptions

In systems using event-driven programming, ensure that event subscriptions are properly managed and unsubscribed when no longer needed. Events can inadvertently keep objects in memory.

Examine Large Data Structures

If your program uses large data structures, check if they are being managed efficiently. Sometimes, inefficient data structures or improper use of collections can lead to memory issues.

Validate External Libraries

If your code relies on external libraries, ensure that you're using them correctly and that they are not causing memory leaks themselves.

Perform Code Reviews

Involve fellow developers for code reviews. Fresh perspectives can often catch issues that might have been overlooked.

Test with Smaller Inputs

Simplify the program inputs or conditions to see if the memory leak is related to the data being processed.

Iterate and Debug

Make necessary changes, fixes, and retest to check if the memory leak is resolved. Repeat as needed.

See Also

• "Memory Leaks … Finally gone?" Wednesday, 3 Nov 2010 by Benny
• "Possible GDI Object Leak AIO-5.2.0-r1-54cc357"