How Can You Avoid Memory Leaks in Managed Code?
Why Is It Important for Your Application to Prevent Memory Leaks?
In the long run, memory leaks might result in out of memory errors and ultimately about the crash of an application.
What Is a Memory Leak?
When you allocate memory but do not correctly deallocate it, your application will continue to use memory that is no longer necessary. This is known as a memory leak.
This code causes a steadily increasing memory usage that lasts until the application crashes due to an out of memory exception.
Here’s a more real-world software development example of how failing to set the expiration date when configuring a cache item results in memory leak.
How Can You Find a Memory Leak in Your Code?
While some memory leaks are easy to detect, particularly in managed code, they are much more difficult to detect in native memory.
- Use a Memory Profiler to Identify Memory Problems in Your Code
You can use a memory profilers to figure out where the problem is. The profiler will show you where your code is allocating memory, and help you find which parts of your code are not deallocating memory properly.
Visual Studio memory profiler supports Memory Analysis and capture snapshot.
- Windows Task Manager Is Also Useful
If you’re trying to find a memory leak in your code, you can use the Windows Task Manager to see how much memory your process is using. If your process is using a lot of memory and growing over time, then you probably have a memory leak.
Keeping this section small to keep it out of the scope for this article because this section deserves its own article.
How Can You Prevent Memory Leaks?
There is no one-size-fits-all answer to this question. Each application is different and will require a different approach to fix memory leaks. However, some general tips on how to fix memory leaks in managed code include:
- “Using” Statement
The using statement is one method for preventing memory leaks. The using statement makes sure that when an object is no longer required, it is properly disposed of.
- GC.Collect()
Making sure that objects are properly disposed of when they are no longer needed.
You should call GC.Collect() when you are done with an object and you want to make sure that its memory is freed. This forces the garbage collector to run and clean up any unclaimed memory.
The GC runs finalizers on a separate low priority thread, so your finalizers will not necessarily have finished executing when GC.Collect() returns.
Although forcing Garbage Collector to run will release some memory, doing so can also slow down your application, so you should use it cautiously.
Here’s another example of using GC.Collect() with MemoryStream serialization.
- Implementing IDisposable Interface
Use the IDisposable interface to release unmanaged resources when an object is no longer needed.
When an object that implements IDisposable is no longer needed, the Dispose method can be called to release any resources that the object is holding onto.
The IDisposable interface provides a single method, Dispose, which takes no parameters and has no return value. When you implement IDisposable, you should also implement the Finalize method.
When you implement Dispose, you should call the Dispose method of the base class if the base class implements IDisposable.
Avoid Holding On to References to Objects That Are No Longer Needed
This includes both objects in memory and handles to external resources such as files or database connections.
In the example below, the strings are removed from the list when they are no longer needed. This will prevent them from taking up memory unnecessarily.
- Try to Reuse Objects Whenever Possible
Creating and destroying objects uses a lot of memory, so reusing objects can help reduce memory usage.
It is important to release an object back to the system when you are finished with it so that it can be reused. This helps to reduce memory usage in your program.
For example,
- If you have a loop that creates a lot of objects, you can reuse those objects instead of creating new ones each time through the loop.
More on this in section below : Use Object Pooling - If you’re working with a data set that contains a lot of numbers, you might want to use an array to store the numbers. Then, when you’re done with the array, you can clear it and reuse it instead of creating a new array.
A better alternative would be to reuse the list object rather than creating it in each iteration.
Caveat: Avoid Accidental Modification Of Original Object
If you want to reduce memory usage, you can reuse objects. But you have to be careful not to accidentally modify the objects you’re reusing.
For example, let’s say you’re working with a data set full of strings. You might want to use a StringBuilder object to save memory. But if you’re not careful, you might end up modifying the original string.
So when you’re reusing objects, be careful not to modify them.
- Use Objects That Are Specific to the Task at Hand
Not all objects are created equal and some exist solely to help with memory management. When working with large data sets, it’s important to choose data structures that are efficient in terms of memory usage. These objects are designed to use memory efficiently and can help you keep your code clean and free of memory leaks.
A few examples of these types of objects are:
Array; List; Dictionary; HashSet; Stack; Queue; LinkedList
- Use Object Pooling
The Garbage Collector can start to have an impact on performance if there are many objects that are allocated and released quickly. Object pooling may be useful in these scenarios.
The GC runs on a separate thread, so it can happen at any time.
Object pooling is a technique that allows you to reuse existing objects rather than creating new ones. This is particularly useful when working with huge data sets because it reduces the number of objects that must be created.
Instead of frequently creating and destroying objects, object pooling creates a pool of objects that can be reused. When you need an object, you take one from the pool. When you’re finished with it, you return it. This can help to mitigate the GC’s performance impact.
Example code of object pooling in c#:
