Memory Leak: Causes, Detection, and How to Fix It

Every program we run, big or small, requires memory to process. However, when a program uses memory and neglects to free it after usage, it leads to a memory leak. 

Over time, more memory leaks can result in storage shortages and failure to process upcoming tasks. That’s why detecting and managing memory leaks is crucial to avoid unnecessary errors.

In this article, we’ll explore memory leaks in depth. Let’s get started!

What is a Memory Leak?

Memory leaks occur when a program or application utilizes memory and doesn't free it after usage. By memory, I mean RAM—don't confuse it with hard disk memory.  These leaks gradually pile up, leaving the RAM too full to handle new processes. 

Memory leaks deplete RAM and impact performance by increasing I/O operations. As memory leaks accumulate, the system tries to free up RAM by offloading data to the disk, leading to a surge in disk I/O operations.

Security is also at risk when memory leaks block sensitive data. If information like passwords or encryption keys remains in RAM longer than necessary, it is more vulnerable to attackers.

Examples of Memory Leaks in Popular Programming Languages

To better understand how memory leaks occur, there is nothing better than seeing them in action with some examples. 

Memory leaks in Python

Python relies on reference counting for memory management. It removes an object when its reference count—the number of other objects referring to it—drops to zero. However, it has certain limitations, such as not handling circular references.

For those not familiar with the term, a circular reference occurs when two or more variables refer to each other in a circular fashion. 

For example, object a refers to b, b refers to c, and c refers back to a, which is an endless loop. Here, the reference count can never become 0, and the objects stay in memory forever, leading to memory leaks in Python.

class Node:
    def __init__(self, value):
        self.value = value
        self.next = None 

# Create two nodes
node1 = Node(1)
node2 = Node(2)

# Establish a circular reference
node1.next = node2  # node1 refers to node2
node2.next = node1  # node2 refers back to node1

The above code snippet shows a circular reference. Python has a garbage collector to handle these scenarios. Still, if it fails to handle specific scenarios, like when using global variables, you should manually manage the memory leaks by setting object references no longer in use to None. 

I recommend learning how to write memory-efficient classes in Python to speed up the runtime while consuming fewer resources.

Memory leaks in Java

Java automatically manages memory and doesn’t require explicit help from programmers. However, in cases like improper listener registrations or static references, the garbage collector can fail to free up the space, leading to memory leaks. Let’s see how that can happen:

• An event source generates events, and a listener object registers itself to be notified when those events occur. 
• If the event source holds a strong reference to the listener, the listener cannot be garbage collected as long as the event source is alive, even if the listener is no longer in use. 

In such cases, memory leaks can occur. To avoid them, manually unregister listeners when they are no longer needed.

Another common cause of memory leaks is static variables. Static variables are stored in memory for the entire lifecycle. So, if they reference objects, these objects won’t be garbage collected, even if they are no longer in use, causing memory leaks. For example:

import java.util.ArrayList;
import java.util.List;

public class StaticMemoryLeak {

    // Static list
    private static List<Object> staticList = new ArrayList<>();

    public static void addObject(Object obj) {
        // Add the object to the static list
        staticList.add(obj);
    }

    public static void main(String[] args) {
        for (int i = 0; i < 1000; i++) {
            Object obj = new byte[1024 * 1024];
            // Add the object to the static list
            addObject(obj);
        }
    }
}

In the above program, the variable staticList is declared as a static array, and objects are added to it. The loop runs 1000 times, adding 1 MB of objects each time, resulting in 1 GB of total memory. 

Because the list is static, it will never lose references to the objects as the program is alive. So, the garbage collector cannot delete those objects and 1 GB of memory will be held for the entire lifecycle. This unutilized object memory can cause OutOfMemoryError errors. To fix this, you should explicitly call staticList.clear() and release the memory.

Memory leaks in C/C++

Unlike Java and Python, C++ doesn’t contain automatic garbage collectors. So, memory leaks in C++ occur when programmers allocate memory and forget to deallocate it. For example, 

void sample_leak() { 
    int* ptr = new int(5);
    return; 
}

In the above snippet, the pointer holds the memory address where the integer 5 is stored. When the function ends, the local variable ptr goes out of scope, but the memory allocated on the heap remains, causing a memory leak. 

To prevent this, explicitly add the line delete ptr; to deallocate the memory.

Memory leaks in JavaScript

Javascript has a garbage collector that automatically manages memory. It works in these steps: finding the root, recursively following its path for children, and marking every child as active or inactive. Finally, delete all inactive references. 

However, the garbage collector may fail to release the memory in the following cases:

1. Global variables: When you forget to declare a variable with let, var, or const, Javascript automatically creates it as a global variable. As long as the program runs, global variables remain in memory and are always reachable, preventing the garbage collector from releasing them. 
2. setTimeOut(): The setTimeOut() schedules a callback function to be executed after a certain time. A memory leak can occur when this callback function holds onto the reference for a longer time. Here is an example:

function TimeoutExample() {
  var obj = 10; 
  setTimeout(function() {
    console.log(obj); 
  }, 1000);  // This runs after 1 second
}

TimeoutExample();

In the above code, even after the TimeoutExample() function finishes, the obj still holds a reference until the callback function is executed because the obj is utilized inside the callback function. If this happens with large objects, it leads to serious memory leaks. 

Causes of Memory Leaks

As mentioned, memory leaks can occur in various programming languages for different reasons. Some languages lack automatic garbage collection, while others may fail to release memory in anomalous scenarios. 

Let’s look at some common reasons in detail:

• Unreleased references: Whenever we create objects or variables, the system allocates memory or references for them. Failing to close those references after usage can block the memory. This kind of memory accumulates over time and leads to memory issues. 
• Circular references: Circular references occur when multiple objects reference each other, forming a loop. Even though the objects are no longer in use, they remain referenced by other objects in the cycle, preventing the garbage collector from reclaiming their memory.
• Improper resource management: Sometimes, we don’t make extra effort to properly close database connections, network sockets, or file handles after use. This ignorance can lead to serious memory leak issues. For example, the OS has limited file descriptors to handle open files. If the files are never closed, the OS runs out of file descriptors, preventing the system from opening new files.
• Misuse of static variables: Memory leaks commonly occur due to excessive use of static variables. Since static variables stay alive for the entire lifetime of the program, any objects they reference remain in memory—even when they are not in use. To prevent memory leaks, these objects must be explicitly released or avoid the usage of static variables.
• External libraries and frameworks: Third-party libraries and external frameworks can also introduce memory leaks due to inefficient resource management. Memory leaks occur if they utilize your system resources and fail to release them. 

How to Detect Memory Leaks?

Now that we’ve examined why memory leaks might occur, we’ll discuss some reliable detection methods for spotting and debugging them.

• Manual inspection: Carefully review the code to identify potential causes of memory leaks, such as circular references, static variables, missing deallocation statements, or variables holding references to unused objects.  By thoroughly inspecting these patterns in the code, you can spot the exact issue and address it proactively. 
• Using debugging tools: There are various debugging tools and libraries native to different programming languages for detecting memory leaks. For example, python’s tracemalloc allows us to compare memory snapshots at different points in time and monitor memory allocations between these timeframes.  Moreover, Python’s memory profiler lets us debug each line of code and spot areas with unexpectedly excessive memory usage.
• Monitoring memory usage: Memory monitoring tools proactively monitor memory consumption and spot issues in real time. These tools alert you of critical memory issues and provide relevant logs, along with suggestions on how to fix them. Examples include Valgrind, Paessler, AddressSanitizer, and others. 
• Writing tests for leaks: Consider adding unit tests that detect memory leaks. This way, in addition to functionality and performance issues, memory leaks are detected during development. 
• Writing integration tests: Integration tests should also be used to simulate real-world scenarios and detect potential memory leaks that may arise in production.

Best Practices to Prevent Memory Leaks

Memory leaks are common in applications that rely on memory resources. Here are a few practices you can follow to prevent them. 

Efficient resource management

Try using languages like Java or Python that automatically handle memory using garbage collectors. Otherwise, in languages like C or C++, ensure that all the allocated memory is explicitly deleted. 

Additionally, use constructs like finally blocks or context managers such as with in Python or try-with-resources in Java for efficient resource cleanup. These practices help prevent memory leaks and ensure proper resource management. 

Use weak references

Unlike strong references, weak references do not prevent objects from being garbage-collected. Even if they hold references to the objects, they don’t account for object reachability. So, the garbage collector can reclaim the memory associated with that object. Therefore, use weak references instead of strong ones. 

Frequent code reviews

It’s important to conduct regular code reviews to identify memory leaks. While reviewing the code, look for common patterns like unclosed resources, circular references, global or static variables, and inefficient caching. This way, you’ll quickly find the issue before it impacts your system. 

Conclusion

In this article, we've explored the core aspects of memory leaks, from their causes and examples to detection techniques. We've seen how different scenarios can lead to memory leaks and how you can handle them. Additionally, we've discussed the best practices you should follow to prevent memory leaks in the future.  

As we’ve explored memory leaks across different programming languages, I recommend exploring the following courses to further deepen your understanding:

• Object-oriented programming in Python
• Object-oriented programming in Java