Memory leaks can arise in various ways depending on how they are introduced, but they all exhibit a similar behavior, which ultimately makes them a performance issue.
To demonstrate, consider a simplified example involving a process. Imagine you're testing a function on a web server, where the process executes a computation and returns a result. During this, it requests a chunk of memory. However, due to a bug, the process mistakenly requests the same chunk twice. When the result is returned, it only releases one chunk, leaving the other unreleased.
Each time this function is called, the same issue occurs, and over time, the process consumes more of the host machine’s available memory, leading to a "memory leak." As this continues, the host system is impacted because the memory that should have been freed is never returned, causing the process to consume excessive resources until it either crashes or is forcefully terminated.
In my experience, these types of memory leaks are often uncovered during load testing. A function may return correct results and pass unit tests, which only evaluate a small number of cases. However, when this function is executed tens or hundreds of thousands of times, the memory issue becomes more evident, as it continuously reserves memory that is never released.
Identifying memory leaks is not always straightforward. There are valid scenarios where a process may reserve memory and not release it immediately. Unfortunately, it's not as simple as releasing every bit of memory as soon as it's used.
Although this is a simplified example, it reflects the typical pattern I associate with a memory leak: memory is allocated but not properly released, eventually leading to performance degradation.
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