21.3. Techniques

This describes some of the techniques I have found useful. Bear in mind:

  • Tracking down memory leaks can take a long, long time.

  • Every memory leak is its own special little snowflake! So what works will be situation specific.

21.3.1. High Level

It is worth spending a fair bit of time at high level before diving into the code since:

  • Working at high level is relatively cheap.

  • It is usually non-invasive.

  • It will quickly find out the scale of the problem.

  • It will quickly find out the repeatability of the problem.

  • You should be able to create the test that shows that the leak is firstly not fixed, then fixed.

At the end of this you should be able to state:

  • The frequency of the memory leak.

  • The severity of the memory leak.

Relevant quote: “Time spent on reconnaissance is seldom wasted.”

21.3.1.1. Using Platform Tools

The high level investigation will usually concentrate on using platform tools such as builtin memory management tools or Python tools such as pymentrace’s pymemtrace Process or psutil will prove useful.

21.3.1.2. Specific Tricks

TODO: Finish this.