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Thursday, October 3, 2013

Tackling memory leaks with machine learning

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In our last week’s upgrades we added something you most likely have not even noticed. Namely – the possibility to improve Plumbr algorithms. If this sounds like a mystery, bear with me and I will demonstrate the value of the change by letting you to take a peek at Plumbr internals.

As you might recall, Plumbr constantly monitors all object creation and destruction events and looks for anomalies. The anomaly detection magic is based on a dataset containing more than a million memory snapshots that we use to train our algorithms on.

In this post we will focus on the “magic” part. In a simplified form, we can say that Plumbr contains an algorithm that observes the trends of dozens of different variables and decides whether particular symptoms indicate presence of a memory leak or not.

Read more here

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