My thesis progress presentation

This document discusses using machine learning to improve garbage collection in Java. It explores using machine learning to predict whether an object will survive long enough to be promoted to the older generation of memory. The author conducted experiments using mutual information to determine which object attributes, like allocation site and size, correlate with object lifetime. Based on the results, the author proposes using a decision tree model for classification to predict object tenuring. Future work would involve offline and possibly online training of the decision tree to integrate the predictions into the Java runtime's garbage collection. The experiments found mutual information a useful technique for analyzing object lifetime heuristics and uncovered new attributes related to object type that correlate with lifetime.