Predicting Lifetimes in Dynamically Allocated Memory
Abstract
Predictions oflifetimes of dynamically allocated objects can be used to improve time and space efficiency of dynamic memory manage(cid:173) ment in computer programs. Barrett and Zorn [1993] used a simple lifetime predictor and demonstrated this improvement on a variety of computer programs. In this paper, we use decision trees to do lifetime prediction on the same programs and show significantly better prediction . Our method also has the advantage that during training we can use a large number of features and let the decision tree automatically choose the relevant subset.
Cite
Text
Cohn and Singh. "Predicting Lifetimes in Dynamically Allocated Memory." Neural Information Processing Systems, 1996.Markdown
[Cohn and Singh. "Predicting Lifetimes in Dynamically Allocated Memory." Neural Information Processing Systems, 1996.](https://mlanthology.org/neurips/1996/cohn1996neurips-predicting/)BibTeX
@inproceedings{cohn1996neurips-predicting,
title = {{Predicting Lifetimes in Dynamically Allocated Memory}},
author = {Cohn, David A. and Singh, Satinder P.},
booktitle = {Neural Information Processing Systems},
year = {1996},
pages = {939-945},
url = {https://mlanthology.org/neurips/1996/cohn1996neurips-predicting/}
}