Microsoft Technology Licensing, LLC

Sandeep Repaka

Brett Owens Simons

Yatpang Cheung

Edmund Chi Man Tse

Jakob Frederik Lichtenberg

Hyuk Joon Kwon

Sebastian Lerner

Matthew John Woolman

Andrew Meyer Kluemke

Swati Kanchan

Rule induction is used to produce human readable descriptions of patterns within a dataset. A rule induction algorithm or classifier is a type supervised machine learning classification algorithm. A rule induction classifier is trained, which involves using labelled examples in the dataset to produce a set of rules. Rather than using the rules/classifier to make predictions on new unlabeled samples, the training of the rule induction model outputs human-readable descriptions of patterns (rules) within the dataset that gave rise to the rules (rather than using the rules to predict new unlabeled samples). Parameters of the rule induction algorithm are tuned to favor simple and understandable rules, instead of only tuning for predictive accuracy. The learned set of rules are outputted during the training process in a human-friendly format.

Rule induction to find and describe patterns in data

Described are examples for tracking memory usage of a driver. A memory allocation request related to the driver to allocate a portion of memory for the driver can be traced in a kernel mode of an operating system. One or more associated allocation parameters can be recorded, and an allocation history of the driver over a period of time can be reported during execution of the driver and based on the one or more allocation parameters indicated by the memory allocation request.

Advanced memory tracking for kernel mode drivers

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Issaquah, WA, United States of America

Sandeep Repaka