Microsoft Technology Licensing, LLC

Matthew A Block

Ovidiu G Temereanca

Calin Negreanu

Daniel Joseph Mastrian, Jr

Nathan Cornillon

Identification of software configuration data. One or more binary files from a memory area in a computing device are identified. The binary files include information relating to execution of software. One or more strings from the identified binary files are extracted according to a rule. The rule defines requirements associated with the configuration data. A list of strings is generated from those extracted one or more strings, each of the strings in the generated list refers to configuration data in the memory area. The configuration data may be transferred to another machine, backed up, or used for informational purposes.

Identification of software configuration data

Identification of software program data and configuration data. A set of installation data is identified from an installation log. A set of deduced data is determined based on the identified set of installation data, using various algorithms and heuristics. A set of program data is organized as a function of the starting and deduced data, said program data constituting all data belonging to the software. The software is applied from the source computing device to a destination computing device as a function of the organized set of program data such that the application process mimics the actions of the software's installer so that the software functions seamlessly on the destination computing device.

Identification of software execution data

The present invention extends to methods, systems, and computer program products for recognizing input gestures. A neural network is trained using example inputs and backpropagation to recognize specified input patterns. Input gesture data is representative of movements in contact on a multi-touch input display surface relative to one or more axes over time. Example inputs used for training the neural network to recognize a specified input pattern can be created from sampling input gesture data for example input gestures known to represent the specified input pattern. Trained neural networks can subsequently be used to recognize input gestures that are similar to known input gestures as the specified input pattern corresponding to the known input gestures.

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Redmond, WA, United States of America

Matthew A Block