Sandia Corporation

National Technology & Engineering Solutions of Sandia, LLC

Lawrence P Ray

Randolph Brost

David Nikolaus Perkins

Lucas Leighton Nunno

Kenneth Michael Munoz

Bettina K Arpin

Jamie L Coram

Thomas Anthony Artale

David Karmol

Patrick DeMoss

Aaron Easter

Amy Sundermier

William Lawry

Various technologies pertaining to computer-executable instruction sequence forensics are described herein. In a general embodiment, an application development framework supports a function library that includes a plurality of recording functions. Calls to these functions are inserted into source code or bytecode of the computer-executable instruction sequence. The source code is then compiled, resulting in formation of instrumented machine code of the computer-executable instruction sequence. Alternately, the runtime environment interprets instrumented bytecode for the instruction sequence. A processor executes the machine code, and the called functions cause the processor to generate forensic data pertaining to portions of the computer-executable instruction sequence that correspond to locations in the source code where the calls were inserted. An execution instance of the computer-executable instruction sequence is visualized based upon the forensic data.

Method for instruction sequence execution analysis and visualization

Various technologies for facilitating analysis of large remote sensing and geolocation datasets to identify features of interest are described herein. A search query can be submitted to a computing system that executes searches over a geospatial temporal semantic (GTS) graph to identify features of interest. The GTS graph comprises nodes corresponding to objects described in the remote sensing and geolocation datasets, and edges that indicate geospatial or temporal relationships between pairs of nodes in the nodes. Trajectory information is encoded in the GTS graph by the inclusion of movable nodes to facilitate searches for features of interest in the datasets relative to moving objects such as vehicles.

Geospatial-temporal semantic graph representations of trajectories from remote sensing and geolocation data

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Albuquerque, NM, United States of America

Lawrence P Ray