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Accession Number:
AD1016836
Title:
Making Big Data, Safe Data: A Test Optimization Approach
Corporate Author:
University of Arizona Tucson United States
Report Date:
2016-06-15
Abstract:
The following report outlines a procedure and algorithm to optimize the potential knowledge gained about a complex system when performing robustness testing and faced with a set of constraints. In particular, this project was catalyzed by the need to put a value on testing. Included with this project report is a proof of concept created in MS Excel utilizing its VBA developer tool. In short, a test network is created by establishing test relationships and then assigning each an expected knowledge value. With these values and an understanding about the relationships between the tests, an optimization about the total potential knowledge of the system can be acquired while minimizing testing costs andor effort.
Descriptive Note:
Technical Report
Pages:
0043
Distribution Statement:
Approved For Public Release;
File Size:
3.35MB
