Making Big Data, Safe Data: A Test Optimization Approach

Report Number: UOA-TE-16-148

Series: Test and Evaluation (T&E)

Category: Test and Evaluation (T&E)

Report Series: Sponsored Reports

Authors: Ricardo Valerdi

Title: Making Big Data, Safe Data: A Test Optimization Approach

Published: 2016-06-01

Sponsored By: Acquisition Research Program

Status: Published--Unlimited Distribution

Research Type: Other Research Faculty

Full Text URL: http://acquisitionresearch.net/files/FY2016/UOA-TE-16-148.pdf

Keywords: Big Data, contractor performance

Abstract:

This 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 b e acquired while minimizing testing costs and/or effort.