Intelligent Reasoning on the Impact of Changes to System Models and Requirements

Award Information
Agency: Department of Defense
Branch: Missile Defense Agency
Contract: HQ0147-13-C-7702
Agency Tracking Number: B2-1943
Amount: $999,823.00
Phase: Phase II
Program: STTR
Awards Year: 2013
Solitcitation Year: 2011
Solitcitation Topic Code: MDA11-T003
Solitcitation Number: 2011.B
Small Business Information
Discovery Machine Incorporated
454 Pine Street, Suite 1C, Williamsport, PA, -
Duns: 128516114
Hubzone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Todd Griffith
 (570) 916-2056
Business Contact
 Anna Griffith
Title: CEO
Phone: (570) 916-6044
Research Institution
 Stevens Institute
 Robert Cloutier
 Castle Point on the Hudson
Hoboken, NJ, 07030-
 (856) 470-0458
 Nonprofit college or university
As complex systems develop, there are inevitably changes to requirements and the system models as the team members formulate a more clear understanding of the customer needs and possible solutions. Often these changes are not coordinated since it is difficult to predict how one change may affect another and current requirements management and system modeling tools don't provide the type of two way traceability required. What ends up happening is that the design proceeds to the point where conflicts arises and certain requirements cannot be met. At that point, design changes are more costly and can derail an otherwise productive design team. We propose an intelligent software system which can aid in understanding the impacts of changes to requirements or system architecture and can identify nuanced interactions between them that only expert system engineers would. The proposed system is capable of understanding both system requirements and system architectures in a way which allows inferencing on proposed changes. The system uses ontological reasoning in a flexible way including potential interfaces to external ontology sources as well as a new context specific inferencing approach which leverages information about the specific issue being addressed to focus the ontological reasoning for improved results.

* information listed above is at the time of submission.

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