USA flag logo/image

An Official Website of the United States Government

Cognitive Techniques for Analysis of Complex Software Systems

Award Information

Agency:
Department of Defense
Branch:
Air Force
Award ID:
78867
Program Year/Program:
2006 / SBIR
Agency Tracking Number:
F061-067-2289
Solicitation Year:
N/A
Solicitation Topic Code:
N/A
Solicitation Number:
N/A
Small Business Information
GrammaTech, Inc.
531 Esty Street Ithaca, NY 14850-4201
View profile »
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No
 
Phase 1
Fiscal Year: 2006
Title: Cognitive Techniques for Analysis of Complex Software Systems
Agency / Branch: DOD / USAF
Contract: FA8750-06-C-0144
Award Amount: $100,000.00
 

Abstract:

The problem of finding flaws in large complex software systems is acute and getting worse because many systems are employing new cognitive techniques to increase their capabilities. Such techniques are typically highly dynamic and concurrent, which increases the complexity of the system and makes it correspondingly harder to debug. Traditional approaches fail because they are incapable of handling such levels of complexity. Often the cause of many complex flaws can be traced to errors in how the components of the system communicate and interact. Recently new methods have emerged that use sophisticated data mining and machine-learning techniques to automatically locate the source of flaws. These work by learning the rules for legal interactions between components by observing the behavior of the system during normal operations. These rules can then be automatically checked either statically or dynamically. We propose to create a prototype of a system that uses these techniques. It will learn temporal properties from traces, and feed the resulting rules to a static checker. The checker will report if any part of a component may violate these rules. This is feasible in Phase I because we are able to leverage a great deal of existing technology and expertise.

Principal Investigator:

Paul Anderson
Senior Scientist
6072737340
paul@grammatech.com

Business Contact:

Ray Teitelbaum
CEO/Chairman
6072737340
tt@grammatech.com
Small Business Information at Submission:

GRAMMATECH, INC.
317 N. Aurora Street Ithaca, NY 14850

EIN/Tax ID: 161338879
DUNS: N/A
Number of Employees:
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No