Finance Sector: Requirements for High Assurance within Spatial SOA Based Grid Infrastructures

2007 ◽  
Author(s):  
P C Donachy ◽  
R H Perrott ◽  
T J Harmer ◽  
F Sharkey
Keyword(s):  
High Assurance ◽  
Grid Infrastructures

Security Engineering for High Assurance, Policy-Based Applications

2002 ◽  
Author(s):  
David Rosenthal ◽  
Francis Fung ◽  
Stephen Garland ◽  
Andrew Myers ◽  
David Evans
Keyword(s):  
Security Engineering ◽  
High Assurance

High Assurance Virtualization Engine (HAVEN)

2009 ◽  
Author(s):  
Ramesh Karri ◽  
Nasir Memon ◽  
Vikram Padman ◽  
Pratik Mathur
Keyword(s):  
High Assurance

High Assurance Testbed for Multilevel Interoperability, 2004 Developments

2004 ◽  
Author(s):  
Cynthia E. Irvine ◽  
Thuy D. Nguyen ◽  
Timothy E. Levin
Keyword(s):  
High Assurance

High assurance composite systems

1993 ◽  
Vol 11 (4) ◽  
pp. 7-12
Author(s):  
Jonathan Fellows
Keyword(s):  
Composite Systems ◽  
High Assurance

USING CLASSIFICATION TREES FOR SOFTWARE QUALITY MODELS: LESSONS LEARNED

1999 ◽  
Vol 09 (02) ◽  
pp. 217-231 ◽  
Author(s):  
TAGHI M. KHOSHGOFTAAR ◽  
EDWARD B. ALLEN ◽  
ARCHANA NAIK ◽  
WENDELL D. JONES ◽  
JOHN P. HUDEPOHL
Keyword(s):  
Software Quality ◽  
Classification Trees ◽  
Lessons Learned ◽  
Quality Models ◽  
Model Based ◽  
Software Product ◽  
High Assurance ◽  
Process Metrics ◽  
Product And Process ◽  
Software Quality Models

High software reliability is an important attribute of high-assurance systems. Software quality models yield timely predictions of quality indicators on a module-by-module basis, enabling one to focus on finding faults early in development. This paper introduces the Classification And Regression Trees (CART) a algorithm to practitioners in high-assurance systems engineering. This paper presents practical lessons learned on building classification trees for software quality modeling, including an innovative way to control the balance between misclassification rates. A case study of a very large telecommunications system used CART to build software quality models. The models predicted whether or not modules would have faults discovered by customers, based on various sets of software product and process metrics as independent variables. We found that a model based on two software product metrics had comparable accuracy to a model based on forty product and process metrics.

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