1. Development of Methodologies for Independent Verification and Validation of Neural Networks NAG5-12069-OSMA-F001-UNCLASS-071904 Methods and Procedures for the Independent Verification and Validation of Neural Networks 19 July 2004

2. 2 NAG5-12069-OSMA-F001-UNCLASS-071904 Project Description The IVVNN Project began in May 2002 in an effort to develop a standard for verifying and validating NN and adaptive systems for the NASA IV&V Facility –As NN and adaptive systems are becoming more common in NASA and commercial applications, the need for such a standard became paramount –The project is scheduled to continue until September 2005 The IVVNN project is a collaborative effort among the ISR, the NASA IV&V Facility, and WVU –The majority of the research under this initiative was conducted by the ISR with support from WVU –Previous research efforts conducted by the NASA DFRC and the NASA ARC provided both insight and direction

3. 3 NAG5-12069-OSMA-F001-UNCLASS-071904 Project Overview Goals: –To develop a methodology for the IVVNN –To test the IVVNN methodology on the NASA DFRC IFCS GEN1 system (and possibly the IFCS GEN2 system) –To train IV&V personnel on the use of IVVNN methodology –To integrate the IVVNN methodology as guidance augmentation to the IEEE 1012 The IVVNN project is separated into 4 major tasks: –Task 1: NN (I)V&V Literature Search –Task 2: Methodology Research –Task 3: Methodology Development –Task 4: Methodology Training

4. 4 NAG5-12069-OSMA-F001-UNCLASS-071904 Task 1: NN IV&V Literature Search Goal was to identify the current state-of-the-art for the V&V and IV&V of NN research –Conducted an extensive literature search in which over 300 artifacts were collected Artifacts included conference papers, journals, technical reports, tools, applications, and presentations that were available in the public domain Artifacts contained methods and techniques that were claimed to be useful for the V&V, and potentially IV&V, of NN All collected artifacts were evaluated to determine which ones were more promising and applicable to the IV&V of NN. –The results of the literature search and evaluation of collected artifacts were collected in a document titled Toward Reliable Neural Network Software for the Development of Methodologies for the Independent Verification and Validation of Neural Networks The conclusion was made that six methods were found to be most promising for the V&V of NN and consisted of: –traditional and automated testing techniques –run-time monitoring –Lyapunov stability analysis –rule extraction –cross validation –Visualization The ISR also concluded that there were very few tools that were directly applicable to the V&V of NN

5. 5 NAG5-12069-OSMA-F001-UNCLASS-071904 Task 2: Methodology Research Goal was to: –examine and evaluate a subset of the methods and techniques identified in Task 1 –conduct research in other areas that the ISR hypothesized would be beneficial to the (I)V&V of NN Task 2 was divided into twelve research elements: –Human Factors Analysis Based on Pilot Certification –Formal Methods –Run-time Monitoring Methods (including Data Sniffing and Lyapanov Stability Analysis) –Testing Methods –Visualization Methods –Automated Neural Network Selection –Neural Network Design Verification –Study of IV&V Current Practices –Failure Modes and Effects Analysis / Risk Assessment –Simulation Methods –Safety Monitors The results of Task 2 were collected in a book entitled Methods and Procedures for the Independent Verification and Validation of Neural Networks

6. 6 NAG5-12069-OSMA-F001-UNCLASS-071904 Task 3: Methodology Development The goal is to: –Utilize work from ‘Standards Mapping’ in Task 2 which identifies neural network / adaptive systems gaps within IEEE 1012 directives –Combine the experiences from the IFCS project with the techniques researched in Task 2 –Add additional directives as a complement to IEEE 1012 –Provide guidance in completing the directives, using the techniques, and highlight important areas of consideration

7. 7 NAG5-12069-OSMA-F001-UNCLASS-071904 Task 3: Methodology Development Methodology Design Approach: –Structured into 3 phases –Methodology to cover all development lifecycles Concept to operations –Methodology testing with IFCS GEN1 and possibly GEN2

8. 8 NAG5-12069-OSMA-F001-UNCLASS-071904 Task 3: Methodology Development In addition to Task 2 and IFCS Gen 1 experience, several documents are being considered as we develop this methodology: –DCP-S-007: Dryden Flight Research Center Software Assurance Document –Verification & Validation of Adaptive Neural Networks for Aerospace Systems (Stacy Nelson et. al) [multiple versions] –V&V of Advanced Systems at NASA (Stacy Nelson & Charles Pecheur) –IEEE 1059: IEEE Guide for Software Verification and Validation Plans –IEEE 828: IEEE Standard for Software Configuration Management Plans –IEEE 730: IEEE Standard for Software Quality Assurance Plans –IFCS Software Verification and Validation Plan –Developing Software to Government Standards (William H. Roetzheim) –NISTIR 5589: A Study of Hazard Analysis in High Integrity Software Standard and Guidance (Laura M. Ippolito and Delores R. Wallace) –Safety Lifecycle for Developing Safety Critical Artificial Neural Networks (Zeshan Kurd and Tim Kelly) –Safety Criteria and Safety Lifecycle for Artificial Neural Networks (Zeshan Kurd, Tim Kelly and Jim Austin)

9. 9 NAG5-12069-OSMA-F001-UNCLASS-071904 Task 3: Methodology Development Concept Phase –Analysis of the concept tasks completed –Rough draft of concept IVVNN guidance created –To date, have written guidance for the following concept phase tasks for NN and adaptive systems Concept documentation evaluation Criticality analysis Hardware/software/user requirements allocation analysis Traceability analysis Hazard analysis Risk analysis –Preliminary testing involved applying the concept phase guidance to the IFCS GEN1 documentation

10. 10 NAG5-12069-OSMA-F001-UNCLASS-071904 Task 3: Methodology Development Concept Documents Considered: –IFCS Objectives and Requirements Document –IFCS Project Plan –IFCS Systems Requirement Document –Pre-Trained Neural Network Report –Dynamic Cell Structure Neural Network Report –Sigma-Pi Neural Network Report (GEN2) –Single Hidden Layer Neural Network Report (GEN2) –Neural Network Evaluator Design Document (GEN2) –Software Verification and Validation Report - Traceability Analysis, Criticality Analysis –IFCS System Safety Plan –IFCS Preliminary Hazard Analysis

11. 11 NAG5-12069-OSMA-F001-UNCLASS-071904 Task 3: Methodology Development Requirements Phase –Currently working on analysis of requirements tasks –Begun writing guidance for the requirements task of traceability analysis Requirements Documents Considered: –IFCS Systems Requirement Document –IFCS Software and Interface Requirements Specification (ISR) –IFCS System Test Plan and Description Document (ISR) –IFCS Preliminary Hazard Analysis

12. 12 NAG5-12069-OSMA-F001-UNCLASS-071904 Task 3: Methodology Development Issue: –Level of documentation detail will vary from project to project Lack of documentation Detailed requirements early Informal documentation by researchers Solution: –Develop the guidance to be adjustable to the IV&V practitioner

13. 13 NAG5-12069-OSMA-F001-UNCLASS-071904 Next Steps Remaining Phase I Methodology Design Tasks –Requirements –Design –Implementation –Testing –Operations –Management –Acquisition –Methodology Design Review (MDR) Phase II Phase III IFCS GEN2 Testing –NASA Dryden Flight Research Center –NASA IV&V Facility

14. 14 NAG5-12069-OSMA-F001-UNCLASS-071904 Questions