Project Description

1. Methods and Procedures for the Independent Verification and Validation of Neural Networks19 July 2004 NAG5-12069-OSMA-F001-UNCLASS-071904

2. 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 NAG5-12069-OSMA-F001-UNCLASS-071904

3. 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 NAG5-12069-OSMA-F001-UNCLASS-071904

4. 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 NAG5-12069-OSMA-F001-UNCLASS-071904

5. 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 NAG5-12069-OSMA-F001-UNCLASS-071904

6. 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 NAG5-12069-OSMA-F001-UNCLASS-071904

7. 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 NAG5-12069-OSMA-F001-UNCLASS-071904

8. 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) NAG5-12069-OSMA-F001-UNCLASS-071904

9. 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 NAG5-12069-OSMA-F001-UNCLASS-071904

10. 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 NAG5-12069-OSMA-F001-UNCLASS-071904

11. 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 NAG5-12069-OSMA-F001-UNCLASS-071904

12. 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 NAG5-12069-OSMA-F001-UNCLASS-071904

13. 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 NAG5-12069-OSMA-F001-UNCLASS-071904

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