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Quantitative Measures for Software Independent Verification and Validation

As software is maintained or reused, it undergoes an evolution which tends to increase the overall complexity of the code. To understand the effects of this, we brought in statistics experts and leading researchers in software complexity, reliability, and their interrelationships. These experts' project has resulted in our ability to statistically correlate specific code complexity attributes, in orthogonal domains, to errors found over time in the HAL/S flight software which flies in the Space Shuttle. Although only a prototype-tools experiment, the result of this research appears to be extendable to all other NASA software, given appropriate data similar to that logged for the Shuttle onboard software. Our research has demonstrated that a more complete domain coverage can be mathematically demonstrated with the approach we have applied, thereby ensuring full insight into the cause-and-effects relationship between the complexity of a software system and the fault density of that system. By applying the operational profile we can characterize the dynamic effects of software path complexity under this same approach We now have the ability to measure specific attributes which have been statistically demonstrated to correlate to increased error probability, and to know which actions to take, for each complexity domain. Shuttle software verifiers can now monitor the changes in the software complexity, assess the added or decreased risk of software faults in modified code, and determine necessary corrections. The reports, tool documentation, user's guides, and new approach that have resulted from this research effort represent advances in the state of the art of software quality and reliability assurance. Details describing how to apply this technique to other NASA code are contained in this document.

Lee, Alice↗

Knowledge-Based Aircraft Automation: Managers Guide on the use of Artificial Intelligence for Aircraft Automation and Verification and Validation Approach for a Neural-Based Flight Controller

The ultimate goal of this report was to integrate the powerful tools of artificial intelligence into the traditional process of software development. To maintain the US aerospace competitive advantage, traditional aerospace and software engineers need to more easily incorporate the technology of artificial intelligence into the advanced aerospace systems being designed today. The future goal was to transition artificial intelligence from an emerging technology to a standard technology that is considered early in the life cycle process to develop state-of-the-art aircraft automation systems. This report addressed the future goal in two ways. First, it provided a matrix that identified typical aircraft automation applications conducive to various artificial intelligence methods. The purpose of this matrix was to provide top-level guidance to managers contemplating the possible use of artificial intelligence in the development of aircraft automation. Second, the report provided a methodology to formally evaluate neural networks as part of the traditional process of software development. The matrix was developed by organizing the discipline of artificial intelligence into the following six methods: logical, object representation-based, distributed, uncertainty management, temporal and neurocomputing. Next, a study of existing aircraft automation applications that have been conducive to artificial intelligence implementation resulted in the following five categories: pilot-vehicle interface, system status and diagnosis, situation assessment, automatic flight planning, and aircraft flight control. The resulting matrix provided management guidance to understand artificial intelligence as it applied to aircraft automation. The approach taken to develop a methodology to formally evaluate neural networks as part of the software engineering life cycle was to start with the existing software quality assurance standards and to change these standards to include neural network development. The changes were to include evaluation tools that can be applied to neural networks at each phase of the software engineering life cycle. The result was a formal evaluation approach to increase the product quality of systems that use neural networks for their implementation.

Broderick, Ron↗

Verification and Validation in a Rapid Software Development Process

The high cost of software production is driving development organizations to adopt more automated design and analysis methods such as rapid prototyping, computer-aided software engineering (CASE) tools, and high-level code generators. Even developers of safety-critical software system have adopted many of these new methods while striving to achieve high levels Of quality and reliability. While these new methods may enhance productivity and quality in many cases, we examine some of the risks involved in the use of new methods in safety-critical contexts. We examine a case study involving the use of a CASE tool that automatically generates code from high-level system designs. We show that while high-level testing on the system structure is highly desirable, significant risks exist in the automatically generated code and in re-validating releases of the generated code after subsequent design changes. We identify these risks and suggest process improvements that retain the advantages of rapid, automated development methods within the quality and reliability contexts of safety-critical projects.

Callahan, John R.↗

Model Checking Verification and Validation at JPL and the NASA Fairmont IV and V Facility

We show how a technology transfer effort was carried out. The successful use of model checking on a pilot JPL flight project demonstrates the usefulness and the efficacy of the approach. The pilot project was used to model a complex spacecraft controller. Software design and implementation validation were carried out successfully. To suggest future applications we also show how the implementation validation step can be automated. The effort was followed by the formal introduction of the modeling technique as a part of the JPL Quality Assurance process.

Schneider, Frank↗

Verification and Validation of Neural Networks for Aerospace Systems

The Dryden Flight Research Center V&V working group and NASA Ames Research Center Automated Software Engineering (ASE) group collaborated to prepare this report. The purpose is to describe V&V processes and methods for certification of neural networks for aerospace applications, particularly adaptive flight control systems like Intelligent Flight Control Systems (IFCS) that use neural networks. This report is divided into the following two sections: Overview of Adaptive Systems and V&V Processes/Methods.

Mackall, Dale↗

Verification and Validation of Neural Networks for Aerospace Systems

The Dryden Flight Research Center V&V working group and NASA Ames Research Center Automated Software Engineering (ASE) group collaborated to prepare this report. The purpose is to describe V&V processes and methods for certification of neural networks for aerospace applications, particularly adaptive flight control systems like Intelligent Flight Control Systems (IFCS) that use neural networks. This report is divided into the following two sections: 1) Overview of Adaptive Systems; and 2) V&V Processes/Methods.

Mackall, Dale↗

Verification and Validation of the RAGE Hydrocode in Preparation for Investigation of Impacts into a Volatile-rich Target

Before a hydrocode is used to investigate a question of scientific interest, it should be tested against analogous laboratory experiments and problems with analytical solutions. The Radiation Adaptive Grid Eulerian (RAGE) hydrocode[1], developed by Los Alamos National Laboratory (LANL) and Science Applications International Corporation (SAIC)[2,3] has been subjected to many tests during its development.[4,5] We extend and review this work, emphasizing tests relevant to impact cratering into volatile-rich targets.

Plesko, C. S.↗

Challenges in verification and validation of autonomous systems for space exploration

Space exploration applications offer a unique opportunity for the development and deployment of autonomous systems, due to limited communications, large distances, and great expense of direct operation. At the same time, the risk and cost of space missions leads to reluctance to taking on new, complex and difficult-to-understand technology. A key issue in addressing these concerns is the validation of autonomous systems. In recent years, higher-level autonomous systems have been applied in space applications. In this presentation, we will highlight those autonomous systems, and discuss issues in validating these systems. We will then look to future demands on validating autonomous systems for space, identify promising technologies and open issues.

Brat, Guillaume↗

Validation and Verification of Composite Pressure Vessel Design

Ten composite pressure vessels were instrumented with fiber Bragg grating sensors and pressure tested Through burst. This paper and presentation will discuss the testing methodology, the test results, compare the testing results to the analytical model, and also compare the fiber Bragg grating sensor data with data obtained against that obtained from foil strain gages.

Kreger, Stephen T.↗

Independent Verification and Validation (IV and V) Criteria

The purpose of this appendix is to establish quantifiable criteria for determining whether IV&V should be applied to a given software development. Since IV&V should begin in the Formulation Subprocess of a project, the process here described is based on metrics which are available before project approval.

McGill, Kenneth↗

Antenna reconfiguration verification and validation

A method of testing the electrical functionality of an optically controlled switch in a reconfigurable antenna is provided. The method includes configuring one or more conductive paths between one or more feed points and one or more test point with switches in the reconfigurable antenna. Applying one or more test signals to the one or more feed points. Monitoring the one or more test points in response to the one or more test signals and determining the functionality of the switch based upon the monitoring of the one or more test points.

Becker, Robert C.↗

Verification and Validation of Requirements on the CEV Parachute Assembly System Using Design of Experiments

The Crew Exploration Vehicle Parachute Assembly System (CPAS) project conducts computer simulations to verify that flight performance requirements on parachute loads and terminal rate of descent are met. Design of Experiments (DoE) provides a systematic method for variation of simulation input parameters. When implemented and interpreted correctly, a DoE study of parachute simulation tools indicates values and combinations of parameters that may cause requirement limits to be violated. This paper describes one implementation of DoE that is currently being developed by CPAS, explains how DoE results can be interpreted, and presents the results of several preliminary studies. The potential uses of DoE to validate parachute simulation models and verify requirements are also explored.

Schulte, Peter Z.↗

Ares I-X Range Safety Trajectory Analyses Overview and Independent Validation and Verification

All Flight Analysis data products were successfully generated and delivered to the 45SW in time to support the launch. The IV&V effort allowed data generators to work through issues early. Data consistency proved through the IV&V process provided confidence that the delivered data was of high quality. Flight plan approval was granted for the launch. The test flight was successful and had no safety related issues. The flight occurred within the predicted flight envelopes. Post flight reconstruction results verified the simulations accurately predicted the FTV trajectory.

Tarpley, Ashley F.↗

Validation and Verification of Operational Land Analysis Activities at the Air Force Weather Agency

The NASA developed Land Information System (LIS) is the Air Force Weather Agency's (AFWA) operational Land Data Assimilation System (LDAS) combining real time precipitation observations and analyses, global forecast model data, vegetation, terrain, and soil parameters with the community Noah land surface model, along with other hydrology module options, to generate profile analyses of global soil moisture, soil temperature, and other important land surface characteristics. (1) A range of satellite data products and surface observations used to generate the land analysis products (2) Global, 1/4 deg spatial resolution (3) Model analysis generated at 3 hours

Shaw, Michael↗

Comprehensive Approach to Verification and Validation of CFD Simulations Applied to Backward Facing Step-Application of CFD Uncertainty Analysis

There are inherent uncertainties and errors associated with using Computational Fluid Dynamics (CFD) to predict the flow field and there is no standard method for evaluating uncertainty in the CFD community. This paper describes an approach to -validate the . uncertainty in using CFD. The method will use the state of the art uncertainty analysis applying different turbulence niodels and draw conclusions on which models provide the least uncertainty and which models most accurately predict the flow of a backward facing step.

Groves, Curtis E.↗