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NASA NTRS1988

Quality measures and assurance for AI (Artificial Intelligence) software

This report is concerned with the application of software quality and evaluation measures to AI software and, more broadly, with the question of quality assurance for AI software. Considered are not only the metrics that attempt to measure some aspect of software quality, but also the methodologies and techniques (such as systematic testing) that attempt to improve some dimension of quality, without necessarily quantifying the extent of the improvement. The report is divided into three parts Part 1 reviews existing software quality measures, i.e., those that have been developed for, and applied to, conventional software. Part 2 considers the characteristics of AI software, the applicability and potential utility of measures and techniques identified in the first part, and reviews those few methods developed specifically for AI software. Part 3 presents an assessment and recommendations for the further exploration of this important area.

Rushby, John↗

DOE OSTI2026

Best practices in software development for robust and reproducible geoscientific models based on insights from the Global Carbon Budget's dynamic vegetation models

Computational models play an increasingly vital role in scientific research by enabling the numerical simulation of complex processes. Such models are also fundamental in geosciences. For instance, they offer critical insights into the impacts of global change on the Earth system today and in the future. Beyond their value as research tools, models are also software products and should therefore adhere to certain established software engineering standards. However, scientists are rarely trained as software developers, which can lead to potential deficiencies in software quality like unreadable, inefficient, or erroneous code. The complexity of models, coupled with their integration into broader workflows, also often makes it challenging to reproduce results, evaluate processes, and build upon them. In this paper, we review the state and current practices of the development processes of the state-of-the-art land surface models used by the Global Carbon Budget. We combine the experience of modelers from the respective research groups with the expertise of software engineers from tech companies to outline key principles and tools for improving software quality in research. We explore four main areas: (1) model testing and validation, (2) scientific, technical, and user documentation, (3) version control, continuous integration, and code review, and (4) the portability and reproducibility of workflows. Our review reveals that while modeling communities are incorporating many best practices, significant room for improvement remains in areas such as automated testing, automated documentation, and reproducibility. Therefore, we here identify and promote essential software engineering practices, including numerous examples of practices from within the community that can serve as guidelines for other models and could help streamline processes across the entire community. We conclude with an open-source example implementation of these principles, demonstrating portable and reproducible data flows, a continuous integration setup, and web-based visualizations. This example may serve as a practical resource for model developers, users, and all scientists engaged in scientific programming.

Gregor, Konstantin [Technical Univ. of Munich (Ger↗

DOE OSTI2025

Cluster Dynamics Modeling Needs for the Advanced Materials and Manufacturing Technologies Program

This milestone report aims to identify and assess the cluster dynamics (CD) modeling requirements within the Department of Energy's Office of Nuclear Energy (DOE-NE) Advanced Materials and Manufacturing Technologies (AMMT) program and to communicate these needs to the DOE-NE Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. The goal is to ensure NEAMS is well-informed about the CD modeling requirements to support AMMT's mission of accelerating the development, qualification, demonstration, and deployment of advanced structural materials and manufacturing for nuclear energy applications. CD modeling is an essential tool for predicting the degradation of structural materials under irradiation, which is a key component of AMMT's accelerated qualification process. The AMMT program focuses on both additively manufactured and wrought structural alloys, such as laser powder-bed fusion 316H austenitic stainless steel, alloy 709, Haynes 244, and alloy 617. These materials require a generalized CD modeling framework to facilitate rapid model development and computational simulation. A flexible, generalized CD software, similar to the Multiphysics Object-Oriented Simulation Environment (MOOSE) finite element framework, would enable modeling of various cluster types, including defect clusters, defect-solute clusters, and multicomponent clusters, incorporating thermodynamics and kinetics parameters. Radiation effects, microstructural feature evolution, and multi-dimensional modeling are critical considerations for the CD model. The usability of the CD code should allow for easy modification and coupling with MOOSE-based simulations. Additionally, the software should adhere to Nuclear Quality Assurance-1 standards, include a testing suite for verification and validation, and be version-controlled within a national laboratory-managed Git repository. Benchmark problems are needed to assess code predictions and performance.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRS1993

Software metrics: The key to quality software on the NCC project

Network Control Center (NCC) Project metrics are captured during the implementation and testing phases of the NCCDS software development lifecycle. The metrics data collection and reporting function has interfaces with all elements of the NCC project. Close collaboration with all project elements has resulted in the development of a defined and repeatable set of metrics processes. The resulting data are used to plan and monitor release activities on a weekly basis. The use of graphical outputs facilitates the interpretation of progress and status. The successful application of metrics throughout the NCC project has been instrumental in the delivery of quality software. The use of metrics on the NCC Project supports the needs of the technical and managerial staff. This paper describes the project, the functions supported by metrics, the data that are collected and reported, how the data are used, and the improvements in the quality of deliverable software since the metrics processes and products have been in use.

Burns, Patricia J.↗

NASA NTRS2003

Software Requirements Analysis as Fault Predictor

Waiting until the integration and system test phase to discover errors leads to more costly rework than resolving those same errors earlier in the lifecycle. Costs increase even more significantly once a software system has become operational. WE can assess the quality of system requirements, but do little to correlate this information either to system assurance activities or long-term reliability projections - both of which remain unclear and anecdotal. Extending earlier work on requirements accomplished by the ARM tool, measuring requirements quality information against code complexity and test data for the same system may be used to predict specific software modules containing high impact or deeply embedded faults now escaping in operational systems. Such knowledge would lead to more effective and efficient test programs. It may enable insight into whether a program should be maintained or started over.

Wallace, Dolores↗

NASA NTRS1988

Markov chains for testing redundant software

A preliminary design for a validation experiment has been developed that addresses several problems unique to assuring the extremely high quality of multiple-version programs in process-control software. The procedure uses Markov chains to model the error states of the multiple version programs. The programs are observed during simulated process-control testing, and estimates are obtained for the transition probabilities between the states of the Markov chain. The experimental Markov chain model is then expanded into a reliability model that takes into account the inertia of the system being controlled. The reliability of the multiple version software is computed from this reliability model at a given confidence level using confidence intervals obtained for the transition probabilities during the experiment. An example demonstrating the method is provided.

White, Allan L.↗

NASA NTRS2009

A Reference Model for Software and System Inspections. White Paper

Software Quality Assurance (SQA) is an important component of the software development process. SQA processes provide assurance that the software products and processes in the project life cycle conform to their specified requirements by planning, enacting, and performing a set of activities to provide adequate confidence that quality is being built into the software. Typical techniques include: (1) Testing (2) Simulation (3) Model checking (4) Symbolic execution (5) Management reviews (6) Technical reviews (7) Inspections (8) Walk-throughs (9) Audits (10) Analysis (complexity analysis, control flow analysis, algorithmic analysis) (11) Formal method Our work over the last few years has resulted in substantial knowledge about SQA techniques, especially the areas of technical reviews and inspections. But can we apply the same QA techniques to the system development process? If yes, what kind of tailoring do we need before applying them in the system engineering context? If not, what types of QA techniques are actually used at system level? And, is there any room for improvement.) After a brief examination of the system engineering literature (especially focused on NASA and DoD guidance) we found that: (1) System and software development process interact with each other at different phases through development life cycle (2) Reviews are emphasized in both system and software development. (Figl.3). For some reviews (e.g. SRR, PDR, CDR), there are both system versions and software versions. (3) Analysis techniques are emphasized (e.g. Fault Tree Analysis, Preliminary Hazard Analysis) and some details are given about how to apply them. (4) Reviews are expected to use the outputs of the analysis techniques. In other words, these particular analyses are usually conducted in preparation for (before) reviews. The goal of our work is to explore the interaction between the Quality Assurance (QA) techniques at the system level and the software level.

He, Lulu↗

NASA NTRS1990

Markov Chains For Testing Redundant Software

Preliminary design developed for validation experiment that addresses problems unique to assuring extremely high quality of multiple-version programs in process-control software. Approach takes into account inertia of controlled system in sense it takes more than one failure of control program to cause controlled system to fail. Verification procedure consists of two steps: experimentation (numerical simulation) and computation, with Markov model for each step.

White, Allan L.↗

NASA NTRS1986

The March 1985 demonstration of the fiducial network concept for GPS geodesy: A preliminary report

The first field tests in preparation for the NASA Global Positioning System (GPS) Caribbean Initiative were conducted in late March and Early April of 1985. The GPS receivers were located at the POLARIS Very Long Base Interferometry (VLBI) stations at Westford, Massachusetts; Richmond, Florida; and Ft. Davis, Texas; and at the Mojave, Owens Valley, and Hat Creek VLBI stations in California. Other mobile receivers were placed near Mammoth Lakes, California; Pt. Mugu, California; Austin, Texas; and Dahlgren, Virginia. These sites were equipped with a combination of GPS receiver types, including SERIES-X, TI-4100 and AFGL dual frequency receivers. The principal objectives of these tests were the demonstration of the fiducial network concept for precise GPS geodesy, the performance assessment of the participating GPS receiver types, and to conduct the first in a series of experiments to monitor ground deformation in the Mammoth Lakes-Long Valley caldera region in California. Other objectives included the testing of the water vapor radiometers for the calibration of GPS data, the development of efficient procedures for planning and coordinating GPS field exercise, the establishment of institutional interfaces for future cooperating ventures, the testing of the GPS Data Analysis Software (GIPSY, for GPS Inferred Positioning SYstem), and the establishment of a set of calibration baselines in California. Preliminary reports of the success of the field tests, including receiver performance and data quality, and on the status of the data analysis software are given.

Davidson, J. M.↗

DOE OSTI2023

Building an Efficient Cluster Cosmology Software Package for Modeling Cluster Counts and Lensing

We introduce a software suite developed for galaxy cluster cosmological analysis with the Dark Energy Survey Data. Cosmological analyses based on galaxy cluster number counts and weak-lensing measurements need efficient software infrastructure to explore an increasingly large parameter space, and account for various cosmological and astrophysical effects. Our software package is designed to model the cluster observables in a wide-field optical survey, including galaxy cluster counts, their averaged weak-lensing masses, or the cluster's averaged weak-lensing radial signals. To ensure maximum efficiency, this software package is developed in C++ in the CosmoSIS software framework, making use of the CUBA integration library. We also implement a testing and validation scheme to ensure the quality of the package. We demonstrate the effectiveness of this development by applying the software to the Dark Energy Survey Year 1 galaxy cluster cosmological data sets, and acquired cosmological constraints that are consistent with the fiducial Dark Energy Survey analysis.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRS1990

Identification challenges for large space structures

The paper examines the on-orbit modal identification of large space structures, stressing the importance of planning and experience, in preparation for the Space Station Structural Characterization Experiment (SSSCE) for the Space Station Freedom. The necessary information to foresee and overcome practical difficulties is considered in connection with seven key factors, including test objectives, dynamic complexity of the structure, data quality, extent of exploratory studies, availability and understanding of software tools, experience with similar problems, and pretest analytical conditions. These factors affect identification success in ground tests. Comparisons with similar ground tests of assembled systems are discussed, showing that the constraints of space tests make these factors more significant. The absence of data and experiences relating to on-orbit modal identification testing is shown to make identification a uniquely mathematical problem, although all spacecraft are constructed and verified by proven engineering methods.

Pappa, Richard S.↗

DOE OSTI2024

Providing Experimental Infrastructure for Accelerating Advanced Reactor Demonstrations through the National Reactor Innovation Center

A suite of experimental infrastructure projects has been developed by the National Reactor Innovation Center to accelerate advanced reactor demonstrations and facilitate their development, addressing crucial gaps in data, materials characterization, and modeling. First, the Molten Salt Thermophysical Examination Capability (MSTEC) provides a specialized platform for post-irradiation characterization of molten salt reactor fuel, coolant salts, and structural materials, essential for supporting the design and operation of advanced reactors and future commercial molten salt reactor development and licensing. The Virtual Test Bed (VTB) complements these efforts by leveraging advanced modeling and simulation tools to evaluate reactor performance and safety. Serving as a library of reference models, the VTB offers a database of multiphysics reactor models, facilitating rapid safety evaluations and includes continuous software quality assurance, crucial for accelerating deployment while maintaining reliability. Additionally, the Helium Component Test Facility (HeCTF) addresses the need for high-temperature helium-cooled reactor component testing. As the first-of-its-kind facility in the United States, HeCTF emulates high-temperature gas reactor conditions, reducing time and cost associated with component validation, thereby accelerating reactor development. Finally, In-cell Thermal Creep Frames provide a unique solution for obtaining thermal creep data from irradiated materials, critical for materials qualification and licensing. Developed by the National Reactor Innovation Center, these compact frames enable the examination of previously irradiated materials, overcoming traditional limitations and enhancing the understanding of mechanical properties crucial for reactor development. Collectively, these experimental infrastructure projects form a comprehensive framework aimed at expediting advanced reactor demonstrations, fostering innovation, and ensuring the viability of next-generation nuclear energy solutions.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2024

pnnl-predictive-phenomics/csc052-gem

Genome-Scale Metabolic Model Continuous Validation with Memote for CarbStor Community Member Bacillus These repositories contain the continuous validation environment for an organism-specific genome-scale metabolic model (GEM) using Memote. Memote is a software tool that provides a suite of tests to ensure the quality and consistency of metabolic models. By integrating Memote into a continuous integration (CI) workflow, we can automatically validate updates to the GEM, ensuring that model modifications improve or maintain the model's integrity.

Torres, Victor E.↗

DOE OSTI2024

pnnl-predictive-phenomics/csc031-gem

Genome-Scale Metabolic Model of CarbStor Community member Microbacterium (csc031) Continuous Validation with Memote These repositories contain the continuous validation environment for an organism-specific genome-scale metabolic model (GEM) using Memote. Memote is a software tool that provides a suite of tests to ensure the quality and consistency of metabolic models. By integrating Memote into a continuous integration (CI) workflow, we can automatically validate updates to the GEM, ensuring that model modifications improve or maintain the model's integrity

McNaughton, Andrew [@PNNL]↗

DOE OSTI2024

pnnl-predictive-phenomics/csc009-gem

Genome-Scale Metabolic Model of CarbStore Community member Curtobacterium (csc009) Continuous Validation with Memote These repositories contain the continuous validation environment for an organism-specific genome-scale metabolic model (GEM) using Memote. Memote is a software tool that provides a suite of tests to ensure the quality and consistency of metabolic models. By integrating Memote into a continuous integration (CI) workflow, we can automatically validate updates to the GEM, ensuring that model modifications improve or maintain the model's integrity

Lin, Tesia↗

DOE OSTI2024

pnnl-predictive-phenomics/csc040-gem

Genome-Scale Metabolic Model Continuous Validation with Memote for CarbStor Community Member Rhodococcus These repositories contain the continuous validation environment for an organism-specific genome-scale metabolic model (GEM) using Memote. Memote is a software tool that provides a suite of tests to ensure the quality and consistency of metabolic models. By integrating Memote into a continuous integration (CI) workflow, we can automatically validate updates to the GEM, ensuring that model modifications improve or maintain the model's integrity.

McNaughton, Andrew [@PNNL]↗

DOE OSTI2024

pnnl-predictive-phenomics/csc043-gem

Genome-Scale Metabolic Model Continuous Validation with Memote for CarbStor Community Member Paenibacillus These repositories contain the continuous validation environment for an organism-specific genome-scale metabolic model (GEM) using Memote. Memote is a software tool that provides a suite of tests to ensure the quality and consistency of metabolic models. By integrating Memote into a continuous integration (CI) workflow, we can automatically validate updates to the GEM, ensuring that model modifications improve or maintain the model's integrity.

Zucker, Jeremy [Pacific Northwest National Laborat↗

NASA NTRS1977

Software engineering project management - A state-of-the-art report

The management of software engineering projects in the aerospace industry was investigated. The survey assessed such features as contract type, specification preparation techniques, software documentation required by customers, planning and cost-estimating, quality control, the use of advanced program practices, software tools and test procedures, the education levels of project managers, programmers and analysts, work assignment, automatic software monitoring capabilities, design and coding reviews, production times, success rates, and organizational structure of the projects.

Thayer, R. H.↗