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All sourcesNASA NTRSDOE OSTI
NASA NTRS2022

Adaptive IV&V for Increasingly Complex Software Systems

As NASA software systems continue to innovate, becoming more complex and nondeterministic, the need for the NASA IV&V Program to become systemically adaptive to ensure mission success is paramount. To ensure adaptability within resource constraints, IV&V has developed an agile, risk-based approach to identify, characterize, scope, focus, and prioritize mission assurance activities. This risk based adaptive framework has been applied to trends such as increased reliance on data driven algorithms for safety and mission critical software behavior, use of MBSE in system design, and application of agile principles to embedded software development. The framework is enabled by continuous innovation of new approaches such as software only test beds, assurance design tools, and initiatives that augment IV&V assurance methods with artificial intelligence and machine learning techniques. This presentation will highlight the trends the NASA IV&V Program is seeing, the innovative steps it is taking to address those challenges, and how it is postured to address evolving risk and constantly changing and new technologies.

Wesley W Deadrick↗
NASA NTRS2005

Development of Advanced Verification and Validation Procedures and Tools for the Certification of Learning Systems in Aerospace Applications

Adaptive control technologies that incorporate learning algorithms have been proposed to enable automatic flight control and vehicle recovery, autonomous flight, and to maintain vehicle performance in the face of unknown, changing, or poorly defined operating environments. In order for adaptive control systems to be used in safety-critical aerospace applications, they must be proven to be highly safe and reliable. Rigorous methods for adaptive software verification and validation must be developed to ensure that control system software failures will not occur. Of central importance in this regard is the need to establish reliable methods that guarantee convergent learning, rapid convergence (learning) rate, and algorithm stability. This paper presents the major problems of adaptive control systems that use learning to improve performance. The paper then presents the major procedures and tools presently developed or currently being developed to enable the verification, validation, and ultimate certification of these adaptive control systems. These technologies include the application of automated program analysis methods, techniques to improve the learning process, analytical methods to verify stability, methods to automatically synthesize code, simulation and test methods, and tools to provide on-line software assurance.

Jacklin, Stephen↗
NASA NTRS2006

Case Study: Test Results of a Tool and Method for In-Flight, Adaptive Control System Verification on a NASA F-15 Flight Research Aircraft

Adaptive control technologies that incorporate learning algorithms have been proposed to enable autonomous flight control and to maintain vehicle performance in the face of unknown, changing, or poorly defined operating environments [1-2]. At the present time, however, it is unknown how adaptive algorithms can be routinely verified, validated, and certified for use in safety-critical applications. Rigorous methods for adaptive software verification end validation must be developed to ensure that. the control software functions as required and is highly safe and reliable. A large gap appears to exist between the point at which control system designers feel the verification process is complete, and when FAA certification officials agree it is complete. Certification of adaptive flight control software verification is complicated by the use of learning algorithms (e.g., neural networks) and degrees of system non-determinism. Of course, analytical efforts must be made in the verification process to place guarantees on learning algorithm stability, rate of convergence, and convergence accuracy. However, to satisfy FAA certification requirements, it must be demonstrated that the adaptive flight control system is also able to fail and still allow the aircraft to be flown safely or to land, while at the same time providing a means of crew notification of the (impending) failure. It was for this purpose that the NASA Ames Confidence Tool was developed [3]. This paper presents the Confidence Tool as a means of providing in-flight software assurance monitoring of an adaptive flight control system. The paper will present the data obtained from flight testing the tool on a specially modified F-15 aircraft designed to simulate loss of flight control faces.

Jacklin, Stephen A.↗
DOE OSTI2025

Status of SPCA-ANL Software Development, Software Quality Assurance, and Application (FY2025)

SPCA-ANL is a simulation tool used to perform deterministic analyses of sodium spray and pool fires. Development of the SPCA-II (Spray Pool Combustion Analysis) code began in the mid- 1980s as part of the Clinch River Breeder Reactor (CRBR) Project. At that time, development of SPCA-II, which was led by Rockwell International, was focused on treatment of large-scale sodium spray, stream, and pool fires that were anticipated to be prototypic of the steam generator building cells in CRBR. Under more recent DOE NE programmatic activities, the SPCA-II code was recovered from existing literature and underwent minor modifications to generate a stable executable. This recovered version of the code was not formally released. As part of the Versatile Test Reactor (VTR) Project in the 2010s, the SPCA-II code underwent key modifications to improve stability, address modeling deficiencies, improve consistency between the code manual and software, and address numerous bugs. At this point, SPCA-II was renamed SPCA-ANL. Given that SPCA-II served as the original basis for SPCA-ANL, both codes share an integrated history. Following termination of the VTR Project, the DOE NE Fast Reactor Program resumed support of the software with the goal of building and maintaining software infrastructure that can enable commercial-grade dedication of SPCA-ANL by an end user. Version 1.0, the first external release of SPCA-ANL, was generated in June 2024. This report summarizes the development and maintenance activities completed for SPCAANL in FY2025. This year’s work was focused on improving quality and usability of the code. The provisional Software Quality Assurance (SQA) program has been established and was used to test the procedures for infrastructure improvements, code development, bug fixes, and code releases, as described in the following sections of this report. A code Version 1.0.1 was released in FY25, as described in Chapter 4.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Watching the Watchers with Verified Formal-Assurance Tools (Abbreviated Final Report)

The “Watching the Watchers” project studied the problem of establishing assurance cases for tools that are used to assure other things. Specifically, we were interested in understanding the tools and techniques one could apply to software to build an assurance case to evaluate their applicability, difficulty, level of assurance provided, and scalability. To do so we chose a set of use cases of relevance to LLNL and our various DOE and non-DOE partners and developed demonstrators to perform this evaluation. Our key focal point was around additive manufacturing problems and assurance gaps that we identified in the additive manufacturing workflow from start to completion. We also explored other areas related to AI, data analysis, and concurrent programming. Follow-on research is planned to take our prototypes from this project and adapt and mature them to fit LLNL mission applications.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1987

Product assurance policies and procedures for flight dynamics software development

The product assurance policies and procedures necessary to support flight dynamics software development projects for Goddard Space Flight Center are presented. The quality assurance and configuration management methods and tools for each phase of the software development life cycles are described, from requirements analysis through acceptance testing; maintenance and operation are not addressed.

Perry, Sandra↗
NASA NTRS1997

An Automated Method for Identifying Inconsistencies within Diagrammatic Software Requirements Specifications

The development of large-scale, composite software in a geographically distributed environment is an evolutionary process. Often, in such evolving systems, striving for consistency is complicated by many factors, because development participants have various locations, skills, responsibilities, roles, opinions, languages, terminology and different degrees of abstraction they employ. This naturally leads to many partial specifications or viewpoints. These multiple views on the system being developed usually overlap. From another aspect, these multiple views give rise to the potential for inconsistency. Existing CASE tools do not efficiently manage inconsistencies in distributed development environment for a large-scale project. Based on the ViewPoints framework the WHERE (Web-Based Hypertext Environment for requirements Evolution) toolkit aims to tackle inconsistency management issues within geographically distributed software development projects. Consequently, WHERE project helps make more robust software and support software assurance process. The long term goal of WHERE tools aims to the inconsistency analysis and management in requirements specifications. A framework based on Graph Grammar theory and TCMJAVA toolkit is proposed to detect inconsistencies among viewpoints. This systematic approach uses three basic operations (UNION, DIFFERENCE, INTERSECTION) to study the static behaviors of graphic and tabular notations. From these operations, subgraphs Query, Selection, Merge, Replacement operations can be derived. This approach uses graph PRODUCTIONS (rewriting rules) to study the dynamic transformations of graphs. We discuss the feasibility of implementation these operations. Also, We present the process of porting original TCM (Toolkit for Conceptual Modeling) project from C++ to Java programming language in this thesis. A scenario based on NASA International Space Station Specification is discussed to show the applicability of our approach. Finally, conclusion and future work about inconsistency management issues in WHERE project will be summarized.

Zhang, Zhong↗
NASA NTRS2009

Architectural Analysis of Complex Evolving Systems of Systems

The goal of this collaborative project between FC-MD, APL, and GSFC and supported by NASA IV&V Software Assurance Research Program (SARP), was to develop a tool, Dynamic SAVE, or Dyn-SAVE for short, for analyzing architectures of systems of systems. The project team was comprised of the principal investigator (PI) from FC-MD and four other FC-MD scientists (part time) and several FC-MD students (full time), as well as, two APL software architects (part time), and one NASA POC (part time). The PI and FC-MD scientists together with APL architects were responsible for requirements analysis, and for applying and evaluating the Dyn-SAVE tool and method. The PI and a group of FC-MD scientists were responsible for improving the method and conducting outreach activities, while another group of FC-MD scientists were responsible for development and improvement of the tool. Oversight and reporting was conducted by the PI and NASA POC. The project team produced many results including several prototypes of the Dyn-SAVE tool and method, several case studies documenting how the tool and method was applied to APL s software systems, and several published papers in highly respected conferences and journals. Dyn-SAVE as developed and enhanced throughout this research period, is a software tool intended for software developers and architects, software integration testers, and persons who need to analyze software systems from the point of view of how it communicates with other systems. Using the tool, the user specifies the planned communication behavior of the system modeled as a sequence diagram. The user then captures and imports the actual communication behavior of the system, which is then converted and visualized as a sequence diagram by Dyn-SAVE. After mapping the planned to the actual and specifying parameter and timing constraints, Dyn-SAVE detects and highlights deviations between the planned and the actual behavior. Requirements based on the need to analyze two inter-system communication protocols that are representative of protocols used in the Aerospace industry have been specified. The protocols are related: APL s Common Ground System (CGS) as used in the MErcury Surface, Space ENvironment, GEochemistry, and Ranging (MESSENGER) and the Radiation Belt Space Probes (RBSP) missions. The analyzed communications were implementations of the Telemetry protocol and the CCSDS File Delivery Protocol (CFDP) protocol. Based on these requirements, three prototypes of Dyn-SAVE were developed and applied to these protocols. The application of Dyn-SAVE to these protocols resulted in the detection of several issues. Dyn-SAVE was also applied to several Testbeds that have previously been used for experimentation earlier on this project, as well as, to other protocols and logs for testing its broader applicability. For example, Dyn-SAVE was used to analyze 1) the communication pattern between a web browser and a web server, 2) the system log of a computer in order to detect offnominal computer shut-down behavior, and 3) the actual test cases of NASA Goddard s Core Flight System (CFS) and automatically generated test cases in order to determine the overlap between the two sets of test cases. In all cases, Dyn-SAVE assisted in providing insightful conclusions about each of the cases identified above.

Lindvall, Mikael↗
NASA NTRS2008

Closing the Certification Gaps in Adaptive Flight Control Software

Over the last five decades, extensive research has been performed to design and develop adaptive control systems for aerospace systems and other applications where the capability to change controller behavior at different operating conditions is highly desirable. Although adaptive flight control has been partially implemented through the use of gain-scheduled control, truly adaptive control systems using learning algorithms and on-line system identification methods have not seen commercial deployment. The reason is that the certification process for adaptive flight control software for use in national air space has not yet been decided. The purpose of this paper is to examine the gaps between the state-of-the-art methodologies used to certify conventional (i.e., non-adaptive) flight control system software and what will likely to be needed to satisfy FAA airworthiness requirements. These gaps include the lack of a certification plan or process guide, the need to develop verification and validation tools and methodologies to analyze adaptive controller stability and convergence, as well as the development of metrics to evaluate adaptive controller performance at off-nominal flight conditions. This paper presents the major certification gap areas, a description of the current state of the verification methodologies, and what further research efforts will likely be needed to close the gaps remaining in current certification practices. It is envisioned that closing the gap will require certain advances in simulation methods, comprehensive methods to determine learning algorithm stability and convergence rates, the development of performance metrics for adaptive controllers, the application of formal software assurance methods, the application of on-line software monitoring tools for adaptive controller health assessment, and the development of a certification case for adaptive system safety of flight.

Jacklin, Stephen A.↗
NASA NTRS2002

A Data-Driven Solution for Performance Improvement

Marketed as the "Software of the Future," Optimal Engineering Systems P.I. EXPERT(TM) technology offers statistical process control and optimization techniques that are critical to businesses looking to restructure or accelerate operations in order to gain a competitive edge. Kennedy Space Center granted Optimal Engineering Systems the funding and aid necessary to develop a prototype of the process monitoring and improvement software. Completion of this prototype demonstrated that it was possible to integrate traditional statistical quality assurance tools with robust optimization techniques in a user- friendly format that is visually compelling. Using an expert system knowledge base, the software allows the user to determine objectives, capture constraints and out-of-control processes, predict results, and compute optimal process settings.

Source record↗
NASA NTRS2020

NASA quality assurance in an MBSE world

We explore the impact and consequences of the MBSE Value items discussed above and how they impact the disciplines of quality assurance, reliability and maintainability, system safety, and software assurance. We provide insight into how the MBSE modeling tools can be used to define S&MA processes (ideally as a result of Use Case [1] elaboration of processes represented in MagicDraw®), produce S&MA products (ViewEditor output of various items), and represent S&MA disciplines (S&MA inside of MagicDraw). We also provide insight into the degree to which some elements can be directly integrated into a SysML® model and when, as often happens, an interface to some external source must be provided.

Evans, John W.↗
NASA NTRS2020

NASA Quality Assurance in an MBSE world

Over the past decade or so, the emergence of Model Based Systems Engineering (MBSE) has demonstrated its desirability and value in terms of 1) being a single source of truth, 2) unambiguous definitions and relationships, and 3) after representation, the ability to explore/extract any sets of data on demand. While much work has been done in showing the value to the system engineering discipline in these areas, how does that value translate to the Safety and Mission Assurance (S&MA) world? This paper provides a vision of a very desirable future of NASA S&MA after it is fully integrated into the MBSE framework. We explore the impact and consequences of the MBSE Value items discussed above and how they impact the disciplines of quality assurance, reliability and maintainability, system safety, and software assurance. We provide insight into how the MBSE modeling tools can be used to define S&MA processes (ideally as a result of Use Case [1] elaboration of processes represented in MagicDraw®), produce S&MA products (ViewEditor output of various items), and represent S&MA disciplines (S&MA inside of MagicDraw). We also provide insight into the degree to which some elements can be directly integrated into a SysML® model and when, as often happens, an interface to some external source must be provided. The desirability of this future is part of the reason for the NASA Office of Safety and Mission Assurance’s (OSMA) recent creation of a Model Based Mission Assurance (MBMA) Program [2] and the MBMA annual workshops. We briefly summarize the efforts to date to generate S&MA Use Cases for eventual deployment into pilot and project efforts. Even simple use of the SysML modeling tools can be used to capture quality assurance tasks and integrate them with the systems engineering and produce products that are easy to use by quality practitioners that are unfamiliar with these methods. We anticipate finding opportunities to pilot and implement various Quality Assurance (QA) Use Cases in FY20. The MBMA Program is focused on implementation; the NASA Office of the Chief Engineer's Community of Practice, as well as the SmallSat communities, are very interested in the integration of S&MA. Finally, as projects move forward utilizing whatever efficiency increases they can find in a cost-constrained environment, the S&MA community cannot be caught unawares and needs to continue preparing for the ever-growing implementation of MBSE across NASA and our government and commercial partners.

Evans, John W↗
NASA NTRSDate not supplied

Certification Concepts for AI/ML Systems

This presentation goes over some of the tools developed at NASA Ames in the Robust Software Engineering group for the assurance and certification of autonomous systems. The research themes presented include improving safety and risk assessment as early as possible in the lifecycle, elicitation and formalization of requirements to facilitate traceability throughout the lifecycle, especially when formal methods are used, algorithms, tools and techniques for the V&V of ML-enabled systems, advanced testing, use of runtime monitoring to ease use of untrusted components, and contribution to draft regulatory standards and assistance in producing and presenting certification evidences.

Autonomy↗
NASA NTRS2023

CST: A Tool for Optimizing the Efficiency and Effectiveness of Static-Code Analysis Tools

Static Code Analysis (SCA) is a vital component of NASA IV&V’s mission assurance for safety-critical software as it reduces the likelihood of software-induced hazards impacting mission success. Static Code Analysis achieves this by identifying hazards that may not have been otherwise detectable by typical code reviews or other testing. Using SCA tools, however, can be intimidating due to steep learning curves, especially considering tool performance and defect coverage varies greatly. Because of this variation amongst SCA tools, understanding which tools support certain defects and which do not, as well as understanding how to run an analysis based on steps that are unique to each tool, can be difficult to both new and experienced analysts alike. To mitigate this, the SCAWG or the IV&V Static Code Analysis Working Group, created the SCA Checker Taxonomy and Starting Point Profiles. The Checker Selection Tool (CST) incorporates these two SCAWG products into an interactive tool which allows the user to: select organized categories of defects they would like the SCA tools to discover, select default checkers depending on their mission type (e.g. flight), and configure multiple SCA tools at once. C/C++, Java, and Python defect checkers from four common SCA tools were utilized in this iteration of the CST. This iteration also includes the addition of training, SCA tool specific help, and taxonomy guide links, into its design to help users new to Static Code Analysis learn how to perform SCA more efficiently. The CST has been subject to beta testing by experienced static code analysts from the SCAWG to ensure a usable and accurate final product. The implications of the CST in the mission assurance of NASA safety-critical software are profound, as the CST can help identify and reduce false positives and false negatives, fundamentally improving overall SCA efficiency and accuracy.

static code analysis↗
NASA NTRS2004

A Tool for Verification and Validation of Neural Network Based Adaptive Controllers for High Assurance Systems

High reliability of mission- and safety-critical software systems has been identified by NASA as a high-priority technology challenge. We present an approach for the performance analysis of a neural network (NN) in an advanced adaptive control system. This problem is important in the context of safety-critical applications that require certification, such as flight software in aircraft. We have developed a tool to measure the performance of the NN during operation by calculating a confidence interval (error bar) around the NN's output. Our tool can be used during pre-deployment verification as well as monitoring the network performance during operation. The tool has been implemented in Simulink and simulation results on a F-15 aircraft are presented.

Gupta, Pramod↗
NASA NTRS1985

Proceedings of Tenth Annual Software Engineering Workshop

Papers are presented on the following topics: measurement of software technology, recent studies of the Software Engineering Lab, software management tools, expert systems, error seeding as a program validation technique, software quality assurance, software engineering environments (including knowledge-based environments), the Distributed Computing Design System, and various Ada experiments.

Source record↗
NASA NTRS2005

Challenges of Developing New Classes of NASA Self-Managing Mission

NASA is proposing increasingly complex missions that will require a high degree of autonomy and autonomicity. These missions pose hereto unforeseen problems and raise issues that have not been well-addressed by the community. Assuring success of such missions will require new software development techniques and tools. This paper discusses some of the challenges that NASA and the rest of the software development community are facing in developing these ever-increasingly complex systems. We give an overview of a proposed NASA mission as well as techniques and tools that are being developed to address autonomic management and the complexity issues inherent in these missions.

Hinchey, M. G.↗