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At least 127 records · Page 7

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NASA NTRS1994

Understanding software faults and their role in software reliability modeling

This study is a direct result of an on-going project to model the reliability of a large real-time control avionics system. In previous modeling efforts with this system, hardware reliability models were applied in modeling the reliability behavior of this system. In an attempt to enhance the performance of the adapted reliability models, certain software attributes were introduced in these models to control for differences between programs and also sequential executions of the same program. As the basic nature of the software attributes that affect software reliability become better understood in the modeling process, this information begins to have important implications on the software development process. A significant problem arises when raw attribute measures are to be used in statistical models as predictors, for example, of measures of software quality. This is because many of the metrics are highly correlated. Consider the two attributes: lines of code, LOC, and number of program statements, Stmts. In this case, it is quite obvious that a program with a high value of LOC probably will also have a relatively high value of Stmts. In the case of low level languages, such as assembly language programs, there might be a one-to-one relationship between the statement count and the lines of code. When there is a complete absence of linear relationship among the metrics, they are said to be orthogonal or uncorrelated. Usually the lack of orthogonality is not serious enough to affect a statistical analysis. However, for the purposes of some statistical analysis such as multiple regression, the software metrics are so strongly interrelated that the regression results may be ambiguous and possibly even misleading. Typically, it is difficult to estimate the unique effects of individual software metrics in the regression equation. The estimated values of the coefficients are very sensitive to slight changes in the data and to the addition or deletion of variables in the regression equation. Since most of the existing metrics have common elements and are linear combinations of these common elements, it seems reasonable to investigate the structure of the underlying common factors or components that make up the raw metrics. The technique we have chosen to use to explore this structure is a procedure called principal components analysis. Principal components analysis is a decomposition technique that may be used to detect and analyze collinearity in software metrics. When confronted with a large number of metrics measuring a single construct, it may be desirable to represent the set by some smaller number of variables that convey all, or most, of the information in the original set. Principal components are linear transformations of a set of random variables that summarize the information contained in the variables. The transformations are chosen so that the first component accounts for the maximal amount of variation of the measures of any possible linear transform; the second component accounts for the maximal amount of residual variation; and so on. The principal components are constructed so that they represent transformed scores on dimensions that are orthogonal. Through the use of principal components analysis, it is possible to have a set of highly related software attributes mapped into a small number of uncorrelated attribute domains. This definitively solves the problem of multi-collinearity in subsequent regression analysis. There are many software metrics in the literature, but principal component analysis reveals that there are few distinct sources of variation, i.e. dimensions, in this set of metrics. It would appear perfectly reasonable to characterize the measurable attributes of a program with a simple function of a small number of orthogonal metrics each of which represents a distinct software attribute domain.

Munson, John C.↗

NASA NTRS2014

NASA's Space Launch System: An Enabling Capability for Discovery

The National Aeronautics and Space Administration's (NASA's) Space Launch System (SLS) Program, managed at the Marshall Space Flight Center, is making progress toward delivering a new capability for human spaceflight and scientific missions beyond Earth orbit. Developed with the goals of safety, affordability, and sustainability in mind, the SLS rocket will launch the Orion Multi-Purpose Crew Vehicle (MPCV), equipment, supplies, and major science missions for exploration and discovery. Making its first uncrewed test flight in 2017 and its first crewed flight in 2021, the SLS will evolve into the most powerful launch vehicle ever flown, capable of supporting human missions into deep space and to Mars. This paper will summarize the planned capabilities of the vehicle, the progress the SLS Program has made in the years since the Agency formally announced its architecture in September 2011, and the path the program is following to reach the launch pad in 2017 and then to evolve the 70 metric ton (t) initial lift capability to 130 t lift capability. The paper will outline the milestones the program has already reached, from developmental milestones such as the manufacture of the first flight hardware and recordbreaking engine testing, to life-cycle milestones such as the vehicle's Preliminary Design Review in the summer of 2013. The paper will also discuss the remaining challenges in both delivering the 70 t vehicle and in evolving its capabilities to the 130 t vehicle, and how the program plans to accomplish these goals. In addition, this paper will demonstrate how the Space Launch System is being designed to enable or enhance not only human exploration missions, but robotic scientific missions as well. Because of its unique launch capabilities, SLS will support simplifying spacecraft complexity, provide improved mass margins and radiation mitigation, and reduce mission durations. These capabilities offer attractive advantages for ambitious science missions by reducing infrastructure requirements, cost, and schedule. A traditional baseline approach for a mission to investigate the Jovian system would require a complicated trajectory with several gravity-assist planetary fly-bys to achieve the necessary outbound velocity. The SLS rocket, offering significantly higher C3 energies, can more quickly and effectively take the mission directly to its destination, providing scientific results sooner and at lower operational cost. The SLS rocket will launch payloads of unprecedented mass and volume, such as "monolithic" telescopes and in-space infrastructure, and will revolutionize science mission planning and design for years to come. As this paper will explain, SLS is making measurable progress toward becoming a global infrastructure asset for robotic and human scouts of all nations by harnessing business and technological innovations to deliver sustainable solutions for space exploration.

Creech, Stephen D.↗

NASA NTRS2014

NASA's Space Launch System: An Enabling Capability for Discovery

Creech, Stephen D.↗

NASA NTRS2011

Source Lines Counter (SLiC) Version 4.0

Source Lines Counter (SLiC) is a software utility designed to measure software source code size using logical source statements and other common measures for 22 of the programming languages commonly used at NASA and the aerospace industry. Such metrics can be used in a wide variety of applications, from parametric cost estimation to software defect analysis. SLiC has a variety of unique features such as automatic code search, automatic file detection, hierarchical directory totals, and spreadsheet-compatible output. SLiC was written for extensibility; new programming language support can be added with minimal effort in a short amount of time. SLiC runs on a variety of platforms including UNIX, Windows, and Mac OSX. Its straightforward command-line interface allows for customization and incorporation into the software build process for tracking development metrics. T

Monson, Erik W.↗

NASA NTRS2012

A Change Impact Analysis to Characterize Evolving Program Behaviors

Change impact analysis techniques estimate the potential effects of changes made to software. Directed Incremental Symbolic Execution (DiSE) is an intraprocedural technique for characterizing the impact of software changes on program behaviors. DiSE first estimates the impact of the changes on the source code using program slicing techniques, and then uses the impact sets to guide symbolic execution to generate path conditions that characterize impacted program behaviors. DiSE, however, cannot reason about the flow of impact between methods and will fail to generate path conditions for certain impacted program behaviors. In this work, we present iDiSE, an extension to DiSE that performs an interprocedural analysis. iDiSE combines static and dynamic calling context information to efficiently generate impacted program behaviors across calling contexts. Information about impacted program behaviors is useful for testing, verification, and debugging of evolving programs. We present a case-study of our implementation of the iDiSE algorithm to demonstrate its efficiency at computing impacted program behaviors. Traditional notions of coverage are insufficient for characterizing the testing efforts used to validate evolving program behaviors because they do not take into account the impact of changes to the code. In this work we present novel definitions of impacted coverage metrics that are useful for evaluating the testing effort required to test evolving programs. We then describe how the notions of impacted coverage can be used to configure techniques such as DiSE and iDiSE in order to support regression testing related tasks. We also discuss how DiSE and iDiSE can be configured for debugging finding the root cause of errors introduced by changes made to the code. In our empirical evaluation we demonstrate that the configurations of DiSE and iDiSE can be used to support various software maintenance tasks

Rungta, Neha Shyam↗

NASA NTRS2019

Scenario Complexity for Unmanned Aircraft System Traffic

This work introduces an approach to estimate the complexity of a low-altitude air traffic scenario involving multiple UASs using mathematical programming. Given a set of multi-point UAS flight trajectories, vehicle dynamics, and a conflict resolution algorithm, an abstract model is developed such that it can be solved quickly using a mathematical programming optimization software without running high-fidelity simulations that can be computationally expensive and may not suit real-time apA quick and accurate assessment of complexity for a given traffic scenario can help plan and schedule flights to alleviate traffic bottleneck and mitigate operation risks, especially for unmanned aerial system traffic management where high traffic density or complexity is expected. This work introduces a traffic scenario complexity metric that was constructed based on the number of potential conflicts weighted by the conflict resolution cost associated. The cost associated with a conflict is calculated based on the corresponding conflict resolution maneuvers. To obtain the conflict resolution maneuvers, a MILP-based optimization was formulated with the vehicle model and conflict management parameters incorporated. To evaluate the complexity metrics, an approach of using measurements from high-fidelity simulations was proposed. The scenario complexity measurements for 920 random-generated scenarios were obtained through high-fidelity simulations and treated as the ground truth. Two statistics methods: Pearson and Alternative Conditional Expectations were applied for analysis. The results showed that the number of flights has low correlation with the scenario complexity according to the correlation coefficients calculated by both methods. The Alternative Conditional Expectations method shows that the proposed scenario complexity metric has better correlation with the ground truth than the number of potential conflicts.plications. In the abstract model, each vehicle is represented by a time-varied vector associated with position, speed, and heading information. The total extra distance that aircraft need to divert from their original routes to avoid collisions is computed and used to setup a quadratic programming formula. The metrics including the number of conflicts and extra distances travelled by all vehicles are then utilized to estimate the complexity of a given UAS flight scenario. Results and verification against high-fidelity simulations will be provided in the final draft.

traffic complexity↗

NASA NTRS1982

Program to compute the positions of the aircraft and of the aircraft sensor footprints

The positions of the ground track of the aircraft and of the aircraft sensor footprints, in particular the metric camera and the radar scatterometer on the C-130 aircraft, are estimated by a program called ACTRK. The program uses the altitude, speed, and attitude informaton contained in the radar scatterometer data files to calculate the positions. The ACTRK program is documented.

Paris, J. F.↗

NASA NTRS1989

Variable-Metric Algorithm For Constrained Optimization

Variable Metric Algorithm for Constrained Optimization (VMACO) is nonlinear computer program developed to calculate least value of function of n variables subject to general constraints, both equality and inequality. First set of constraints equality and remaining constraints inequalities. Program utilizes iterative method in seeking optimal solution. Written in ANSI Standard FORTRAN 77.

Frick, James D.↗

NASA NTRS1997

An Improved Suite of Object Oriented Software Measures

In the pursuit of ever increasing productivity, the need to be able to measure specific aspects of software is generally agreed upon. As object oriented programming languages are becoming more and more widely used, metrics specifically designed for object oriented software are required. In recent years there has been an explosion of new, object oriented software metrics proposed in the literature. Unfortunately, many or most of these proposed metrics have not been validated to measure what they claim to measure. In fact, an analysis of many of these metrics shows that they do not satisfy basic properties of measurement theory, and thus their application has to be suspect. In this paper ten improved metrics are proposed and are validated using measurement theory.

Neal, Ralph D.↗

NASA NTRS2010

The Role and Quality of Software Safety in the NASA Constellation Program

In this study, we examine software safety risk in the early design phase of the NASA Constellation spaceflight program. Obtaining an accurate, program-wide picture of software safety risk is difficult across multiple, independently-developing systems. We leverage one source of safety information, hazard analysis, to provide NASA quality assurance managers with information regarding the ongoing state of software safety across the program. The goal of this research is two-fold: 1) to quantify the relative importance of software with respect to system safety; and 2) to quantify the level of risk presented by software in the hazard analysis. We examined 154 hazard reports created during the preliminary design phase of three major flight hardware systems within the Constellation program. To quantify the importance of software, we collected metrics based on the number of software-related causes and controls of hazardous conditions. To quantify the level of risk presented by software, we created a metric scheme to measure the specificity of these software causes. We found that from 49-70% of hazardous conditions in the three systems could be caused by software or software was involved in the prevention of the hazardous condition. We also found that 12-17% of the 2013 hazard causes involved software, and that 23-29% of all causes had a software control. Furthermore, 10-12% of all controls were software-based. There is potential for inaccuracy in these counts, however, as software causes are not consistently scoped, and the presence of software in a cause or control is not always clear. The application of our software specificity metrics also identified risks in the hazard reporting process. In particular, we found a number of traceability risks in the hazard reports may impede verification of software and system safety.

Layman, Lucas↗

NASA NTRS2017

Knowledge Base for Distributed Spacecraft Mission Design Using the Trade-Space Analysis Tool for Constellations (TAT-C)

Opportunities for multi-point measurements, greater revisit frequency, failure robustness, and improved cost effectiveness motivate consideration of Distributed Spacecraft Missions (DSMs) for future Earth science missions. However, careful analysis is required to assess the distributed sensing capabilities of a constellation compared to more mature monolithic spacecraft while also considering other important dimensions such as cost and risk. The large combinatorial DSM design space limits existing mission analysis tools and exploration methods which emphasize monolithic design variables. The Trade-space Analysis Tool for Constellations (TAT-C) under development at Goddard seeks to enumerate and evaluate alternative mission architectures to minimize cost and maximize scientific return for pre-defined goals during pre-phase A analysis.Similar to other model-centric engineering efforts, efficient data management is a significant challenge for DSM mission analysis. In TAT-C, a Knowledge Base (KB) is envisioned as a cumulative central repository of information and meta-information about DSMs. Initial KB concepts store related data for reuse within or across mission analyses; however, over time, the KB is envisioned to be an important layer to coordinate actions of both human analysts and automated design agents to search a large design space for desirable mission alternatives. Preliminary KB research builds on a modern web technology stack to provide the following functionality: 1) storage of trade-space search requests which set requirements and constraints for DSM concepts, 2) storage of analysis results which quantify performance metrics for evaluated DSM concepts, 3) a RESTful application programming interface (API) for scripted access to data from TAT-C modules, 4) web-based graphical user interface (GUI) for manual access to underlying data, and 5) access control and management restrictions relevant to data protection and security. These efforts have culminated in a prototype KB used by the research team during TAT-C development to assess opportunities for future work.

Pattern Recognition↗

NASA NTRS2024

NASA Engineering and Safety Center Lunar Rover Design Concepts Assessments

Mass is a significant risk to programs and projects as they transition from formulation to implementation, especially in larger human space systems where delivery mass or volume can be a constrained commodity. • Concepts developed without an adequate systems-engineering basis, including design and operations experience, may miss significant functionality and subsequent mass required for integration or operations. • Further uncertainty can be associated with not fully understanding design best practices and standards that drive mass, such as design for minimum risk or fault tolerance.1 • Finally, the appropriate systems engineering mass properties management rigor and technical discipline insight are required to set the mass baseline, including appropriate mass growth allowance (MGA) to ensure program success. Mass is a key quantity that should be constantly monitored by the systems engineer and the program/project management stakeholder to ensure mission compatibility throughout the project life cycle. In addition, mass is a key programmatic performance metric monitored by the NASA Chief Financial Officer for current and future program cost estimating. NASA Exploration Systems sought an assessment of reasonableness with respect to different potential rover concepts that balances mass needs and human-class cargo lander capabilities. Appropriate systems engineering mass properties management rigor and technical discipline insight were used, and are required to set the mass baseline, including appropriate MGA to ensure program success. Two independent Lunar rover concepts were evaluated, with a goal to understand concept credibility and the Lunar rover designs potential extensibility for Mars surface operations. A notional generic rover concept is shown in Figure 1.

Systems Engineering↗

NASA NTRS2014

An Overview of the Characterization of the Space Launch Vehicle Aerodynamic Environments

Aerodynamic environments are some of the rst engineering data products that are needed to design a space launch vehicle. These products are used in performance predic- tions, vehicle control algorithm design, as well as determing loads on primary and secondary structures in multiple discipline areas. When the National Aeronautics and Space Admin- istration (NASA) Space Launch System (SLS) Program was established with the goal of designing a new, heavy-lift launch vehicle rst capable of lifting the Orion Program Multi- Purpose Crew Vehicle (MPCV) to low-earth orbit and preserving the potential to evolve the design to a 200 metric ton cargo launcher, the data needs were no di erent. Upon commencement of the new program, a characterization of aerodynamic environments were immediately initiated. In the time since, the SLS Aerodynamics Team has produced data describing the majority of the aerodynamic environment de nitions needed for structural design and vehicle control under nominal ight conditions. This paper provides an overview of select SLS aerodynamic environments completed to date.

Blevins, John A.↗

NASA NTRS2019

Metric Tracking Services in the Era of Optical Communications

The Space Communications and Navigation program, at the National Aeronautics and Space Administration, is developing free-space optical communications technology to facilitate the next generation of space missions in near-Earth, Lunar, and planetary space. A discussion of optimetric observation performance and hardware-in-the-loop test results are presented. Simulation of orbit-determination for LEO and Lunar spacecraft relying on optimetric tracking extends raw observation accuracy to realizable orbit-determination performance. Potential science and operational applications are reviewed, along with NASA's approach for developing optimetric technology. Current investments in developing optimetric hardware and plans for NASA's future optical communications network define the path for a future operational optimetric capability in the 2020's and beyond.

optimetrics↗

NASA NTRS2001

Shuttle-Mir: The United States and Russia Share History's Highest Stage

This book is an example of what may become the norm for history texts-an illustrated narrative accompanied by a CD-ROM. The text tells the story from the human side. It is based on reflections and quotes from the astronauts, cosmonauts, and team members who participated in the historic partnership. The main chapters give the perspectives of the seven U.S. astronauts living on Mir. The "STS boxes" share the Space Shuttle crews' experiences from the 11 Shuttle-Mir missions. The "Meanwhile on Earth" sections provide details of what was happening on Earth while the attention of the Program focused on the situations in space. The text reflects conventional usage; that is, temperature is given in degrees Fahrenheit, and metrics are used as appropriate. While this publication provides an accurate overview of the Shuttle-Mir Program, the reader is encouraged to explore the companion CD-ROM. It contains a complete, searchable text of the book itself plus source publications, mission data, status reports, drawings and illustrations, videos and hundreds of images, and even a virtual Shuttle-Mir children's book. Of particular interest are the Shuttle-Mir oral history transcripts and the letters written by American astronauts while they were in residence on the Russian space station. Many of the quotes in "Shuttle-Mir: The U.S. and Russia Share History's Highest Stage" came from sources located on the CD-ROM. The reader is invited to explore the Shuttle-Mir story through the words, images, and insights of those who took part in it.

Morgan, Clay↗

NASA NTRS1996

Utilization of an agility assessment module in analysis and optimization of preliminary fighter configuration

A study has been conducted to develop and to analyze a FORTRAN computer code for performing agility analysis on fighter aircraft configurations. This program is one of the modules of the NASA Ames ACSYNT (AirCraft SYNThesis) design code. The background of the agility research in the aircraft industry and a survey of a few agility metrics are discussed. The methodology, techniques, and models developed for the code are presented. The validity of the existing code was evaluated by comparing with existing flight test data. A FORTRAN program was developed for a specific metric, PM (Pointing Margin), as part of the agility module. Example trade studies using the agility module along with ACSYNT were conducted using a McDonnell Douglas F/A-18 Hornet aircraft model. Tile sensitivity of thrust loading, wing loading, and thrust vectoring on agility criteria were investigated. The module can compare the agility potential between different configurations and has capability to optimize agility performance in the preliminary design process. This research provides a new and useful design tool for analyzing fighter performance during air combat engagements in the preliminary design.

Ngan, Angelen↗

NASA NTRS1999

Systems Engineering Design Via Experimental Operation Research: Complex Organizational Metric for Programmatic Risk Environments (COMPRE)

Unique and innovative graph theory, neural network, organizational modeling, and genetic algorithms are applied to the design and evolution of programmatic and organizational architectures. Graph theory representations of programs and organizations increase modeling capabilities and flexibility, while illuminating preferable programmatic/organizational design features. Treating programs and organizations as neural networks results in better system synthesis, and more robust data modeling. Organizational modeling using covariance structures enhances the determination of organizational risk factors. Genetic algorithms improve programmatic evolution characteristics, while shedding light on rulebase requirements for achieving specified technological readiness levels, given budget and schedule resources. This program of research improves the robustness and verifiability of systems synthesis tools, including the Complex Organizational Metric for Programmatic Risk Environments (COMPRE).

Mog, Robert A.↗

NASA NTRS2018

NASA's Space Launch System Moves into Testing and Integration

NASA's Space Launch System (SLS) has moved from design and manufacturing into testing and integration for its first flight in fiscal year 2020. In 2017, the NASA/industry team completed manufacturing of all major structural elements for the launch vehicle for Exploration Mission-1 (EM-1). This work included shipping the first major flight hardware element to the launch site. Current work is focused on the initial Block 1 variant of SLS, capable of launching more than 70 metric tons (t) to low Earth orbit (LEO). As the needs of the nation's deep space exploration program grow, SLS performance is designed to evolve to a payload mass of 130 t to LEO and up to 45 metric tons (t) to trans-lunar injection (TLI). The advantages of this mass - as well as volume - are critical to the entire exploration architecture for deep space exploration. They translate to greater capability, greater infrastructure and operational simplicity, less overall mission risk, and opportunities to accomplish unprecedented exploration and discovery.

Honeycutt, John↗