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At least 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

SEL's Software Process-Improvement Program

The goals and operations of the Software Engineering Laboratory (SEL) is reviewed. For nearly 20 years the SEL has worked to understand, assess, and improve software and the development process within the production environment of the Flight Dynamics Division (FDD) of NASA's Goddard Space Flight Center. The SEL was established in 1976 with the goals of reducing: (1) the defect rate of delivered software, (2) the cost of software to support flight projects, and (3) the average time to produce mission-support software. After studying over 125 projects of FDD, the results have guided the standards, management practices, technologies, and the training within the division. The results of the studies have been a 75 percent reduction in defects, a 50 percent reduction in cost, and a 25 percent reduction in development time. Over time the goals of SEL have been clarified. The goals are now stated as: (1) Understand baseline processes and product characteristics, (2) Assess improvements that have been incorporated into the development projects, (3) Package and infuse improvements into the standard SEL process. The SEL improvement goal is to demonstrate continual improvement of the software process by carrying out analysis, measurement and feedback to projects with in the FDD environment. The SEL supports the understanding of the process by study of several processes including, the effort distribution, and error detection rates. The SEL assesses and refines the processes. Once the assessment and refinement of a process is completed, the SEL packages the process by capturing the process in standards, tools and training.

Basili, Victor↗
DOE OSTI2018

High Fidelity Fast Running Multi-scale Multi-physics Battery Pack Software

The project team comprising of General Motors LLC (GM), ANSYS, ESim, and the National Renewable Energy Laboratory (NREL) proposed to develop multiscale multiphysics battery pack engineering software that significantly surpassed the most advanced state-of-the-art software in computational speed and accuracy. The successful software was to run faster than current state-of-the-art software by a factor of 100 while resolving complex multiphysics interplays across the scales from materials to large automotive battery pack systems. The proposed project was to shift the paradigm to using software for battery pack system design and evaluation, potentially revolutionizing the standard development process for the broader electric vehicle industry. The project objectives were to: (a) enhance computation speed and stability of the pack level multiscale model while still resolving nonlinearities of the battery’s dynamic responses across the scales from particles to a battery pack and (b) enhance multiphysics integrity at the pack level model enabling model-based diagnostics and prognostics for life and safety.

25 ENERGY STORAGE↗
NASA NTRS1992

Description of research interests and current work related to automating software design

Enclosed is a list of selected and recent publications. Most of these publications concern applied research in the areas of software engineering and human-computer interaction. It is felt that domain-specific knowledge plays a major role in software development. Additionally, it is believed that improvements in the general software development process (e.g., object-oriented approaches) will have to be combined with the use of large domain-specific knowledge bases.

Kaindl, Hermann↗
NASA NTRS1994

A measurement system for large, complex software programs

This paper describes measurement systems required to forecast, measure, and control activities for large, complex software development and support programs. Initial software cost and quality analysis provides the foundation for meaningful management decisions as a project evolves. In modeling the cost and quality of software systems, the relationship between the functionality, quality, cost, and schedule of the product must be considered. This explicit relationship is dictated by the criticality of the software being developed. This balance between cost and quality is a viable software engineering trade-off throughout the life cycle. Therefore, the ability to accurately estimate the cost and quality of software systems is essential to providing reliable software on time and within budget. Software cost models relate the product error rate to the percent of the project labor that is required for independent verification and validation. The criticality of the software determines which cost model is used to estimate the labor required to develop the software. Software quality models yield an expected error discovery rate based on the software size, criticality, software development environment, and the level of competence of the project and developers with respect to the processes being employed.

Rone, Kyle Y.↗
NASA NTRS1999

Prototype Tool Support for SEI Process and Risk Knowledge

We have developed a prototype of tool support for risk assessment that uses selected components of the Software Engineering Institute (SEI) information, specifically: Capability Maturity Model (CMM) process activities, CMM process goals and the SEI taxonomy of software project risks.

risk management risk assessment SEI CMM software r↗
DOE OSTI2021

Automating Software Productivity Planning: Lightweight Tools for Upgrading Team Practices

A lightweight iterative workflow, called Productivity and Sustainability Improvement Planning (PSIP) has been developed to assist software teams with employing good software engineering practices. Three PSIP tools automate practice summarization, self-assessment, and progress tracking to enhance team engagement around software process improvement: Reposcanner, RateYourProject (RYP) and Progress Tracking Cards (PTCs) respectively. Reposcanner is a data analysis tool. RYP is an interactive self-assessment tool that provides an easy-to-use entry point to the PSIP process. Once process improvements are identified, PTCs are created by teams to measure outcomes and progression toward their goals. We present an exemplifying case study with a software team where these tools have been put to use, along with a description of the tools, and future plans for further improvements.

Raybourn, Elaine↗
NASA NTRS2014

More Than A SketchUp

This 2014 summer internship assignment at John F. Kennedy Space Center (K.S.C) was conducted with the National Aeronautics and Space Administration (NASA) Engineering and Technology (NE) group in support of the Control and Data Systems Division (NE-C) within the Test, Operations & Support Software Engineering Branch (NE-C2). The primary focus of this project was to assist Branch Chief Laurie B. Griffin, to support NASA's Small Payload Launch Integrated Testing Services (SPLITS) mission, by mastering the capabilities of 3-D modeling software called SketchUp. I used SketchUp to create a virtual environment for different laboratories of the NE-00 Division. My mission was to have these models uploaded into a K.S.C Partnerships Website and be used as a visual aid to viewers who browsed the site. The leads of this project were Kay L. Craig, Business and Industry Specialist (AD-A) and Steven E. Cain, (FA-C). I teamed with fellow intern Tait Sorenson of the Flight Structures and Thermal Protection Systems Branch (NE-M5) and met with many K.S.C lab managers willing to display their lab's structure and capabilities. The information collected during these lab tours was vital to the building of the K.S.C Partnerships Website. To accomplish this goal Sorenson and I later teamed with fellow Marketing intern Marlee Pereda-Ramos, of the Spaceport Planning Office In Center Planning And Development (AD-A) Along with Ramos, Tait and I toured an array of laboratories and got first hand exposure to their functions and capabilities.

Trimble Corporation↗
NASA NTRSDate not supplied

From the Knowledge-based Digital Platform (KbDP) Concept for Advanced Air Mobility Research to a Preliminary Prototype

Advanced Air Mobility (AAM) encompasses a range of innovative operational and technological changes to aviation (electric aircraft, increasingly automated aircraft, increasingly automated airspace operations, etc.) that are transforming aviation’s role in everyday movement of people and goods. There are multiple associated concepts and use cases for AAM, all interrelated, including small Unmanned Aircraft System (UAS) Traffic Management (UTM), Upper-Class E Traffic Management (ETM), Extensible Traffic Management (xTM), Regional Air Mobility (RAM), and Urban Air Mobility (UAM). These AAM operations must integrate with traditional Air Traffic Management (ATM) operations, as well as non-aviation modes of transportation and logistics. National Aeronautics and Space Administration (NASA) is spearheading an innovative digital engineering approach to integrate, communicate, and facilitate the research of multi-modal transportation systems. The Knowledge-based Digital Platform (KbDP) is a concept being developed that ties the workflows of Project Managers (PM), Principal Investigators (PI), and System Engineers together across organizational boundaries. It does so through the management of an information database defined by mathematical, data science, and system engineering principles. Machine Learning (ML) algorithms play a key role in this concept by extracting meaningful knowledge from the information database, which the human user leverages to greatly improve the efficiency and effectiveness of their research. Expected benefits of this concept include improved technology transfers from research to production, improved research portfolio investments, and research outcomes that are more integrated with all aspects of the multi-modal transportation problem. The preliminary KbDP prototype has been realized using UAM as a pathfinder use case and developed by a team of system engineer, software developer, data scientist, and interns.

Systems Engineering↗
DOE OSTI2021

Summarizing the interoperabilities between xSDK members

Rapid, efficient production of high-quality, sustainable extreme-scale scientific applications is best accomplished using a rich ecosystem of state-of-the art reusable libraries, tools, lightweight frameworks, and defined software methodologies, developed by a community of scientists who are striving to identify, adapt, and adopt best practices in software engineering. The vision of the xSDK is to provide infrastructure for and interoperability of a collection of related and complementary software elements — developed by diverse, independent teams throughout the high-performance computing (HPC) community — that provide the building blocks, tools, models, processes, and related artifacts for rapid and efficient development of high-quality applications. A primary component, and challenge, of the xSDK is to improve interoperability among software libraries and domain components. This document summarizes the current and planned interoperabilities of the twenty-three xSDK member packages as of March 2021. Additionally, the status of the xSDK example codes that demonstrate and test the interoperabilities within the xSDK is provided.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Finding the missing pieces: filling gaps that impede the translation of omics data into models

High-throughput omics technologies such as DNA sequencing have made the sequencing and computational assembly of microbial genomes recovered from the environment relatively routine. Computational inference of the protein products encoded by these genomes, and the associated biochemical functions, should enable the accurate prediction and modeling of microbial metabolism, organismal interactions, and ecosystem processes. However, a lack of scalable, probabilistic protein annotation tools limits the full potential of modeling for understanding the metabolism and biogeochemical cycles of microbial communities. Our approach to improve inference of protein annotations and metabolic models relied on learning from and emulating expert manual curation, leveraging software engineering and data science best practices to scale up the throughput and accuracy of annotations and metabolic model construction, building software to objectively evaluate different annotation strategies, and more closely linking the protein annotation and metabolic model inference process. Outcomes of this research include several improved or new computational tools, including DRAM (Distilled and Refined Annotation of Metabolism) for annotating microbial genomes with protein function and metabolic traits, CAMPER (Curated Annotations for Microbial Polyphenol Enzymes and Reactions) for annotating key polyphenol metabolisms, EC-Bench for comprehensive and unbiased benchmarking of annotation tools, and several apps available via the DOE Systems Biology Knowledgebase (KBase) for building genome-scale metabolic models. We demonstrate that these tools allow us to scalably annotate and understand thousands of genomes for microbial communities from a variety of systems and test cases, including rivers, thawing permafrost, and gut microbiomes. All of these computational tools are available as open-source software, with most broadly and easily accessible to the scientific community via KBase apps.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1986

Towards a document structure editor for software requirements analysis

Of the six or seven phases of the software engineering life cycle, requirements analysis tends to be the least understood and the least formalized. Correspondingly, a scarcity of useful software tools exist which aid in the development of user and system requirements. It is proposed that requirements analysis should culminate in a set of documents similar to those that usually accompany a delivered Software product. The design of a software tool, the Document Structure Editor, which facilitates the development of such documentation.

Kowalski, Vincent J.↗
NASA NTRS1988

Empirical studies of software design: Implications for SSEs

Implications for Software Engineering Environments (SEEs) are presented in viewgraph format for characteristics of projects studied; significant problems and crucial problem areas in software design for large systems; layered behavioral model of software processes; implications of field study results; software project as an ecological system; results of the LIFT study; information model of design exploration; software design strategies; results of the team design study; and a list of publications.

Krasner, Herb↗
NASA NTRS1992

Toward full life cycle control: Adding maintenance measurement to the SEL

Organization-wide measurement of software products and processes is needed to establish full life cycle control over software products. The Software Engineering Laboratory (SEL)--a joint venture between NASA GSFC, the University of Maryland, and Computer Sciences Corporation--started measurement of software development more than 15 years ago. Recently, the measurement of maintenance was added to the scope of the SEL. In this article, the maintenance measurement program is presented as an addition to the already existing and well-established SEL development measurement program and evaluated in terms of its immediate benefits and long-term improvement potential. Immediate benefits of this program for the SEL include an increased understanding of the maintenance domain, the differences and commonalities between development and maintenance, and the cause-effect relationships between development and maintenance. Initial results from a sample maintenance study are presented to substantiate these benefits. The long-term potential of this program includes the use of maintenance baselines to better plan and manage future projects and to improve development and maintenance practices for future projects wherever warranted.

Rombach, H. Dieter↗
DOE OSTI2015

Continuous integration for concurrent MOOSE framework and application development on GitHub

For the past several years, Idaho National Laboratory’s MOOSE framework team has employed modern software engineering techniques (continuous integration, joint application/framework source code repos- itories, automated regression testing, etc.) in developing closed-source multiphysics simulation software (Gaston et al., Journal of Open Research Software vol. 2, article e10, 2014). In March 2014, the MOOSE framework was released under an open source license on GitHub, significantly expanding and diversifying the pool of current active and potential future contributors on the project. Despite this recent growth, the same philosophy of concurrent framework and application development continues to guide the project’s development roadmap. Several specific practices, including techniques for managing multiple repositories, conducting automated regression testing, and implementing a cascading build process are discussed in this short paper. Furthermore, special attention is given to describing the manner in which these practices naturally synergize with the GitHub API and GitHub-specific features such as issue tracking, Pull Requests, and project forks.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1989

Some issues related to simulation of the tracking and communications computer network

The Communications Performance and Integration branch of the Tracking and Communications Division has an ongoing involvement in the simulation of its flight hardware for Space Station Freedom. Specifically, the communication process between central processor(s) and orbital replaceable units (ORU's) is simulated with varying degrees of fidelity. The results of investigations into three aspects of this simulation effort are given. The most general area involves the use of computer assisted software engineering (CASE) tools for this particular simulation. The second area of interest is simulation methods for systems of mixed hardware and software. The final area investigated is the application of simulation methods to one of the proposed computer network protocols for space station, specifically IEEE 802.4.

Lacovara, Robert C.↗
NASA NTRS1990

AdaNET research plan

The mission of the AdaNET research effort is to determine how to increase the availability of reusable Ada components and associated software engineering technology to both private and Federal sectors. The effort is structured to define the requirements for transfer of Federally developed software technology, study feasible approaches to meeting the requirements, and to gain experience in applying various technologies and practices. The overall approach to the development of the AdaNET System Specification is presented. A work breakdown structure is presented with each research activity described in detail. The deliverables for each work area are summarized. The overall organization and responsibilities for each research area are described. The schedule and necessary resources are presented for each research activity. The estimated cost is summarized for each activity. The project plan is fully described in the Super Project Expert data file contained on the floppy disk attached to the back cover of this plan.

Mcbride, John G.↗
NASA NTRS1990

Evaluation of an expert system for fault detection, isolation, and recovery in the manned maneuvering unit

The authors explore issues in the specification, verification, and validation of artificial intelligence (AI) based software, using a prototype fault detection, isolation and recovery (FDIR) system for the Manned Maneuvering Unit (MMU). They use this system as a vehicle for exploring issues in the semantics of C-Language Integrated Production System (CLIPS)-style rule-based languages, the verification of properties relating to safety and reliability, and the static and dynamic analysis of knowledge based systems. This analysis reveals errors and shortcomings in the MMU FDIR system and raises a number of issues concerning software engineering in CLIPs. The authors came to realize that the MMU FDIR system does not conform to conventional definitions of AI software, despite the fact that it was intended and indeed presented as an AI system. The authors discuss this apparent disparity and related questions such as the role of AI techniques in space and aircraft operations and the suitability of CLIPS for critical applications.

Rushby, John↗
NASA NTRS1990

A conceptual model for megaprogramming

Megaprogramming is component-based software engineering and life-cycle management. Magaprogramming and its relationship to other research initiatives (common prototyping system/common prototyping language, domain specific software architectures, and software understanding) are analyzed. The desirable attributes of megaprogramming software components are identified and a software development model and resulting prototype megaprogramming system (library interconnection language extended by annotated Ada) are described.

Tracz, Will↗