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At least 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Cyber-Informed Engineering Implementation Guide: Version 1.0 [Slides]

This Implementation Guide describes the principles of Cyber-Informed Engineering (CIE) and outlines questions that engineering teams should consider during each phase of a system's lifecycle to effectively employ these principles. It describes what it means to engineer systems in a cyber-informed way, rather than offering a comprehensive, step-by-step process or procedure for CIE implementation. This guide complements - but does not replace - the application of cybersecurity standards or practices currently in place within an organization. Engineers and technicians that design critical energy infrastructure installations can use this Implementation Guide to integrate the 12 principles of CIE into each phase of the engineering lifecycle, from concept to retirement. The guide is aimed at system or design engineers, rather than software engineers or operational cybersecurity practitioners. The engineers who design, build, operate, and maintain the physical infrastructure are best positioned to leverage a system's engineering design to diminish the severity of cyber attacks or digital technology failures. CIE expands cybersecurity decisions into the engineering space, not by asking engineers to become cyber experts, but by calling on engineers to apply engineering tools and make engineering decisions that improve cybersecurity outcomes. CIE examines the engineering consequences that a sophisticated cyber attacker could achieve and drives engineering changes that may provide deterministic mitigations to limit or eliminate those consequences.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1986

Software testing - A way to improve software reliability

Various software testing techniques are described. The techniques are classified as dynamic or static, structural or functional, and manual or automated. The objects tested include the elements designed during the development of the software, such as codes, data structures, and requirements. Testing techniques and procedures applicable to each phase of software development are examined; the development phases are: software requirements analysis, preliminary design, detailed design, coding, testing, and operation and maintenance. The characteristics of a future software engineering environment for software testing and validation are discussed.

Mahindru, Andy↗
NASA NTRS1989

AdaNET services

MountainNet is a small firm which serves as a distribution center for AdaNET Services. These services include providing host systems and telecommunications for AdaNET, developing and supporting AdaNET Information Services, and developing a dynamic software inventory. AdaNET hosts are a Data General MV8000II and DEC VAX. Telecommunications are provided via the MountainNet private network and the Telenet public access dial network. Initially, the AdaNET Information Services will include software repositories, user communications and forums, software engineering information, bibliographic and library services, and an educational directory. The dynamic software inventory, which will become available in January 1990, will contain software engineering code and parts.

Digman, Michael↗
NASA NTRS1990

An expert system based software sizing tool, phase 2

A software tool was developed for predicting the size of a future computer program at an early stage in its development. The system is intended to enable a user who is not expert in Software Engineering to estimate software size in lines of source code with an accuracy similar to that of an expert, based on the program's functional specifications. The project was planned as a knowledge based system with a field prototype as the goal of Phase 2 and a commercial system planned for Phase 3. The researchers used techniques from Artificial Intelligence and knowledge from human experts and existing software from NASA's COSMIC database. They devised a classification scheme for the software specifications, and a small set of generic software components that represent complexity and apply to large classes of programs. The specifications are converted to generic components by a set of rules and the generic components are input to a nonlinear sizing function which makes the final prediction. The system developed for this project predicted code sizes from the database with a bias factor of 1.06 and a fluctuation factor of 1.77, an accuracy similar to that of human experts but without their significant optimistic bias.

Friedlander, David↗
NASA NTRS1994

Model-based software process improvement

The activities of a field test site for the Software Engineering Institute's software process definition project are discussed. Products tested included the improvement model itself, descriptive modeling techniques, the CMM level 2 framework document, and the use of process definition guidelines and templates. The software process improvement model represents a five stage cyclic approach for organizational process improvement. The cycles consist of the initiating, diagnosing, establishing, acting, and leveraging phases.

Zettervall, Brenda T.↗
NASA NTRS1994

Using CLIPS in the domain of knowledge-based massively parallel programming

The Program Development Environment (PDE) is a tool for massively parallel programming of distributed-memory architectures. Adopting a knowledge-based approach, the PDE eliminates the complexity introduced by parallel hardware with distributed memory and offers complete transparency in respect of parallelism exploitation. The knowledge-based part of the PDE is realized in CLIPS. Its principal task is to find an efficient parallel realization of the application specified by the user in a comfortable, abstract, domain-oriented formalism. A large collection of fine-grain parallel algorithmic skeletons, represented as COOL objects in a tree hierarchy, contains the algorithmic knowledge. A hybrid knowledge base with rule modules and procedural parts, encoding expertise about application domain, parallel programming, software engineering, and parallel hardware, enables a high degree of automation in the software development process. In this paper, important aspects of the implementation of the PDE using CLIPS and COOL are shown, including the embedding of CLIPS with C++-based parts of the PDE. The appropriateness of the chosen approach and of the CLIPS language for knowledge-based software engineering are discussed.

Dvorak, Jiri J.↗
NASA NTRS1996

The Improvement Cycle: Analyzing Our Experience

NASA's Software Engineering Laboratory (SEL), one of the earliest pioneers in the areas of software process improvement and measurement, has had a significant impact on the software business at NASA Goddard. At the heart of the SEL's improvement program is a belief that software products can be improved by optimizing the software engineering process used to develop them and a long-term improvement strategy that facilitates small incremental improvements that accumulate into significant gains. As a result of its efforts, the SEL has incrementally reduced development costs by 60%, decreased error rates by 85%, and reduced cycle time by 25%. In this paper, we analyze the SEL's experiences on three major improvement initiatives to better understand the cyclic nature of the improvement process and to understand why some improvements take much longer than others.

Pajerski, Rose↗
NASA NTRS2007

A Software Safety Risk Taxonomy for Use in Retrospective Safety Cases

Safety standards contain technical and process-oriented safely requirements. The best time to include these requirements is early in the development lifecycle of the system. When software safety requirements are levied on a legacy system after the fact, a retrospective safety case will need to be constructed for the software in the system. This can be a difficult task because there may be few to no art facts available to show compliance to the software safely requirements. The risks associated with not meeting safely requirements in a legacy safely-critical computer system must be addressed to give confidence for reuse. This paper introduces a proposal for a software safely risk taxonomy for legacy safely-critical computer systems, by specializing the Software Engineering Institute's 'Software Development Risk Taxonomy' with safely elements and attributes.

Hill, Janice L.↗
DOE OSTI2023

Cyber-Informed Engineering Implementation Guide

This Implementation Guide describes the principles of Cyber-Informed Engineering (CIE) and outlines questions that engineering teams should consider during each phase of a system’s lifecycle to effectively employ these principles. It describes what it means to engineer systems in a cyber-informed way, rather than offering a comprehensive, step-by-step process or procedure for CIE implementation. This guide complements—but does not replace—the application of cybersecurity standards or practices currently in place within an organization. Engineers and technicians that design critical energy infrastructure installations can use this Implementation Guide to integrate the 12 principles of CIE into each phase of the engineering lifecycle, from concept to retirement. The guide is aimed at system or design engineers, rather than software engineers or operational cybersecurity practitioners. The engineers who design, build, operate, and maintain the physical infrastructure are best positioned to leverage a system’s engineering design to diminish the severity of cyber attacks or digital technology failures. CIE expands cybersecurity decisions into the engineering space, not by asking engineers to become cyber experts, but by calling on engineers to apply engineering tools and make engineering decisions that improve cybersecurity outcomes. CIE examines the engineering consequences that a sophisticated cyber attacker could achieve and drives engineering changes that may provide deterministic mitigations to limit or eliminate those consequences.

42 ENGINEERING↗
NASA NTRS1992

Impacts of object-oriented technologies: Seven years of SEL studies

The premise that object-oriented technology (OOT) is the most significant technology ever examined by the Software Engineering Laboratory is examined. The evolution of the use of OOT in the Software Engineering Laboratory (SEL) 'experience factory' is described in terms of the SEL's original expectations, focusing on how successive generations of projects have used OOT. General conclusions are drawn on how the usage of the technology has evolved in this environment.

Stark, Michael↗
NASA NTRS1993

Process improvement as an investment: Measuring its worth

This paper discusses return on investment (ROI) generated from software process improvement programs. It details the steps needed to compute ROI and compares these steps from the perspective of two process improvement approaches: the widely known Software Engineering Institute's capability maturity model and the approach employed by NASA's Software Engineering Laboratory (SEL). The paper then describes the specific investments made in the SEL over the past 18 years and discusses the improvements gained from this investment by the production organization in the SEL.

Mcgarry, Frank↗
NASA NTRS1996

The Impact of Ada and Object-Oriented Design in NASA Goddard's Flight Dynamics Division

This paper presents the highlights and key findings of 10 years of use and study of Ada and object-oriented design in NASA Goddard's Flight Dynamics Division (FDD). In 1985, the Software Engineering Laboratory (SEL) began investigating how the Ada language might apply to FDD software development projects. Although they began cautiously using Ada on only a few pilot projects, they expected that, if the Ada pilots showed promising results, the FDD would fully transition its entire development organization from FORTRAN to Ada within 10 years. However, 10 years later, the FDD still produced 80 percent of its software in FORTRAN and had begun using C and C++, despite positive results on Ada projects. This paper presents the final results of a SEL study to quantify the impact of Ada in the FDD, to determine why Ada has not flourished, and to recommend future directions regarding Ada. Project trends in both languages are examined as are external factors and cultural issues that affected the infusion of this technology. The detailed results of this study were published in a formal study report in March of 1995. This paper supersedes the preliminary results of this study that were presented at the Eighteenth Annual Software Engineering Workshop in 1993.

Waligora, Sharon↗
NASA NTRSDate not supplied

Feature-Guided Analysis of Neural Networks

Applying standard software engineering practices to neural networks is challenging due to the lack of high-level abstractions describing a neural network’s behavior. To address this challenge, we propose to extract high-level task-specific features from the neural network internal representation, based on monitoring the neural network activations.The extracted feature representations can serve as a link to high-level requirements and can be leveraged to enable fundamental software engineering activities, such as automated testing, debugging, requirements analysis, and formal verification, leading to better engineering of neural networks. Using two case studies, we present initial empirical evidence demonstrating the feasibility of our ideas.

Features↗
NASA NTRS1992

Maximizing reuse: Applying common sense and discipline

Computer Sciences Corporation (CSC)/System Sciences Division (SSD) has maintained a long-term relationship with NASA/Goddard, providing satellite mission ground-support software and services for 23 years. As a partner in the Software Engineering Laboratory (SEL) since 1976, CSC has worked closely with NASA/Goddard to improve the software engineering process. This paper examines the evolution of reuse programs in this uniquely stable environment and formulates certain recommendations for developing reuse programs as a business strategy and as an integral part of production. It focuses on the management strategy and philosophy that have helped make reuse successful in this environment.

Waligora, Sharon↗
NASA NTRS1988

Validation of highly reliable, real-time knowledge-based systems

Knowledge-based systems have the potential to greatly increase the capabilities of future aircraft and spacecraft and to significantly reduce support manpower needed for the space station and other space missions. However, a credible validation methodology must be developed before knowledge-based systems can be used for life- or mission-critical applications. Experience with conventional software has shown that the use of good software engineering techniques and static analysis tools can greatly reduce the time needed for testing and simulation of a system. Since exhaustive testing is infeasible, reliability must be built into the software during the design and implementation phases. Unfortunately, many of the software engineering techniques and tools used for conventional software are of little use in the development of knowledge-based systems. Therefore, research at Langley is focused on developing a set of guidelines, methods, and prototype validation tools for building highly reliable, knowledge-based systems. The use of a comprehensive methodology for building highly reliable, knowledge-based systems should significantly decrease the time needed for testing and simulation. A proven record of delivering reliable systems at the beginning of the highly visible testing and simulation phases is crucial to the acceptance of knowledge-based systems in critical applications.

Johnson, Sally C.↗
DOE OSTI2020

Verifiable Security Templates for Hardware

High-level synthesis (HLS) research generally focuses on transferring "software engineering virtues" (e.g., modularity, abstraction, extensibility, etc.) to hardware development with the ultimate goal of making hardware development as agile as software development. And recent HLS research has focused on transferring ideas and techniques from high assurance software formal methods to hardware development. Just as it has introduced software engineering virtues, we believe HLS can also become a vector for adapting software formal methods to the challenge of high assurance security in hardware. This paper introduces the Device Calculus and its mechanization in the Agda proof checking system. The Device Calculus is a starting point for exploring the formal methods and security of high-level synthesis flows. We illustrate the Device Calculus with a number of examples of formally verifiable security templates-i.e., functions in the Device Calculus that express common security structures at a high-level of abstraction.

Harrison, Bill↗
DOE OSTI2020

Teaching Software Sustainability for High Performance Computing at ATPESC

The Argonne Training Program in Extreme Scale Computing (ATPESC) was started by Argonne National Laboratory with the objective of expanding the ranks of better-prepared users of high-performance computing (HPC) machines. One of the unique aspects of the program was inclusion of a track on software engineering and community codes. The inclusion was motivated by the observation that the projects with good software processes were better able to meet their scientific goals. Over the years, with greater awareness of software sustainability issues in the community, the track has evolved into a software productivity and sustainability track. In this paper we present our experience in choosing and disseminating the content related to the topic of software engineering in high performance computing science from the beginning of the program until now. We discuss the motivations and the reception of the tracks. We also document the evolution of the track over the years based on student feedback and also the growth of awareness about software productivity in high performance computing.

Dubey, Anshu↗
NASA NTRS1998

Spacecraft Autonomy and the Missions of Exploration

Practitioners of artificial intelligence are being engaged to help develop the next generation of flight software for NASA missions, in partnership with other computer scientists, mission designers, operations personnel, spacecraft engineers, systems engineers, software engineers, and scientists.

artificial intelligence spacecraft autonomy ground↗