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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Graphical workstation capability for reliability modeling

In addition to computational capabilities, software tools for estimating the reliability of fault-tolerant digital computer systems must also provide a means of interfacing with the user. Described here is the new graphical interface capability of the hybrid automated reliability predictor (HARP), a software package that implements advanced reliability modeling techniques. The graphics oriented (GO) module provides the user with a graphical language for modeling system failure modes through the selection of various fault-tree gates, including sequence-dependency gates, or by a Markov chain. By using this graphical input language, a fault tree becomes a convenient notation for describing a system. In accounting for any sequence dependencies, HARP converts the fault-tree notation to a complex stochastic process that is reduced to a Markov chain, which it can then solve for system reliability. The graphics capability is available for use on an IBM-compatible PC, a Sun, and a VAX workstation. The GO module is written in the C programming language and uses the graphical kernal system (GKS) standard for graphics implementation. The PC, VAX, and Sun versions of the HARP GO module are currently in beta-testing stages.

Bavuso, Salvatore J.↗
NASA NTRS1987

Effectiveness of back-to-back testing

Three models of back-to-back testing processes are described. Two models treat the case where there is no intercomponent failure dependence. The third model describes the more realistic case where there is correlation among the failure probabilities of the functionally equivalent components. The theory indicates that back-to-back testing can, under the right conditions, provide a considerable gain in software reliability. The models are used to analyze the data obtained in a fault-tolerant software experiment. It is shown that the expected gain is indeed achieved, and exceeded, provided the intercomponent failure dependence is sufficiently small. However, even with the relatively high correlation the use of several functionally equivalent components coupled with back-to-back testing may provide a considerable reliability gain. Implications of this finding are that the multiversion software development is a feasible and cost effective approach to providing highly reliable software components intended for fault-tolerant software systems, on condition that special attention is directed at early detection and elimination of correlated faults.

Vouk, Mladen A.↗
NASA NTRS1989

Predicting software reliability

A detailed look is given to software reliability techniques. A conceptual model of the failure process is examined, and some software reliability growth models are discussed. Problems for which no current solutions exist are addressed, emphasizing the very difficult problem of safety-critical systems for which the reliability requirements can be enormously demanding.

Littlewood, B.↗
DOE OSTI2016

Finite-Test-Case Development to Demonstrate Logical Integrity of Software in DRPS

Reactor protection system (RPS) in nuclear power plant (NPP) is in the process of digitalization in response to advanced features of digital systems. In this context, software integrity in the RPS becomes an important issue since it may cause common-cause failure. Therefore, to guarantee the safety of NPPs, the integrity of the software need to be properly demonstrated or assessed. There are three typical approaches for software reliability quantification: software reliability growth model (SRGM), Bayesian belief network (BBN), and test-based method. Basically, SRGM is difficult to apply to the safety-critical software because not only sufficient failure sets are unavailable but consequence of system failure is also unacceptable. Then the result obtained through the BBN model may have large uncertainty, so it produces difficulties in integrity demonstration of safety-critical software. Thus, the BBN result need to be complemented or verified by test-based method. Currently, for the integrity demonstration of safety-critical software, black-box test which feeds inputs and examines just outputs whether they succeeded or failed is considered based on trajectory-form-of-input (a series of successive values for the input variables that occur during the operation of the software over time). Usually these trajectory-inputs are randomly sampled from operational profile. In this approach, however, there are some practical difficulties. Therefore, we proposed a new test method for safety-critical software in digitalized reactor protection system (DRPS). The main contents described in this paper are about basic concepts under development of finite-test-cases by which the integrity of the software logic can be verified. It should be noted that the influence of the environments, such as operating system and other hardware, are not considered since the method focuses on software logic only. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1993

The infeasibility of quantifying the reliability of life-critical real-time software

This paper affirms that the quantification of life-critical software reliability is infeasible using statistical methods, whether these methods are applied to standard software or fault-tolerant software. The classical methods of estimating reliability are shown to lead to exorbitant amounts of testing when applied to life-critical software. Reliability growth models are examined and also shown to be incapable of overcoming the need for excessive amounts of testing. The key assumption of software fault tolerance - separately programmed versions fail independently - is shown to be problematic. This assumption cannot be justified by experimentation in the ultrareliability region, and subjective arguments in its favor are not sufficiently strong to justify it as an axiom. Also, the implications of the recent multiversion software experiments support this affirmation.

Butler, Ricky W.↗
NASA NTRS1991

The Infeasibility of Quantifying the Reliability of Life-Critical Real-Time Software

This paper affirms that the quantification of life-critical software reliability is infeasible using statistical methods whether applied to standard software or fault-tolerant software. The classical methods of estimating reliability are shown to lead to exhorbitant amounts of testing when applied to life-critical software. Reliability growth models are examined and also shown to be incapable of overcoming the need for excessive amounts of testing. The key assumption of software fault tolerance separately programmed versions fail independently is shown to be problematic. This assumption cannot be justified by experimentation in the ultrareliability region and subjective arguments in its favor are not sufficiently strong to justify it as an axiom. Also, the implications of the recent multiversion software experiments support this affirmation.

Butler, Ricky W.↗
DOE OSTI2020

Safety Risk Reliability Model Library

SR2ML is a software package which contains a set of safety and reliability models designed to be interfaced with the INL developed RAVEN code. These models can be employed to perform both static and dynamic system risk analysis and determine risk importance of specific elements of the considered system. Two classes of reliability models have been developed; the first class includes all classical reliability models (Fault-Trees, Event-Trees, Markov models and Reliability Block Diagrams) which have been extended to deal not only with Boolean logic values but also time dependent values. The second class includes several components aging models. Models of these two classes are designed to be included in a RAVEN ensemble model to perform time dependent system reliability analysis (dynamic analysis). Similarly, these models can be interfaced with system analysis codes to determine failure time of systems and evaluate accident progression (static analysis).

Wang, Congjian↗
NASA NTRS1987

Space station software reliability analysis based on failures observed during testing at the multisystem integration facility

Quality of software not only is vital to the successful operation of the space station, it is also an important factor in establishing testing requirements, time needed for software verification and integration as well as launching schedules for the space station. Defense of management decisions can be greatly strengthened by combining engineering judgments with statistical analysis. Unlike hardware, software has the characteristics of no wearout and costly redundancies, thus making traditional statistical analysis not suitable in evaluating reliability of software. A statistical model was developed to provide a representation of the number as well as types of failures occur during software testing and verification. From this model, quantitative measure of software reliability based on failure history during testing are derived. Criteria to terminate testing based on reliability objectives and methods to estimate the expected number of fixings required are also presented.

Tamayo, Tak Chai↗
NASA NTRS2003

How simple is software defect detection?

This study benchmarks several FSS techniques and reports several studies where a large set metrics were reduced to a handful with little loss of detection accuracy. This result raises the possibility that software defect detection may be much simpler than previously believed.

feature subset selection software fault model soft↗
NASA NTRS1989

Error-Free Software

001 is an integrated tool suited for automatically developing ultra reliable models, simulations and software systems. Developed and marketed by Hamilton Technologies, Inc. (HTI), it has been applied in engineering, manufacturing, banking and software tools development. The software provides the ability to simplify the complex. A system developed with 001 can be a prototype or fully developed with production quality code. It is free of interface errors, consistent, logically complete and has no data or control flow errors. Systems can be designed, developed and maintained with maximum productivity. Margaret Hamilton, President of Hamilton Technologies, also directed the research and development of USE.IT, an earlier product which was the first computer aided software engineering product in the industry to concentrate on automatically supporting the development of an ultrareliable system throughout its life cycle. Both products originated in NASA technology developed under a Johnson Space Center contract.

Source record↗
NASA NTRS1992

Software reliability through fault-avoidance and fault-tolerance

Accomplishments in the following research areas are summarized: structure based testing, reliability growth, and design testability with risk evaluation; reliability growth models and software risk management; and evaluation of consensus voting, consensus recovery block, and acceptance voting. Four papers generated during the reporting period are included as appendices.

Vouk, Mladen A.↗
NASA NTRS1987

Computer Reliability

Using a NASA developed program, Dr. J. Walter Bond is creating a course in computer reliability modeling. The course will examine three different computer programs, one of them NASA's Care III, the others UCLA's Aries 78 and Aries 82. All three are designed to help estimate the reliability of complex, redundant, fault tolerant system. In computer design, software of this kind can predict or model the effects of various hardware or software failures, a process called reliability modeling.

Source record↗
NASA NTRS1998

Towards a Theory for Integration of Mathematical Verification and Empirical Testing

From the viewpoint of a project manager responsible for the V&V (verification and validation) of a software system, mathematical verification techniques provide a possibly useful orthogonal dimension to otherwise standard empirical testing. However, the value they add to an empirical testing regime both in terms of coverage and in fault detection has been difficult to quantify. Furthermore, potential cost savings from replacing testing with mathematical verification techniques cannot be realized until the tradeoffs and synergies can be formulated. Integration of formal verification with empirical testing is also difficult because the idealized view of mathematical verification providing a correctness proof with total coverage is unrealistic and does not reflect the limitations imposed by computational complexity of mathematical techniques. This paper first describes a framework based on software reliability and formalized fault models for a theory of software design fault detection - and hence the utility of various tools for debugging. It then describes a utility model for integrating mathematical and empirical techniques with respect to fault detection and coverage analysis. It then considers the optimal combination of black-box testing, white-box (structural) testing, and formal methods in V&V of a software system. Using case studies from NASA software systems, it then demonstrates how this utility model can be used in practice.

Lowry, Michael↗
DOE OSTI2022

Application of Orthogonal Defect Classification for Software Reliability Analysis

The modernization of existing and new nuclear power plants with digital instrumentation and control systems (DI&C) is a recent and highly trending topic. However, there lacks strong consensus on best-estimate reliability methodologies by both the United States (U.S.) Nuclear Regulatory Commission (NRC) and the industry. This has resulted in hesitation for further modernization projects until a more unified methodology is realized. In this work, we develop an approach called Orthogonal-defect Classification for Assessing Software Reliability (ORCAS) to quantify probabilities of various software failure modes in a DI&C system. The method utilizes accepted industry methodologies for software quality assurance that are also verified by experimental or mathematical formulations. In essence, the approach combines a semantic failure classification model with a reliability growth model to predict (and quantify) the potential failure modes of a DI&C software system. The semantic classification model is used to address the question: How do latent defects in software contribute to different software failure root causes? The use of reliability growth models is then used to address the question: Given the connection between latent defects and software failure root causes, how can we quantify the reliability of the software? A case study was conducted on a representative I&C platform (ChibiOS) running a smart sensor acquisition software developed by Virginia Commonwealth University (VCU). The testing and evidence collection guidance in ORCAS was applied, and defects were uncovered in the software. Qualitative evidence, such as condition coverage, was used to gauge the completeness and trustworthiness of the assessment while quantitative evidence was used to determine the software failure probabilities. The reliability of the software was then estimated and compared to existing operational data of the sensor device. It is demonstrated that by using ORCAS, a semantic reasoning framework can be developed to justify if the software is reliable (or unreliable) while still leveraging the strength of the existing methods.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗