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A new simulation architecture for improving software reliability in Collider-Accelerator control systems
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Virtual Reliability Software for Real Time Detection of Failures at PV Plants
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A NASA initiative: Software engineering for reliable complex systems
The objective is the development of methods, technology, and skills that will enable NASA to cost-effectively specify, build, and manage reliable software which can evolve and be maintained over an extended period. The need for such software is rooted in the increasing integration of software and computing components into NASA systems. Current NASA Software Engineering expertise was applied toward some of the largest reliable systems including: shuttle launch; ground support; shuttle simulation; minor control; satellite tracking; and scientific data systems. Unfortunately, no theory exists for reliable complex software systems. NASA is seeking to fill this theoretical gap through a number of approaches. One such approach is to conduct research on theoretical foundations for managing complex software systems. It includes: communication models, new and modified paradigms, and life-cycle models. Another approach is research in the theoretical foundations for reliable software development and validation. It focuses upon formal specifications, programming languages, software engineering systems, software reuse, formal verification, and software safety. Further approaches involve benchmarking a NASA software environment, experimentation within the NASA context, evolution of present NASA methodology, and transfer of technology to the space station software support environment.
Software For Computing Reliability Of Other Software
Computer Aided Software Reliability Estimation (CASRE) computer program developed for use in measuring reliability of other software. Easier for non-specialists in reliability to use than many other currently available programs developed for same purpose. CASRE incorporates mathematical modeling capabilities of public-domain Statistical Modeling and Estimation of Reliability Functions for Software (SMERFS) computer program and runs in Windows software environment. Provides menu-driven command interface; enabling and disabling of menu options guides user through (1) selection of set of failure data, (2) execution of mathematical model, and (3) analysis of results from model. Written in C language.
Bayesian And Human Reliability Analysis (hra)-aided Method For The Reliability Analysis Of Software (bahamas)
The purpose of the BAHAMAS code is to provide a simplified process for performing quantitative evaluations of software reliability. The Bayesian and Human Reliability Analysis (HRA)-Aided method for the Reliability Analysis of software (BAHAMAS) was developed specifically to perform quantification under limited data conditions, i.e., when limited testing or operational data are available, such as during early development stages. BAHAMAS essentially examines the quality of a software development life cycle to determine the probability of specific types of software failure. BAHAMAS will have modules to support user input for detailed and simplified analyses. The user interface will also support software common cause failure analysis.
Reliability measurement during software development
Measurement of software reliability was carried out during the development of data base software for a multi-sensor tracking system. Every run made during this project was scored as success or failure, and supporting data were collected on forms for further analysis. The failure ratio (number of failures per calendar interval divided by total number of runs) and failure rate (number of failures divided by CPU time for the interval) were found to be consistent measures, on a month-to-month basis as well as from module to module, and therefore considered valid indicators of reliability in this environment. Trend lines could be established from these measurements that provide good visualization of the progress on the job as a whole as well as on individual modules. Over one-half of the observed failures were due to factors associated with the specific run submission rather than with the code proper.
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)
Developing Confidence Limits For Reliability Of Software
Technique developed for estimating reliability of software by use of Moranda geometric de-eutrophication model. Pivotal method enables straightforward construction of exact bounds with associated degree of statistical confidence about reliability of software. Confidence limits thus derived provide precise means of assessing quality of software. Limits take into account number of bugs found while testing and effects of sampling variation associated with random order of discovering bugs.
Evaluation of Open-Source Hard Real Time Software Packages
Reliable software is, at times, hard to find. No piece of software can be guaranteed to work in every situation that may arise during its use here at Glenn Research Center or in space. The job of the Software Assurance (SA) group in the Risk Management Office is to rigorously test the software in an effort to ensure it matches the contract specifications. In some cases the SA team also researches new alternatives for selected software packages. This testing and research is an integral part of the department of Safety and Mission Assurance. Real Time operation in reference to a computer system is a particular style of handing the timing and manner with which inputs and outputs are handled. A real time system executes these commands and appropriate processing within a defined timing constraint. Within this definition there are two other classifications of real time systems: hard and soft. A soft real time system is one in which if the particular timing constraints are not rigidly met there will be no critical results. On the other hand, a hard real time system is one in which if the timing constraints are not met the results could be catastrophic. An example of a soft real time system is a DVD decoder. If the particular piece of data from the input is not decoded and displayed to the screen at exactly the correct moment nothing critical will become of it, the user may not even notice it. However, a hard real time system is needed to control the timing of fuel injections or steering on the Space Shuttle; a delay of even a fraction of a second could be catastrophic in such a complex system. The current real time system employed by most NASA projects is Wind River's VxWorks operating system. This is a proprietary operating system that can be configured to work with many of NASA s needs and it provides very accurate and reliable hard real time performance. The down side is that since it is a proprietary operating system it is also costly to implement. The prospect of replacing this somewhat costly implementation is the focus of one of the SA group s current research projects. The explosion of open source software in the last ten years has led to the development of a multitude of software solutions which were once only produced by major corporations. The benefits of these open projects include faster release and bug patching cycles as well as inexpensive if not free software solutions. The main packages for hard real time solutions under Linux are Real Time Application Interface (RTAI) and two varieties of Real Time Linux (RTL), RTLFree and RTLPro. During my time here at NASA I have been testing various hard real time solutions operating as layers on the Linux Operating System. All testing is being run on an Intel SBC 2590 which is a common embedded hardware platform. The test plan was provided to me by the Software Assurance group at the start of my internship and my job has been to test the systems by developing and executing the test cases on the hardware. These tests are constructed so that the Software Assurance group can get hard test data for a comparison between the open source and proprietary implementations of hard real time solutions.
Pivotal-Function Assessment Of Reliability Of Software
Approach developed to establish utility of pivotal functions for estimation and prediction of reliability of software. Improved estimates of reliability with statistical confidence obtained when relatively few testing data available. Pivotal functions effective tools for determination of confidence limits for reliability of software and prediction limits for time to next failure. Provides exact confidence and prediction limits regardless of how many bugs found in software.
Evaluation methodologies for an advanced information processing system
The system concept and requirements for an Advanced Information Processing System (AIPS) are briefly described, but the emphasis of this paper is on the evaluation methodologies being developed and utilized in the AIPS program. The evaluation tasks include hardware reliability, maintainability and availability, software reliability, performance, and performability. Hardware RMA and software reliability are addressed with Markov modeling techniques. The performance analysis for AIPS is based on queueing theory. Performability is a measure of merit which combines system reliability and performance measures. The probability laws of the performance measures are obtained from the Markov reliability models. Scalar functions of this law such as the mean and variance provide measures of merit in the AIPS performability evaluations.
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.
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.
Applying reliability models to the maintenance of Space Shuttle software
Software reliability models provide the software manager with a powerful tool for predicting, controlling, and assessing the reliability of software during maintenance. We show how a reliability model can be effectively employed for reliability prediction and the development of maintenance strategies using the Space Shuttle Primary Avionics Software Subsystem as an example.
Quantifying parameters for Bayesian prior assumptions when estimating the probability of failure of software
Software reliability has become increasingly important, especially in life-critical situations. The ability to measure the results of testing and to quantify software reliability is needed. If this is accomplished, a certain minimum amount of reliability for a piece of software can be specified, and testing and/or other analysis may be done until that minimum number has been attained. There are many models for estimating software reliability. The accuracy of these models has been challenged and many revisions for the models and recalibration techniques have been devised. Of particular interest is the method of estimating the probability of failure of software when no failures have yet occurred in its current version as described by Miller. This model uses black box testing with formulae based on Bayesian estimation. The focus is on three interrelated issues: estimating the probability of failure when testing has revealed no errors; modifying this estimation when the input use distribution does not match the test distribution; and combining the results from random testing with other relevant information to obtain a possibly more accurate estimate of the probability of failure. Obtaining relevant information about the software and combining the results for a better estimate for the Miller model are discussed.
An overview of the mathematical and statistical analysis component of RICIS
Mathematical and statistical analysis components of RICIS (Research Institute for Computing and Information Systems) can be used in the following problem areas: (1) quantification and measurement of software reliability; (2) assessment of changes in software reliability over time (reliability growth); (3) analysis of software-failure data; and (4) decision logic for whether to continue or stop testing software. Other areas of interest to NASA/JSC where mathematical and statistical analysis can be successfully employed include: math modeling of physical systems, simulation, statistical data reduction, evaluation methods, optimization, algorithm development, and mathematical methods in signal processing.
Integrating Formal Methods and Testing 2002
Traditionally, qualitative program verification methodologies and program testing are studied in separate research communities. None of them alone is powerful and practical enough to provide sufficient confidence in ultra-high reliability assessment when used exclusively. Significant advances can be made by accounting not only tho formal verification and program testing. but also the impact of many other standard V&V techniques, in a unified software reliability assessment framework. The first year of this research resulted in the statistical framework that, given the assumptions on the success of the qualitative V&V and QA procedures, significantly reduces the amount of testing needed to confidently assess reliability at so-called high and ultra-high levels (10-4 or higher). The coming years shall address the methodologies to realistically estimate the impacts of various V&V techniques to system reliability and include the impact of operational risk to reliability assessment. Combine formal correctness verification, process and product metrics, and other standard qualitative software assurance methods with statistical testing with the aim of gaining higher confidence in software reliability assessment for high-assurance applications. B) Quantify the impact of these methods on software reliability. C) Demonstrate that accounting for the effectiveness of these methods reduces the number of tests needed to attain certain confidence level. D) Quantify and justify the reliability estimate for systems developed using various methods.