Detection of faults and software reliability analysis annual progress report, award no. NAG-1-605 by J. C. Knight

Cover of: Detection of faults and software reliability analysis | J. C. Knight

Published by School of Engineering and Applied Science, Dept. of Computer Science, University of Virginia, National Aeronautics and Space Administration, Langley Research Center, National Technical Information Service, distributor in Charlottesville, Va, Hampton, Va, [Springfield, Va .

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Statementsubmitted to National Aeronautics and Space Administration, Langley Research Center ; submitted by J.C. Knight
SeriesNASA contractor report -- NASA CR-179835
ContributionsLangley Research Center
The Physical Object
Pagination1 v
ID Numbers
Open LibraryOL14985783M

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A knowledge based approach to systems safety and reliability analysis to be implemented in an intelligent software tool (STARS: Software Tool for Advanced Reliability and Safety) is presented. The approach evolved from previous experience in the development and use of the CAFTS and RIKKE codes for automatic fault tree construction.

Software Reliability reviews some fundamental issues of software reliability as well as the techniques, models, and metrics used to predict the reliability of software. Topics covered include fault avoidance, fault removal, and fault tolerance, Detection of faults and software reliability analysis book with statistical methods for the objective assessment of.

Get this from a library. Detection of faults and software reliability analysis. [John C Knight; United States. National Aeronautics and Space Administration.]. Software reliability growth models (SRGMs) have been developed to estimate software reliability measures such as the number of remaining faults, software failure rate, and software reliability.

Get this from a library. Detection of faults and software reliability analysis: annual progress report, award no. NAG [John C Knight; Langley Research Center.]. The common assumption for most existingsoftware reliability growth models is that fault is independent and can be removed perfectly upon detection.

However, it is often not true due to various factors including software complexity, programmer proficiency, organization hierarchy, etc. In this paper, we develop a software reliability model with considerations of fault-dependent detection Cited by: Lo and Huang [26] provided integrated fault detection and correction processes in software reliability analysis.

Recently, the fault correction process of software reliability growth model was. Software Reliability reviews some fundamental issues of software reliability as well as the techniques, models, and metrics used to predict the reliability of software.

Topics covered include fault avoidance, fault removal, and fault tolerance, along with statistical methods for the objective assessment of predictive Edition: 1. Purchase Fault Detection & Reliability - 1st Edition.

Print Book & E-Book. ISBNBook Edition: 1. One of the software engineering interests is quality assurance activities such as testing, verification and validation, fault tolerance and fault prediction.

When any company does not have sufficient budget and time for testing the entire application, a project manager can use some fault prediction algorithms to identify the parts of the system that are more defect by: – For systems that require high reliability, this may still be a necessity.

– For most other systems, eventually you give up looking for faults and ship it. • We will now consider several methods for dealing with software faults: – Fault avoidance – Fault detection – Fault tolerance, recovery and repair.

Software Reliability - features• failures in software are design faults,• reliability during test changes continually (new problems are found as old ones are fixed / new code is never perfect)• phenomenon of software reliability growth• environment is important (platform/inputs) - new envt.

may require s/w retest 3. Software Faults and Fault Injection Models. Abstract: Software Faults can be created at any time in any phase of the software development. This paper will explore software faults in the perspective of software reliability.

Complex software faults occurring in various systems have been studied and are classified, basing on the behavior of the fault. / Home / Software / Fault Analyses Fault Analyses Fault analysis is an essential tool for the determination of short-circuit currents that result from different fault phenomena, the estimation of fault locations, the identification of under-rated equipment in electric power systems and.

A Brief description of Software reliability. Software reliability 1. LT CDR PABITRA KUMAR PANDA M TECH (RE), IIT KGP 11 AUG SOFTWARE RELIABILITY. The reliability detection method for the traditional large-scale automation software is based on the module design principle of the automation software which detects the reliability features one by one.

It does not consider the concurrent reliable chain problems for the automation software which cause the low detection accuracy. The paper proposes a novel automation software system reliability Author: Wen Lai Liu. Reliability analysis includes reliability calculations performed at the stages of preliminary design and detailed design, failure data analysis based on the results of special and operational tests as well as data received from a customer/user.

analyzed static analysis faults and test and customer-reported failures for three large-scale industrial software systems developed at Nortel Networks.

The data indicate that automated static analysis is an affordable means of software fault detection. Using the Orthogonal Defect Classification scheme, we found that automated static analysis is File Size: 1MB.

During the software-testing phase, software reliability is highly related to the amount of development resources spent on detecting and correcting latent software errors, i.e.

the amount of testing effort expenditures. Some researches proposed in the literature to study in the fault detection and fault correction processes.

Software fault (and failures they cause) are independent. Inputs for software selected randonly from an input space. Test space is representative of the operational input space.

Each software failure is observed. Faults are corrected without introducing new ones. File Size: KB. Mapping of IEEE to available software reliability tools Section Contents Tools Available 1,2,3, 4 Overview, definitions and acronyms, Tailoring guidance Planning for software reliability Develop a failure modes model –SFMEA, Software Fault Tree Analysis Frestimate System Software Analysis Module, Software FMEA ToolkitFile Size: 4MB.

The paper focuses on diversity, as a desirable approach for addressing the classes of faults that underlay all these topics, i.e., design faults and intrusion faults. Introduction The paper is aimed at examining the relationship between the three topics of the workshops that gave rise to this book: security, fault tolerance and software.

Software reliability model can measure and predict the number of software failures, software failure intervals, software reliability, and failure rates.

In this paper, we propose a new model with an inflection factor of the fault detection rate function, considering the uncertainty of operating environments and analyzing how the predicted value Cited by: 1.

Software faults: spreading, detection and costs by Claes Wohlin and Ulf Korner The paper considers, through modelling, how software faults are spread throughout the entire life-cycle of a large software product and how fault detection and correction processes will affect the spreading mechanism.

The study is further enlarged to. software trace analysis for failure detection. A set of discriminative features capturing repetitive series of events from program execution traces are first executed. Subsequently feature selection is done to select the best features for classification.

The classifier model is trained with. Fault-Diagnosis Systems: An Introduction from Fault Detection to Fault Tolerance - Kindle edition by Isermann, Rolf. Download it once and read it on your Kindle device, PC, phones or tablets.

Use features like bookmarks, note taking and highlighting while reading Fault-Diagnosis Systems: An Introduction from Fault Detection to Fault Tolerance.3/5(1). Fault detection, isolation, and recovery (FDIR) is a subfield of control engineering which concerns itself with monitoring a system, identifying when a fault has occurred, and pinpointing the type of fault and its location.

Two approaches can be distinguished: A direct pattern recognition of sensor readings that indicate a fault and an analysis of the discrepancy between the sensor readings.

Insights from the software architecture Expert insights/ engineering judgment Knowledge of module quality from quality classification Other insights i.e.

Were formal methods used?, etc. Ł Possible outputs A probability that the software reliability lies in a certain range Confidence value that the software reliability has an acceptable value. A Review of Fault Detection Techniques to Detect Faults and Improve the Reliability in Web Applications Jyoti Tamak Department of Computer Science and Engineering University Institute of Engineering & Technology Kurukshetra University,Kurukshetra, Haryana, India Abstract--Software reliability is a big anxiety in industry.

In this book, bestselling author Martin Shooman draws on his expertise in reliability engineering and software engineering to provide a complete and authoritative look at fault tolerant computing.

He clearly explains all fundamentals, including how to use redundant elements in system design to ensure the reliability of computer systems and Cited by: Analysis of power system faults and relay protection measures (photo credit: ZGL) Fault detection is required to activate the measurement process of protective relays.

In relation to specification of time intervals of the signals, fault detection can be treated as distinguishing the. Software reliability is a key part in software quality. The study of software reliability can be categorized into three parts: modeling, measurement and improvement.

Software reliability modeling has matured to the point that meaningful results can be obtained by applying suitable models to the problem. JOHN D. MUSA Software Reliability Engineering and Testing Courses More Reliable Software Faster and Cheaper 8 Copyright John D.

Musa SREH9H 15 Define the File Size: KB. Fault Handling Techniques. This article describes some of the techniques that are used in fault handling software design.

A typical fault handling state transition diagram is described in detail. The article also covers several fault detection and isolation techniques. Fault Handling Lifecycle. By analyzing the structure features and tool changing process of a large-scale national Automatic Tool Changer (ATC) with a chain-type tool magazine, a chain-type tool magazine reliability test bench is designed with a new fault detection system, where a new failure data collecting method is applied for taking failure data statistics and reliability : Ye Hu, Zhao Jun Yang, Xiao Ming Zeng, Peng Fei Song, Yu Peng Ma, Yang Wang, Qiao Lou.

of faults. Typical software systems are generally so complex that it is virtually impossible to achieve fault free software products. On the other hand, hardware faults typically stem not from poor design but from physical wear and operating conditions.

Hence fault avoidance. reliability theory including the accelerated life testing. The failure models are discussed at length and are supported by various graphs to provide easy understanding of the concept.

In CHAPTER-2 entitled " SOFTWARE RELIABILITY", the basic concepts in software reliability, the software development process and various models has been discussed. Development process, faults and failures found are all factors related to software reliability.

Improvement: Software reliability improvement is hard. The difficulty of the problem stems from insufficient understanding of software reliability and in general, the characteristics of software.

• Hazard & Operability Analysis (HAZOP) • Human Reliability • Preliminary Hazard Analysis (PHA) • Relative Ranking • Safety Review • What-If / Checklist Analysis • What-If Analysis For the purpose of this class, two common but fundamentally different techniques will be presented in detail: 1.

Failure Modes Effects Analysis (FMEA) Size: KB. Introduction. This 5-day BOOST training course is concerned with the calculation of fault currents in practical electrical power systems. Short-circuit currents are associated with large amounts of very destructive energy and therefore calculations must be made to ensure that the short-circuit ratings of equipment are adequate to cater for these high currents.

Experience report: anomaly detection of cloud application operations using log and cloud metric correlation analysis. In M. Vieira, & K. Wolter (Eds.), Proceedings of the IEEE 26th International Symposium on Software Reliability Engineering (ISSRE) (pp.

). [] IEEE, Institute of Electrical and Electronics by: The failure-detection and fault-correction are critical processes in attaining good performance of software quality.

In this paper, we propose several improvements on the conventional software reliability growth models (SRGMs) to describe actual software development process by eliminating some unrealistic assumptions. Most of these models have focused on the failure detection process and not.The history of software reliability theory began more than 60 years ago.

The first paper, in which the words “Software” and “Reliability” are used together in a single word-combination, is likely the one written in [1]. Although the idea that the reliability growth is possible in complex systems was given much earlier – in [2].Cited by: 2.

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