Reliability Assessment of Multi-release Software System Under Imperfect Fault Removal Phenomenon

2020 ◽  
pp. 367-380
Author(s):  
Vibha Verma ◽  
Sameer Anand ◽  
Anu Gupta Aggarwal
Keyword(s):  
Reliability Assessment ◽  
Software System ◽  
Fault Removal

Statistical Dependence of Input Variables in Doproc Method / Statistická Závislost Vstupních Veličin V Metodě Popv

2012 ◽  
Vol 12 (2) ◽  
pp. 48-58 ◽  
Author(s):  
Petr Janas ◽  
Krejsa Martin
Keyword(s):  
Reliability Assessment ◽  
Random Variables ◽  
Statistical Dependence ◽  
Software System ◽  
Dependent Variables ◽  
Computational Procedures ◽  
Input Variables

Abstract In probabilistic tasks, input random variables are often statistically dependent. This fact should be considered in correct computational procedures. In case of the newly developed Direct Optimized Probabilistic Calculation (DOProC), the statistically dependent variables can be expressed by the socalled multidimensional histograms, which can be used e.g. for probabilistic calculations and reliability assessment in the software system ProbCalc.

A SOFTWARE RELIABILITY GROWTH MODEL WITH TESTING EFFORT DEPENDENT LEARNING FUNCTION FOR DISTRIBUTED SYSTEMS

2004 ◽  
Vol 11 (04) ◽  
pp. 365-377 ◽  
Author(s):  
P. K. KAPUR ◽  
D. N. GOSWAMI ◽  
AMIT GUPTA
Keyword(s):  
Software Reliability ◽  
Goodness Of Fit ◽  
Software Process Improvement ◽  
Software System ◽  
Reliability Growth ◽  
Development Environment ◽  
Testing Effort ◽  
Growth Phenomenon ◽  
Software Reliability Growth ◽  
Fault Removal

Effective software process improvement will not start until management insists that product development work be planned and properly managed. This becomes even more challenging in an increasing number of major system developments made up from distributed sub-system software projects. These sub-systems are integrated and validated to provide the final system and product release. The need is growing to estimate, risk assess, plan and manage the development of these distributed sub-systems and the final full system release. In this paper, an attempt has been made to model the software reliability growth phenomenon with testing effort in a distributed development environment. Proposed Non Homogeneous Poisson Process (NHPP) based model assumes that the software system consists of a finite number of reused and newly developed sub-systems. The reused sub-systems do not consider the effect of severity of the faults on the software reliability growth phenomenon because they stabilize over a period of time i.e., the growth is uniform whereas, the newly developed sub-system do consider that. Fault removal phenomenon for reused and newly developed sub-systems have been modeled separately and is summed up to get the total fault removal phenomenon of the software system. The applicability of our model is shown by validating it on software failure data sets obtained from different real software development projects. The comparisons with established models in terms of goodness of fit, the Akaike Information Criterion (AIC), Mean of Squared Errors (MSE) have been presented.

Reliability Assessment of Software System Using IFS and OWA-Tree Analysis

2020 ◽  
Vol 27 (05) ◽  
pp. 2040013
Author(s):  
Abhishek Tandon ◽  
Neha ◽  
Anu G. Aggarwal ◽  
Ajay Jaiswal
Keyword(s):  
Failure Rate ◽  
Failure Probability ◽  
Intuitionistic Fuzzy Set ◽  
Reliability Assessment ◽  
Weighted Averaging ◽  
Software System ◽  
Tree Analysis ◽  
Software Product ◽  
To Come ◽  
Theory Failure

To address the software design and development, reliability assessment is considered as crucial and most important task. Several studies have been directed towards reliability assessment approaches for obtaining highly reliable software product. In conventional reliability theory, failure probability of any component is assumed as an exact value but in actuality it’s not possible to get failure probability precisely. In this study, we have proposed an approach to assess the reliability of a software system with vague failure rate of the components as the given information might be incomplete or uncertain. It is a bottom–top methodology which includes the combination of intuitionistic fuzzy set (IFS) theory and ordered weighted averaging (OWA) tree analysis. Using IFS, we are able to come over the vagueness in the failure rate data and by using OWA-tree, we incorporate the subjectivity in the opinion of software developers with respect to selection of module. Further, for the illustration of the proposed approach one numerical example has been discussed and software reliability is assessed based upon different orness level.

SOFTWARE RELIABILITY ASSESSMENT USING ARTIFICIAL NEURAL NETWORK BASED FLEXIBLE MODEL INCORPORATING FAULTS OF DIFFERENT COMPLEXITY

2008 ◽  
Vol 15 (02) ◽  
pp. 113-127 ◽  
Author(s):  
P. K. KAPUR ◽  
SUNIL K. KHATRI ◽  
MASHAALLAH BASIRZADEH
Keyword(s):  
Neural Network ◽  
Software Reliability ◽  
Growth Models ◽  
Reliability Assessment ◽  
Reliability Growth ◽  
Removal Process ◽  
Proposed Model ◽  
Software Reliability Growth ◽  
Fault Removal ◽  
Artificial Neural

With growth in demand for zero defects, predicting reliability of software products is gaining importance. Software Reliability Growth Models (SRGM) are used to estimate the reliability of a software product. We have a large number of SRGM; however none of them works across different environments. Recently, Artificial Neural Networks have been applied in software reliability assessment and software reliability growth prediction. In most of the existing research available in the literature, it is considered that similar testing effort is required on each debugging effort. However, in practice, different amount of testing efforts may be required for detection and removal of different type of faults on basis of their complexity. Consequently, faults are classified into three categories on basis of complexity: simple, hard and complex. In this paper we apply neural network methods to build software reliability growth models (SRGM) considering faults of different complexity. Logistic learning function accounting for the expertise gained by the testing team is used for modeling the proposed model. The proposed model assumes that in the simple faults the growth in removal process is uniform whereas, for hard and complex faults, removal process follows logistic growth curve due to the fact that learning of removal team grows as testing progresses. The proposed model has been validated, evaluated and compared with other NHPP model by applying it on two failure/fault removal data sets cited from real software development projects. The results show that the proposed model with logistic function provides improved goodness-of-fit for software failure/fault removal data.

scholarly journals RESEARCH OF ACCURACY OF SOFTWARE SOFTWARE RELIABILITY ASSESSMENT

2020 ◽  
Vol 33 (108) ◽  
pp. 17-25
Author(s):  
D. A. Maevsky ◽  
◽  
O. V. Naidenko ◽  
E. J. Maevskaya ◽  
O. V. Strelzov ◽  
...  
Keyword(s):  
Time Series ◽  
Programming Language ◽  
Defect Detection ◽  
Software Reliability ◽  
Geometric Model ◽  
Reliability Assessment ◽  
Internet Resource ◽  
Software System ◽  
Reliability Model ◽  
Simulation Accuracy

The aim of the work is to establish the presence or absence of dependence of the accuracy of reliability assessment on the programming language and software reliability model. To this end, software reliability modeling was performed using the main reliability models, such as: Dzhelinsky-Moranda, non- uniform Poisson process (Gela-Okumoto), Schneide-Windows, Musa, Weibul model, S-Shaped model, Du- ena, geometric model of Moranda, Musa-Okumoto. The existence of the problem of choosing a reliability model, which is due to their large number, is noted. It is shown that the problem of choosing a model has not yet been resolved. For research, we selected time series for defect detection in 40 software systems writ- ten in various programming languages: JavaScript, Ruby, Python, Objective-C, C ++, Scala, C #, PHP, C, Java, Rust, ActionScript. The data source for the specified time series is the Internet resource Github.com. Modeling was carried out using specialized software developed by the authors. The simulation accuracy was estimated as the mean-squared deviation of the calculated cumulative defect detection curve from the real one. The dependence of the accuracy of software reliability assessment on the programming language and reliability model is given. Recommendations are given on choosing a model for a software system de- pending on the programming language. It is concluded that there is no one universal model that with ac- ceptable accuracy would allow us to evaluate the reliability of a software system, regardless of the pro- gramming language in which it was written.

Research on Reliability of Software in Internet of Things for Risk Assessment and Reengineering

2013 ◽  
Vol 427-429 ◽  
pp. 2660-2663
Author(s):  
Jun Wang ◽  
Li Hu Shao
Keyword(s):  
Risk Assessment ◽  
Quality Of Service ◽  
Internet Of Things ◽  
Reliability Index ◽  
Evaluation System ◽  
Reliability Assessment ◽  
Software System ◽  
Application Layer ◽  
Software Assessment

In order to establish software system in application conditions of Internet of Things (IOT) on reliability of evaluation system and methods. This paper puts Quality of Service (QoS) of the protocols and reliability assessment of software system together, with aims at research on very large complex software system in reliability assessment, which is consisted of individual components in distribution of the perception layer, network layer and application layer of IOT and subsystems. At the same time, this paper adopts reengineering technology to realize the reliability evolution of software system in IOT application conditions, and improve the reliability index of software assessment further.

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