Evaluation of reliability of critical software system using fuzzy approach (original) (raw)

Software Reliability Modeling using Soft Computing Techniques: Critical Review

International Journal of Information Technology and Computer Science, 2015

Software reliability models assess the reliability by predicting faults for the software. Reliability is a real world phenomenon with many associated real-time problems. To obtain solutions to problems quickly, accurately and acceptably, a large number of soft computing techniques have been developed, but it is very difficult to find out which one is the most suitable and can be used globally. In this paper, we have provided an overview of existing soft computing techniques, and then critically analyzed the work done by the various researchers in the field of software reliability. Further to this, we have also compared soft computing techniques in terms of software reliability modeling capabilities.

Freepaper me-10 1145 2047414 2047425-Measuring-software-reliability-a-fuzzy-model 2

Software reliability is an essential part of software engineering to ensure the quality of a system. There are various techniques, which can be used in building models for predicting quality attributes. This paper presents a Fuzzy model for software reliability prediction. We have proposed three parameters Availability, Failure Probability and Recoverability as an integrated measure of software reliability. Fuzzy Model provides a way to arrive at a discrete Reliability Non-functional requirement (NFR) in contrast to imprecise, vague and ambiguous. This model will help us to evolve intermediate stages between reliable state and unreliable state of a system. Results obtained by proposed model show that this is suitable for predicting software reliability of the software.

SOFT COMPUTING APPROACH FOR PREDICTION OF SOFTWARE RELIABILITY

ICIC Express Letters ICIC International , 2018

The paper is based on Fuzzy Logic (FL) and Neural Network (NN) techniques to predict the software reliability using the MATLAB toolbox. There are four methods used in this paper to predict reliability of the dataset retrieved from John Musa of bell laboratories. These methods are fuzzy method, neural network, fuzzy-neural network and neural-fuzzy. After the assessment of data the results we achieved were best from the fuzzy-neural method among all proposed methods. In Fuzzy-neural method the Levenberg-Marquardt algorithm is used for training the neurons. The performance of our proposed approaches has been tested using the testing data, which 15% of the data from failure data set.

A Fuzzy Neural Network Approach for Assessment and Enhancing Software Reliability

Advances in Modelling and Analysis B, 2017

Software Reliability is the probability of non-failure software procedure for a predefined duration in a predetermined domain. Software Reliability is similarly an imperative factor manipulating structure with reliability [2]. It contrasts from hardware reliability in the way that it reflects the outline faultlessness, and to provide reliable software. The elevated intricacy of software is the major contributing element of Software Reliability issues. Software reliability engineering (SRE) surveys how well software based items and administrations meet client's operational needs. SRE utilizes quantitative techniques in view of reliability measures to do this evaluation. The essential objective of SRE is to boost consumer loyalty. SRE uses such quantitative strategies as factual estimation and expectation, estimation, and displaying. As the reliability of an item or administration is profoundly subject to working conditions and the reliability of software is identified with how the product is utilized, the quantitative portrayal of the utilization of software is an indispensable part in SRE. Software Cost Estimation with resonating unwavering quality, profitability and improvement exertion is a testing and burdensome undertaking. This has prompted the product group to give much required push and dig into broad research in Software exertion estimation for developing refined strategies. Estimation by similarity is one of the practical strategies in Software exertion estimation field. Be that as it may, the technique used for the estimation of Software exertion by similarity can't deal with the all-out information in an express and exact way. Another approach has been created in this paper to assess Software exertion for ventures spoke to by all out or numerical information utilizing thinking by similarity and fluffy 540 approach. The current chronicled datasets, investigated with fluffy rationale, deliver precise brings about correlation with the dataset examined with the before approaches. Software designing is a more extensive training of which SRE is a sub train. Software building is worried about all parts of outlining, executing, and dealing with the advancement of software [8]. Different parts of software building incorporate the financial aspects of creating software and the interfaces between software, frameworks, and people and with the practices and procedures for guaranteeing the nature of conveyed software. In this paper we ponder the product reliability of frameworks with the assistance of past failure related informational collections by utilizing Fuzzy Neural Networks (FNN) methods, Numerical cases are appeared with both real and mimicked datasets. Better execution of software reliability evaluation is watched, contrasted and unique FNN demonstrate with no such verifiable failure related information joined.

Predicting the Reliability of Software Systems Using Fuzzy Logic

2011 Eighth International Conference on Information Technology: New Generations, 2011

Software industry suffer many challenges in developing a high quality reliable software. Many factors affect their development such as the schedule, limited resources, uncertainty in the developing environment and inaccurate requirement specification. Software Reliability Growth Models (SRGM) were significantly used to help in solving these problems by accurately predicting the number of faults in the software during both development and testing processes. The issue of building growth models was the subject of many research work. In this paper, we explore the use of fuzzy logic to build a SRGM. The proposed fuzzy model consists of a collection of linear sub-models joined together smoothly using fuzzy membership functions to represent the fuzzy model. Results and analysis based data set developed by John Musa of Bell Telephone Laboratories [1] are provided to show the potential advantages of using fuzzy logic in solving this problem.

Reliability of Component based Software System using Soft Computing Techniques A Review

International Journal of Computer Applications, 2014

Component based software is a recent approach in the field of software engineering emphasizes on design and development of component based software system. It is based on reusability of code which let customer to have quality product by paying less amount of money and spending less time to produce. To enhance security there is need of reliable software. In this paper reliability study of windows operating system is done and aim of this study is to find out the most reliable windows operating system by use of fuzzy analytic hierarchy process and fuzzy technique for order preference by similarity to ideal solution (TOPSIS). Reliability factors for windows operating system is determined which forms criteria for selecting reliable windows operating system. After determining the criteria fuzzy multi-criteria decision making methods such as fuzzy analytic hierarchy process (AHP) and fuzzy technique for order preference by similarity to ideal solution (TOPSIS) are applied to reliable windows operating system selection problem and results are presented.

Fuzzy based ranking of software reliability measures

International Journal of System Assurance Engineering and Management, 2015

This research paper summarizes the results of an implementation of fuzzy multilevel methodology to rank software reliability measures. Of late, computer based systems are used largely for monitoring, protecting and to control safety critical systems like nuclear power plants, Aircraft etc. Reliability is an important factor for assessing the performance of such safety critical digital systems. The characteristics of such digital safety critical systems are explicitly or implicitly reflected by software engineering measures. Therefore, with the help of such measures, models can be built to predict the reliability of software applications that run on safety critical systems. It is not necessary that every software engineering measures contribute to predict the reliability, hence they need to be ranked based on their influence on reliability. Since sufficient practical data is not available in literature, expert opinion on the selected software engineering measures contributing to reliability based on criterion has been sought. These expert ratings are aggregated and ranked using Chen's fuzzy logic based ranking method. As the data involved with this kind of problems are inherently imprecise and inexact, application of fuzzy set theory is very suitable for such situations. The top-ranked software engineering measures can be later used to develop a model to predict reliability of safety critical digital systems.

Effective Assessment of Software Reliability by Using Neuro-Fuzzy System

International Journal of Research, 2015

Software reliability is defined as the probability of software to deliver correct service over a period of time under a specified environment. This is becoming more and more important in various software organizations to discover the faults that occur commonly during development process. As the demand of the software application programs increases the quality becomes higher and higher and the reliability of these software becomes more essential. Hence Software reliability is mentioned to be as the one of the important factor during development. Many analytical models were being proposed over the years for assessing the reliability of a software system and for modeling the growth trends of software reliability with different capabilities of prediction at different testing phases. A Neuro Fuzzy based software reliability (SR) model is presented to estimate and assess the quality. Multiple datasets containing software failures are applied to the proposed model. These datasets are obtained from several software projects. Then it is observed that the results obtained indicate a significant improvement in performance by using neural fuzzy model over conventional statistical models (Fuzzy Model) based on non homogeneous Poisson process.

A Survey of Software Reliability factor

Software Reliability is the probability of failure free software which work for a specified period of time in a specified environment. Software Reliability is also an important factor affecting system reliability. In the Existing, Software management approaches like CMM and SPICE gives the quantitative model of software process management. But these methods are based on the accuracy and the reliability of the input data to the system. This paper estimates the reliability factor issues of data for different metrics of software process model under different criteria. This paper is a survey which can be used to design a reliability system based on soft technique

Software Reliability Estimation of Component Based Software System using Fuzzy

Software Reliability Modeling has been one of the much-attracted research domains in Software Reliability Engineering. Software reliability means provide reusable, less complex software, to perform a set of successful operation and his function within a provided time and environment. Software designers are motivated to develop reliable, reusable and useful software. In past, Object-Oriented Programming System (OOPS) concept is to be used in purpose of reusability but they are not providing powerful to cope with the successive changing as per requirements of ongoing applications. After that Component Based Software system (CBSS) is in floor. IT is based on reusability of his component with less complexity. This paper presents a new approach to analyze the reusability, dependency, and operation profile as well as application complexity of component-based software system. Here, we apply Fuzzy Logic approach to estimate the reliability of component-based software system with the basis of reliability factor. Index Terms—Component, Object-Oriented Programming System (OOPS), Component Based Software system (CBSS), Fuzzy Logic, Fuzzy Inference System (FIS), Adaptive Neuro Fuzzy Inference System (ANFIS), Reliability, Application Complexity, Component Dependency, Operation Profile, Reusability, Fuzzification, Defuzzification, Reliability Model, Rule Based Model, Path Based Model, Additive Model, etc. http://sites.google.com/site/ijcsis/ ISSN 1947-5500