Software Reliability Model Study

IEEE Software, 2000

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Software reliability is one of the significant factor in finalizing the quality of software. In recent years, Software Reliability Growth Models(SRGM) are used by number of software development organizations to assess and analyse the software product's quality. The estimation of reliability of software can save loss of time and cost. These models are applicable at the final stage of software development. In this paper, we propose a new model for assessing the software product's reliability. It first focuses on some of available reliability models and discuss about the problems associated with existing models and arrive at a new reliability model. Keywordssoftware reliability growth models(SRGM), hazard function, failure rate.

Software Engineering, IEEE Transactions …, 1985

When a new computer software package is developed and all obvious erros removed, a testing procedure is often put into effect to eliminate the remaining errors in the package. One common procedure is to try the package on a set of randomly chosen problems. We suppose that whenever a program encounters an error, a system failure results. At this point the software is inspected to determine and remove the error responsible for the failure. This goes on for some time and two problems of interest are 1) to estimate the error rate of the software at a given time t, and 2) to develop a stopping rule for determining when to discontinue the testing and declare that the software is ready for use. In this paper, a model for the above is proposed as an estimation and stopping rule procedure.

Software reliability is one of the attributes of software quality. Due to the increasing complexity of the software systems, delivering reliable software in a timely manner becomes a challenging task. Software Reliability Growth Models (SRGMs) are used to estimate the reliability of the software systems during testing. Although large number of SRGMs have been proposed, it appears that no single model can be considered to be suitable to describe every software failure data set. The research is still continuing to develop more robust models. However, the success of reliability modeling for a given project depends on selection of appropriate SRGM that will fi t the software failure data adequately. This paper presents a brief review of existing SRGMs, model selection methods.

Software plays an important role in every field of human activity today varying from medical diagnosis to remote controlling spacecraft. Hence it is important for the software to provide failure-free performance whenever needed. The Information technology industry has witnessed rapid growth in the recent past. The competition among the firms also increased. The software organization in the developing countries like India can no longer survive on cost advantage alone. The software companies need to deliver reliable and quality software on time. A lot of research has been carried out on software quality management and reliability estimation. The objective of this paper is to provide a brief review of the major research contribution in the field of software reliability and identify the future research areas in software reliability estimation and prediction Keywords: software reliability growth models, nonhomogeneous Poisson process models, s-shaped models, imperfect debugging I. INTRODUCTION Many organizations utilize information technology (IT) to improve productivity, enhance operational efficiency, responsiveness, etc [1] As a result, the IT industry has witnessed tremendous growth in the past few decades. As the number of information technology companies increased, the competition among them also increased. The software organization in the developing countries like India can no longer survive or grow based on cost advantage alone. But delivering reliable and quality software on time within budgeted cost is a challenge for many organizations [2], [3]. Many times the companies would compromise on software testing and release the software with residual defects. This would make the software unreliable. The software reliability is defined as the probability of failure-free operation of a software system for a specified time in a specified environment [4]. The failure of the software during operations can lead to customer dissatisfaction, loss of market share, etc. The failure of a software used in the medical device or that used in air traffic control system can have a disastrous effect on the individual as well as society. Hence it is imperative for the software firms to ensure their product is sufficiently reliable before releasing the software for usage. This paper is a brief review of the important developments happened in the field of software reliability and identifies the future research areas. The remaining part of this article is arranged as follows: the session II describes the literature review methodology, the literature review analysis is given in session III and the conclusion are discussed in session IV. II. LITERATURE REVIEW METHODOLOGY A lot of articles have been presented at conferences, published in journals and books have been written in the last few decades on software reliability estimation and prediction. The aim of this paper is to provide a brief review of the important researches carried on developing software reliability models. The process started with searching for relevant published articles. The scope of the review is limited to the published books and papers published in journals and important conference proceedings. The databases searched are IEEE explore, Science direct, Google scholar and research gate. Two hundred and nine papers are identified for review. After reading the abstract, ninety-seven papers are shortlisted for review. Another twenty-nine papers are later dropped as the content is not directly related to the focus area of the review. Finally, sixty-eight papers are included in the review. The details are given in fig 1.

Many software reliability growth models (SRGMs) have been analyzed for measuring the growth of software reliability. Selection of optimal SRGMs for use in a particular case has been an area of interest for researchers in the field of software reliability. All existing methodologies use same weight for each comparison criterion. But in reality, it is the fact that all the parameters do not have the same priority in reliability measurement. Keeping this point in mind, in this paper, a computational methodology based on weighted criteria is presented to the problem of performance analysis of various non-homogenous Poisson process (NHPP) models. It is relatively simple and requires less calculation.

Annual Reliability and Maintainability Symposium. 2002 Proceedings (Cat. No.02CH37318), 2002

The performance of a subset of the Software Reliability Growth models is investigated using various smoothing techniques. The method of parameter estimation for the models is the Maximum Likelihood Method. The evaluation of the performance of the models is judged by the relative error of the predicted number of failures over future time intervals relative to the number of failures eventually observed during the interval.

A software quality aspect is measured in terms of mean time to failure or failure intensity of the software. It is one of the key attributes when talk about software quality. Software quality may parts into quality aspect in various ways; however, software reliability seen as one of the key attribute of software quality. Software reliability is a valuable measure in planning and controlling the resources throughout the development process, as a result, high quality software can be developed. Scheduling and controlling the testing resources through software reliability measures can be completed by matching the additional cost of testing and the corresponding improvement in software reliability. It is too, a valuable measure for providing the user confidence about software correctness. A number of analytical models have been introduced in the past decades to assess the reliability of the software system. In this paper, researchers are giving an overview & analysis of software reliabil...

Software Engineering, IEEE Transactions on, 1985

A number of analytical models have been proposed during the past 15 years for assessing the reliability of a software system. In this paper we present an overview of the key modeling approaches, provide a critical analysis of the underlying assumptions, and assess the limitations and applicability of these models during the software development cycle. We also propose a step-by-step procedure for fitting a model and illustrate it via an analysis of failure data from a mediumsized real-time command and control software system.

This paper proposes a novel framework of software reliability growth models with software metrics. Our approach is to integrate a classical Poisson-regression-based fault prediction with non-homogeneous Poisson process based software reliability growth models. The remarkable feature of this approach is to handle time series data of fault detections and software metrics for a number of modules at the same time. In the paper, we present the modeling framework that combines Poisson-regression-based fault prediction and software reliability growth models, and also develop an efficient algorithm to estimate model parameters based on EM (expectation-maximization) algorithm. In numerical experiments, by comparing the proposed model with both Poisson-regression-based fault prediction and non-homogeneous Poisson process based software reliability growth models, we discuss the effectiveness of using time series data of fault detections and software metrics from both viewpoints of reliability ...