Failure correlation in software reliability models

Proceedings. 2000 Pacific Rim International Symposium on Dependable Computing, 2000

Since the early 1970's a number of models have been proposed for estimating software reliability. However, the realism of many of the underlying assumptions and the applicability of these models continue to be questioned. Our research work was motivated by the fact that although there are practical situations in which the assumption of independence among successive software failures could be easily violated, much of the published literature on software reliability modeling does not seriously address this issue. In this paper we present a modeling framework based on Markov renewal processes which naturally introduces dependence among successive software runs and enables the phenomena of failure correlation to be precisely characterized. Thus, incorporating failure correlation into dependability and performability predictions contributes toward more realistic modeling of software systems in operation. u C © e

Proceedings of 1993 IEEE International Symposium on Software Reliability Engineering, 1993

T h e reliability models often assume random testing and statistical independence of f a u l t s t o keep the analysis tractable. In practice, these assumptions d o n o t hold. T h i s paper presents a reliability modeling approach that considers nonrandom testing. T h i s approach is used t o calculate the f a u l t exposure ratio, which characterizes the testingprocess. T h e analysis of the experimental data suggests that the fault exposure ratio varies differently in the early and the later stages of testing. T h e analysis here presents a n explanation of this behavior.

Software Engineering, IEEE …, 1978

This paper examines the most widely used reliability modeLs. The models discussed fall into two categories, the data domain and the time domain. Besides tracing the historical development of the various models their advantages and disadvantages are analyzed. This includes models based on discrete as weil as continuous probability distributions. How well a given model performs its purpose in a specific economic environment will determine the usefulness of the model. Each of the models is examined with actual data as to the applicability of the error fmding process.

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.

Relation, 2007

Experience of applying reliability models in the past has shown that the relative predictive performance of the models depends entirely on the context. It has been found that there is no one model that performs well over all data sets. It has also been found that for some data sets all models ...

International Journal of Performability Engineering, 2013

The primary intention of the present study is to investigate the critical factors and issues that are accountable for poor performance of software reliability models. Critically reviewing the literature indicates that software reliability models have not delivered fully the desirable outcomes that they are intended to achieve. The findings of the current stuffy reveal that the reasons for performance incompetence of the software reliability models in effectively improving the reliability of the software are attributed to 14 major flaws. The implications of these flaws on the performance of software reliability models' have been explored.

1996

A number of software reliability models have been proposed for assessing the reliability of a software system. In this paper, we discuss the time-domain and data-domain approaches to software reliability modeling, and classify the previously reported models into these two classes based on their underlying assumptions. The data-domain models are further classi ed into fault-seeding and input domain models, while the time-domain models are further classi ed into homogeneous Markov, non-homogeneous Markov and semi-Markov models. We present some representative models belonging to each of the classes, and then discuss the relative merits and limitations of the time and data-domain approaches.

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.

Software reliability analysis is performed at various stages during the process of engineering software as an attempt to evaluate if the software reliability requirements have been (or might be) met. In this report, I present a summary of some fundamental black-box and white-box software reliability models. I also present some general shortcomings of these models and suggest avenues for further research.

IEEE Transactions on Reliability, 1979

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