I owe my gratitude to my parents, inlaws, relatives and family friends for their. Software designers are motivated to develop reliable, reusable and useful software. A change in operation environment may cause false alarm, or masking of faults. Citeseerx document details isaac councill, lee giles, pradeep teregowda. In the context of software engineering, software quality refers to two related but distinct notions.
An overview of software reliability models semantic scholar. A number of soft computing approaches for estimating cbss reliability have been proposed. Soft computing may be applied to estimate reliability. A soft computing approach for ranking firms based on experts valuation of corporate social responsibility free download. He received his phd from iit kharagpur in reliability engineering. Software reliability modeling has been one of the muchattracted research domains in software reliability engineering.
Software reliability modeling has matured to the point that meaningful results can be obtained by applying suitable models to the problem. Their combined citations are counted only for the first article. Various statistical multiple linear regression and multivariate adaptive regression splines and intelligent techniques backpropagation trained neural. Reliability and high availability have always been a major concern in distributed systems. Maintainability is closely related to ward cunninghams concept of technical debt, which is an expression of the costs resulting of a lack of maintainability. Software reliability using soft computing chander diwaker1, pradeep tomar2, arun solanki2, anand nayyar 3, nz jhanjhi 4, azween abdullah4, and mahadevan supramaniam5 1department of computer science and engineering, u. Vadlamani ravi, mieee, macm, fapas,minforms,mismcdm. Citeseerx design and analysis of reliability for component. Reliable information about the coronavirus covid19 is available from the world health organization current situation, international travel. A study on software reliability prediction models using. This cited by count includes citations to the following articles in scholar. Kassem saab for the reliability software development, implementation and simulation. A fuzzy logic approach studies in fuzziness and soft computing pdf, epub, docx and torrent then this site is not for you. A fuzzy logic approach studies in fuzziness and soft computing hardcover 24 july 20 by ajeet kumar pandey author visit amazons ajeet kumar pandey page.
The goal of this paper is to propose a fuzzy logic soft computing technique based model using three reliability metrics for estimating the security of open source. Use features like bookmarks, note taking and highlighting while reading early software reliability prediction. Software reliability without excessive limitations. For most other systems, eventually you give up looking for faults and ship it. A fuzzy logic approach studies in fuzziness and soft computing. Machine learning approach for software reliability growth. Application of soft computing techniques in software reliability engineering has come up recently madsen et al. For systems that require high reliability, this may still be a necessity.
The continuous demand for ever more complex software systems and the emergence of new computing platforms pose significant challenges for the reliability and security of software applications. Various approaches can be used to improve the reliability of component based software system, however, it is hard to balance development time and budget with software reliability. For software reliability, we present mutation analysis as a technique of software testing. It provides rapid dissemination of important results in soft computing technologies, a fusion of research in evolutionary algorithms and genetic programming, neural science and neural net systems, fuzzy set theory and fuzzy systems, and chaos theory and chaotic systems. Reliability and high availability in cloud computing. Programming for reliability as we have seen, squeezing the last few bugs out of a system can be very costly. These various soft computing approaches can able to give better prediction, dynamic behavior, and extraordinary performance of modelling. Only an already known behavior, that is a deterministic process, can be. Soft computing to sensor network reliability, systems and their fpga implementation arati m. Pdf software reliability estimation of component based. This paper discusses different techniques to evaluate the system reliability.
Software reliability testing is a field of software testing that relates to testing a software s ability to function, given environmental conditions, for a particular amount of time. A new model for predicting componentbased software. Software reliability modeling using soft computing techniques. For computerbased systems that are running software applications, soft errors become a key challenge in microprocessor design. A new model for predicting componentbased software reliability. Providing highly available and reliable services in cloud computing is essential for maintaining customer confidence and satisfaction and preventing revenue losses. Soft computing approach for prediction of software reliability. A study on software reliability prediction models using soft. Software reliability models assess the reliability by\ud predicting faults for the software. Software reliability testing is a field of software testing that relates to testing a softwares ability to function, given environmental conditions, for a particular amount of time. Different approaches are discussed in this book to tackle this challenging issue. A new model is proposed to estimate the reliability of componentbased software cbs. These errors may have an effect on the correct software execution, and thus impact the overall system reliability. To overcome this lacuna, test effort was used instead of time in srgms.
Software reliability training covers all the concepts, tools, and methods to predict software reliability before writing the code. Reliability of component based software system using soft. Although various solutions have been proposed for cloud availability and reliability, but there are no comprehensive studies that completely. The two basic elements of soft computing are neural networks and fuzzy logic. Download it once and read it on your kindle device, pc, phones or tablets. Software reliability is an useful measure in planning and controlling the resources during the development process so that high quality software can be developed. Pdf software reliability modeling using soft computing. A fuzzy logic approach studies in fuzziness and soft computing book 303 kindle edition by pandey, ajeet kumar, goyal, neeraj kumar. Reliability is a real world\ud phenomenon with many associated realtime problems. Memoryaware design space exploration for reliability. Reasons for why maintainability is low can be classified as reckless vs.
Her research interests include software reliability modelling, artificial neural networks and soft computing techniques. These techniques learn from the past and capture existing patterns in data. Despite the recent advancements in the software reliability growth models, it was observed that different models have different predictive capabilities and also no single model is suitable under all circumstances. Hybrid intelligent systems for predicting software reliability. On using soft computing techniques in software reliability engineering 65 models, and knowledge. Traditional timebased srgms may not be accurate enough in all situations where test effort varies with time.
Software reliability prediction by soft computing techniques article in journal of systems and software 814. What is soft computing techniques used in soft computing 2 what is soft computing. Soft computing techniques can help to solve problems whose solutions are uncertain or unpredictable. Software reliability means provide reusable, less complex software, to perform a set of successful operation and his function within a provided time and environment. This paper considers soft computing techniques in order to be used for s.
Software reliability prediction using soft computing techniques. Software reliability prediction by soft computing techniques journal. That attribute can also be described as the fitness for purpose of a piece of software or how it compares to competitors in the marketplace as a. Journal of systems and software 81 4, 576583, 2008.
Neeraj kumar goyal is currently an associate professor in subir chowdhury school of quality and reliability, indian institute of technology kharagpur, india. Software reliability prediction of open source software using soft. Abstract software reliability is the probability of failurefree software operation for a specified period of time in a specified environment. Software reliability engineering is an area that created from family history in the dependability controls of electrical, auxiliaryabstract, and equipment building. Software reliability models assess the reliability by predicting faults for the software. Topics in software reliability college of computing. Software reliability growth models srgms are used to assess the reliability achieved at different times of testing. If youre looking for a free download links of early software reliability prediction. Software reliability modeling using soft computing. Zadeh soft computing differs from conventional hard computing in that, unlike hard computing, it is tolerant of imprecision, uncertainty, partial truth, and approximation. The book presents an early software reliability prediction model that will help to grow the reliability of the software systems by monitoring it in each development phase, i. Numerous and frequentlyupdated resource results are available from this search.
It provides rapid dissemination of important results in soft computing technologies, a fusion of research in evolutionary algorithms and genetic programming, neural science and neural net systems, fuzzy set theory and fuzzy systems, and chaos theory and chaotic. In this paper, we examine an analytical perspective of software reliability prediction using soft computing techniques with specific focus on methods, metrics and datasets. O n fuzzy logic, neura l nets and soft computing, 1. A fuzzy logic approach studies in fuzziness and soft computing pandey, ajeet kumar, goyal, neeraj kumar on. Planning and controlling the testing resources via software reliability measures can be done by balancing the additional cost of testing and the corresponding improvements in software reliability. Software reliability is a key part in software quality. Pdf soft computing approach for prediction of software reliability. In this paper, ensemble models are developed to accurately forecast software reliability.
Software reliability is defined as the probability of the failurefree operation of a software system for a specified period of time in a specified environment 22. Soft computing is dedicated to system solutions based on soft computing techniques. Soft computing techniques in soft computing the problem is represented in such a way that the state of the system can somehow be calculated and compared to some desired state. Ravi, title software reliability prediction by soft computing techniques, year 2007.
Pdf the paper is based on fuzzy logic fl and neural network nn techniques to predict the software reliability using the matlab toolbox. In effect, the role model for soft computing is the human mind. Software reliability differs considerably from program correctness see program correctness proof. Prediction of software reliability using bio inspired soft computing. Previous investigations have shown the importance of evaluating computer performances and predicting the system reliability. Software functional quality reflects how well it complies with or conforms to a given design, based on functional requirements or specifications. Software reliability is also an important factor affecting system reliability.
Reliability models are the most prevailing devices in programming dependability building for approximating, insidious, gauging, and assessing the unwavering quality of the product. Reliability is one of the quantifiable software quality attributes. To\ud obtain solutions to problems quickly, accurately and acceptably,\ud a large number of soft computing techniques have been\ud developed, but it is very difficult to. Software reliability testing helps discover many problems in the software design and functionality. Various statistical multiple linear regression and multivariate adaptive. Citeseerx software reliability prediction by soft computing.
Accurate software reliability prediction can not only enable developers to improve the quality of software but also provide useful information to help them for planning valuable resources. In this paper, we examine an analytical perspective of software reliability prediction using soft computing techniques with specific focus on methods. Artificial neural network applications for software. Soft computing to sensor network reliability, systems and. Software reliability prediction by soft computing techniques. Several possibilities are available to apply soft computing techniques in medicine related problems. Pdf software reliability prediction by soft computing. Software reliability training provides you with all the knowledge and techniques you need to practically apply software reliability in real world projects. The study of software reliability can be categorized into three parts. An adaptive neuro fuzzy model for estimating the reliability. Prediction of software reliability using bio inspired soft computing techniques. Oclcs webjunction has pulled together information and resources to assist library staff as they consider how to handle coronavirus. However, few techniques propose an accurate evaluation, at the software level, of the overall reliability of computing systems that are running a software against hardware faults. Reliability is a real world phenomenon with many associated realtime problems.
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