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Titlebook: Early Software Reliability Prediction; A Fuzzy Logic Approa Ajeet Kumar Pandey,Neeraj Kumar Goyal Book 2013 Springer India 2013 Bayesian Mo

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發(fā)表于 2025-3-21 19:21:10 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Early Software Reliability Prediction
副標題A Fuzzy Logic Approa
編輯Ajeet Kumar Pandey,Neeraj Kumar Goyal
視頻videohttp://file.papertrans.cn/301/300809/300809.mp4
概述Presents an early software reliability prediction model that will help to grow the reliability of the software systems.Highly useful for practitioners and professionals.Discusses multistage model for
叢書名稱Studies in Fuzziness and Soft Computing
圖書封面Titlebook: Early Software Reliability Prediction; A Fuzzy Logic Approa Ajeet Kumar Pandey,Neeraj Kumar Goyal Book 2013 Springer India 2013 Bayesian Mo
描述The development of software system with acceptable level of reliability and quality within available time frame and budget becomes a challenging objective. This objective could be achieved to some extent through early prediction of number of faults present in the software, which reduces the cost of development as it provides an opportunity to make early corrections during development process. 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.e. from requirement phase to testing phase. Different approaches are discussed in this book to tackle this challenging issue. An important approach presented in this book is a model to classify the modules into two categories (a) fault-prone and (b) not fault-prone. The methods presented in this book for assessing expected number of faults present in the software, assessing expected number of faults present at the end of eachphase and classification of software modules in fault-prone or no fault-prone category are easy to understand, develop and use for any practitioner. The practitioners are expected to gain more informat
出版日期Book 2013
關(guān)鍵詞Bayesian Models; Capability Maturity Model; Fault Count Models; Fault Seeding Models; Fuzzy Set Theory; S
版次1
doihttps://doi.org/10.1007/978-81-322-1176-1
isbn_softcover978-81-322-1742-8
isbn_ebook978-81-322-1176-1Series ISSN 1434-9922 Series E-ISSN 1860-0808
issn_series 1434-9922
copyrightSpringer India 2013
The information of publication is updating

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Annahme A3: Konstante Parameterwertedeliver reliable software with acceptable level of quality, within given budget and schedule. One measure of software quality and reliability is the number of residual faults. Therefore, researchers are focusing on the identification of the number of fault presents in the software or identification
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https://doi.org/10.1007/978-3-322-80005-3o forth. It is very important to ensure that these changes are incorporated properly without any adverse effect on the quality and reliability of the software. In general, changing the software to correct faults or add new functionality can cause existing functionality to depart, introducing new fau
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