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Titlebook: Software Development Measurement Programs; Development, Managem Miroslaw Staron,Wilhelm Meding Book 2018 Springer International Publishing

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書目名稱Software Development Measurement Programs
副標(biāo)題Development, Managem
編輯Miroslaw Staron,Wilhelm Meding
視頻videohttp://file.papertrans.cn/871/870717/870717.mp4
概述Combines academic research with industrial practice to support companies in their journey from manual reporting to automated decision support.Organized as a gradual progression from theories of measur
圖書封面Titlebook: Software Development Measurement Programs; Development, Managem Miroslaw Staron,Wilhelm Meding Book 2018 Springer International Publishing
描述This book seeks to promote the structured, standardized and accurate use of software measurement at all levels of modern software development companies. To do so, it focuses on seven main aspects:? sound scientific foundations, cost-efficiency, standardization, value-maximization, flexibility, combining organizational and technical aspects, and seamless technology integration. Further, it supports companies in their journey from manual reporting to automated decision support by combining academic research and industrial practice..When scientists and engineers measure something, they tend to focus on two different things. Scientists focus on the ability of the measurement to quantify whatever is being measured; engineers, however, focus on finding the right qualities of measurement given the designed system (e.g. correctness), the system’s quality of use (e.g. ease of use), and the efficiency of the measurement process. In this book, the authors arguethat both focuses are necessary, and that the two are complementary. Thus, the book is organized as a gradual progression from theories of measurement (yes, you need theories to be successful!) to practical, organizational aspects of ma
出版日期Book 2018
關(guān)鍵詞Software Functional Properties; Software Creation and Management; Software Measurement; Software Develo
版次1
doihttps://doi.org/10.1007/978-3-319-91836-5
isbn_softcover978-3-030-06308-5
isbn_ebook978-3-319-91836-5
copyrightSpringer International Publishing AG, part of Springer Nature 2018
The information of publication is updating

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Miroslaw Staron,Wilhelm Meding This course, taught in a mathematically rigorous fashion, covers essential - terials in statistical theory that a ?rst or second year graduate student typically needs to learn as preparation for work on a Ph. D. degree in stat- tics. The course is designed for two 15-week semesters, with three lect
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Miroslaw Staron,Wilhelm Meding This course, taught in a mathematically rigorous fashion, covers essential - terials in statistical theory that a ?rst or second year graduate student typically needs to learn as preparation for work on a Ph. D. degree in stat- tics. The course is designed for two 15-week semesters, with three lect
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Miroslaw Staron,Wilhelm Meding This course, taught in a mathematically rigorous fashion, covers essential - terials in statistical theory that a ?rst or second year graduate student typically needs to learn as preparation for work on a Ph. D. degree in stat- tics. The course is designed for two 15-week semesters, with three lect
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發(fā)表于 2025-3-22 21:58:26 | 只看該作者
Miroslaw Staron,Wilhelm Meding This course, taught in a mathematically rigorous fashion, covers essential - terials in statistical theory that a ?rst or second year graduate student typically needs to learn as preparation for work on a Ph. D. degree in stat- tics. The course is designed for two 15-week semesters, with three lect
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Miroslaw Staron,Wilhelm Meding This course, taught in a mathematically rigorous fashion, covers essential - terials in statistical theory that a ?rst or second year graduate student typically needs to learn as preparation for work on a Ph. D. degree in stat- tics. The course is designed for two 15-week semesters, with three lect
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Miroslaw Staron,Wilhelm Meding This course, taught in a mathematically rigorous fashion, covers essential - terials in statistical theory that a ?rst or second year graduate student typically needs to learn as preparation for work on a Ph. D. degree in stat- tics. The course is designed for two 15-week semesters, with three lect
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