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Software performance and scalability : a quantitative approach /

Praise from the Reviewers:. "The practicality of the subject in a real-world situation distinguishes this book from othersavailable on the market."--Professor Behrouz Far, University of Calgary. "This book could replace the computer organization texts now in use that every CS and CpEs...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Liu, Henry H.
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Hoboken, N.J. : John Wiley & Sons, ©2009.
Colección:Quantitative software engineering series.
Temas:
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)

MARC

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245 1 0 |a Software performance and scalability :  |b a quantitative approach /  |c Henry H. Liu. 
260 |a Hoboken, N.J. :  |b John Wiley & Sons,  |c ©2009. 
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490 1 |a Quantitative software engineering series 
504 |a Includes bibliographical references and index. 
520 |a Praise from the Reviewers:. "The practicality of the subject in a real-world situation distinguishes this book from othersavailable on the market."--Professor Behrouz Far, University of Calgary. "This book could replace the computer organization texts now in use that every CS and CpEstudent must take. ... It is much needed, well written, and thoughtful."--Professor Larry Bernstein, Stevens Institute of Technology. A distinctive, educational text onsoftware performance and scalability. This is the first book to take a quantitative approach to the subject of software 
588 0 |a Print version record. 
505 0 |a Software Performance and Scalability; Contents; PREFACE; ACKNOWLEDGMENTS; Introduction; Performance versus Scalability; PART 1 THE BASICS; 1. Hardware Platform; 2. Software Platform; 3. Testing Software Performance and Scalability; PART 2 APPLYING QUEUING THEORY; 4. Introduction to Queuing Theory; 5. Case Study I: Queuing Theory Applied to SOA; 6. Case Study II: Queuing Theory Applied to Optimizing and Tuning Software Performance and Scalability; PART 3 APPLYING API PROFILING; 7. Defining API Profiling Framework; 8. Enabling API Profiling Framework; 9. Implementing API Profiling Framework. 
505 8 |a 10. Case Study: Applying API Profiling to Solving Software Performance and Scalability ChallengesAPPENDIX A STOCHASTIC EQUILIBRIUM AND ERGODICITY; A.1 Basic Concepts; A.2 Classification of Random Processes; A.3 Discrete-Time Markov Chains; A.4 Continuous-Time Markov Chains; A.5 Stochastic Equilibrium and Ergodicity; A.6 Birth-Death Chains; APPENDIX B MEMORYLESS PROPERTY OF THE EXPONENTIAL DISTRIBUTION; APPENDIX C M/M/1 QUEUES AT STEADY STATE; C.1 Review of Birth-Death Chains; C.2 Utilization and Throughput; C.3 Average Queue Length in the System; C.4 Average System Time; C.5 Average Wait Time. 
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650 0 |a System design. 
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