Algorithm Engineering [recurso electrónico] : Bridging the Gap between Algorithm Theory and Practice / edited by Matthias Müller-Hannemann, Stefan Schirra.
Tipo de material: TextoSeries Lecture Notes in Computer Science ; 5971Editor: Berlin, Heidelberg : Springer Berlin Heidelberg, 2010Descripción: XVI, 513 p. 72 illus. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9783642148668Tema(s): Computer science | Software engineering | Data structures (Computer science) | Computer software | Electronic data processing | Computer simulation | Computer Science | Algorithm Analysis and Problem Complexity | Mathematical Logic and Formal Languages | Software Engineering | Simulation and Modeling | Data Structures | Numeric ComputingFormatos físicos adicionales: Printed edition:: Sin títuloClasificación CDD: 005.1 Clasificación LoC:QA76.9.A43Recursos en línea: Libro electrónicoTipo de ítem | Biblioteca actual | Colección | Signatura | Copia número | Estado | Fecha de vencimiento | Código de barras |
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Libro Electrónico | Biblioteca Electrónica | Colección de Libros Electrónicos | QA76.9 .A43 (Browse shelf(Abre debajo)) | 1 | No para préstamo | 374882-2001 |
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QA76.9 .A43 Wireless Algorithms, Systems, and Applications | QA76.9 .A43 Matters Computational | QA76.9 .A43 Methods and Tools of Parallel Programming Multicomputers | QA76.9 .A43 Algorithm Engineering | QA76.9 .A43 Mathematical Foundations of Computer Science 2010 | QA76.9 .A43 Theoretical Computer Science | QA76.9 .A43 Introduction to Reliable and Secure Distributed Programming |
1. Foundations of Algorithm Engineering -- 2. Modeling -- 3. Selected Design Issues -- 4. Analysis of Algorithms -- 5. Realistic Computer Models -- 6. Implementation Aspects -- 7. Libraries -- 8. Experiments -- 9. Case Studies -- 10. Challenges in Algorithm Engineering.
Algorithms are essential building blocks of computer applications. However, advancements in computer hardware, which render traditional computer models more and more unrealistic, and an ever increasing demand for efficient solution to actual real world problems have led to a rising gap between classical algorithm theory and algorithmics in practice. The emerging discipline of Algorithm Engineering aims at bridging this gap. Driven by concrete applications, Algorithm Engineering complements theory by the benefits of experimentation and puts equal emphasis on all aspects arising during a cyclic solution process ranging from realistic modeling, design, analysis, robust and efficient implementations to careful experiments. This tutorial - outcome of a GI-Dagstuhl Seminar held in Dagstuhl Castle in September 2006 - covers the essential aspects of this process in ten chapters on basic ideas, modeling and design issues, analysis of algorithms, realistic computer models, implementation aspects and algorithmic software libraries, selected case studies, as well as challenges in Algorithm Engineering. Both researchers and practitioners in the field will find it useful as a state-of-the-art survey.
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