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Experimental algorithmics, as its name indicates, combines algorithmic work and experimentation: algorithms are not just designed, but also implemented and tested on a variety of instances. Perhaps the most important lesson in this process is that designing an algorithm is but the first step in the process of developing robust and efficient software for applications.

Based on a seminar held at Dagstuhl Castle, Germany in September 2000, this state-of-the-art survey presents a coherent survey of the work done in the area so far. The 11 carefully reviewed chapters provide complete coverage of all current topics in experimental algorithmics.




 Experimental algorithmics, as its name indicates, combines algorithmic work and experimentation: algorithms are not just designed, but also implemented and tested on a variety of instances. Perhaps the most important lesson in this process is that designing an algorithm is but the first step in the process of developing robust and efficient software for applications.

Based on a seminar held at Dagstuhl Castle, Germany in September 2000, this state-of-the-art survey presents a coherent survey of the work done in the area so far. The 11 carefully reviewed chapters provide complete coverage of all current topics in experimental algorithmics.




 Experimental algorithmics, as its name indicates, combines algorithmic work and experimentation: algorithms are not just designed, but also implemented and tested on a variety of instances. Perhaps the most important lesson in this process is that designing an algorithm is but the first step in the process of developing robust and efficient software for applications.

Based on a seminar held at Dagstuhl Castle, Germany in September 2000, this state-of-the-art survey presents a coherent survey of the work done in the area so far. The 11 carefully reviewed chapters provide complete coverage of all current topics in experimental algorithmics.


Content:
Front Matter....Pages I-XIII
Algorithm Engineering for Parallel Computation....Pages 1-23
Visualization in Algorithm Engineering: Tools and Techniques....Pages 24-50
Parameterized Complexity: The Main Ideas and Connections to Practical Computing....Pages 51-77
A Comparison of Cache Aware and Cache Oblivious Static Search Trees Using Program Instrumentation....Pages 78-92
Using Finite Experiments to Study Asymptotic Performance....Pages 93-126
WWW.BDD-Portal.ORG: An Experimentation Platform for Binary Decision Diagram Algorithms....Pages 127-138
Algorithms and Heuristics in VLSI Design....Pages 139-162
Reconstructing Optimal Phylogenetic Trees: A Challenge in Experimental Algorithmics....Pages 163-180
Presenting Data from Experiments in Algorithmics....Pages 181-196
Distributed Algorithm Engineering....Pages 197-228
Implementations and Experimental Studies of Dynamic Graph Algorithms....Pages 229-278
Back Matter....Pages 279-279


 Experimental algorithmics, as its name indicates, combines algorithmic work and experimentation: algorithms are not just designed, but also implemented and tested on a variety of instances. Perhaps the most important lesson in this process is that designing an algorithm is but the first step in the process of developing robust and efficient software for applications.

Based on a seminar held at Dagstuhl Castle, Germany in September 2000, this state-of-the-art survey presents a coherent survey of the work done in the area so far. The 11 carefully reviewed chapters provide complete coverage of all current topics in experimental algorithmics.


Content:
Front Matter....Pages I-XIII
Algorithm Engineering for Parallel Computation....Pages 1-23
Visualization in Algorithm Engineering: Tools and Techniques....Pages 24-50
Parameterized Complexity: The Main Ideas and Connections to Practical Computing....Pages 51-77
A Comparison of Cache Aware and Cache Oblivious Static Search Trees Using Program Instrumentation....Pages 78-92
Using Finite Experiments to Study Asymptotic Performance....Pages 93-126
WWW.BDD-Portal.ORG: An Experimentation Platform for Binary Decision Diagram Algorithms....Pages 127-138
Algorithms and Heuristics in VLSI Design....Pages 139-162
Reconstructing Optimal Phylogenetic Trees: A Challenge in Experimental Algorithmics....Pages 163-180
Presenting Data from Experiments in Algorithmics....Pages 181-196
Distributed Algorithm Engineering....Pages 197-228
Implementations and Experimental Studies of Dynamic Graph Algorithms....Pages 229-278
Back Matter....Pages 279-279
....
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