Experimental Algorithmics [electronic resource] :From Algorithm Design to Robust and Efficient Software /
Contributor(s): Fleischer, Rudolf [editor.] | Moret, Bernard [editor.] | Schmidt, Erik Meineche [editor.] | SpringerLink (Online service).Material type: BookSeries: Lecture Notes in Computer Science: 2547Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2002.Description: XVIII, 286 p. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783540363835.Subject(s): Computer science | Data structures (Computer science) | Algorithms | Numerical analysis | Computer science -- Mathematics | Computer Science | Computer Science, general | Data Structures | Algorithm Analysis and Problem Complexity | Numeric Computing | Discrete Mathematics in Computer Science | AlgorithmsOnline resources: Click here to access online
Algorithm Engineering for Parallel Computation -- Visualization in Algorithm Engineering: Tools and Techniques -- Parameterized Complexity: The Main Ideas and Connections to Practical Computing -- A Comparison of Cache Aware and Cache Oblivious Static Search Trees Using Program Instrumentation -- Using Finite Experiments to Study Asymptotic Performance -- WWW.BDD-Portal.ORG: An Experimentation Platform for Binary Decision Diagram Algorithms -- Algorithms and Heuristics in VLSI Design -- Reconstructing Optimal Phylogenetic Trees: A Challenge in Experimental Algorithmics -- Presenting Data from Experiments in Algorithmics -- Distributed Algorithm Engineering -- Implementations and Experimental Studies of Dynamic Graph Algorithms.
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.