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020 _a9783030818852
_9978-3-030-81885-2
024 7 _a10.1007/978-3-030-81885-2
_2doi
050 4 _aQA76.9.M35
050 4 _aQA297.4
072 7 _aUYAM
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082 0 4 _a004.0151
_223
100 1 _aValiente, Gabriel.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 1 0 _aAlgorithms on Trees and Graphs
_h[electronic resource] :
_bWith Python Code /
_cby Gabriel Valiente.
250 _a2nd ed. 2021.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2021.
300 _aXV, 387 p. 145 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aTexts in Computer Science,
_x1868-095X
505 0 _a1. Introduction -- 2. Algorithmic Techniques -- 3. Tree Traversal -- 4. Tree Isomorphism -- 5. Graph Traversal -- 6. Clique, Independent Set, and Vertex Cover -- 7. Graph Isomorphism.
520 _aGraph algorithms is a well-established subject in mathematics and computer science. Beyond classical application fields, like approximation, combinatorial optimization, graphics, and operations research, graph algorithms have recently attracted increased attention from computational biology, bioinformatics, and computational chemistry. This textbook introduces graph algorithms on an intuitive basis followed by a detailed exposition using structured pseudocode, with correctness proofs as well as worst-case analyses. Centered around the fundamental issue of graph isomorphism, the content goes beyond classical graph problems of shortest paths, spanning trees, flows in networks, and matchings in bipartite graphs. Advanced algorithmic results and techniques of practical relevance are presented in a coherent and consolidated way. Numerous illustrations, examples, problems, exercises, and a comprehensive bibliography support students and professionals in using the book as a text and source of reference. Furthermore, Python code for all algorithms presented is given in an appendix. Topics and features: Algorithms are first presented on an intuitive basis, followed by a detailed exposition using structured pseudocode Correctness proofs are given, together with a worst-case analysis of the algorithms Full implementation of all the algorithms in Python An extensive chapter is devoted to the algorithmic techniques used in the book Solutions to all the problems Gabriel Valiente, PhD, is an accredited Full Professor at the Department of Computer Science and a member of the Algorithms, Bioinformatics, Complexity and Formal Methods Research Group of the Technical University of Catalonia in Barcelona, Spain. He has been lecturing on Data Structures and Algorithms at the undergraduate level and Advanced Graph Algorithms at the graduate level over the last several years. His current research is centered on combinatorial algorithms on graphs and, in particular, algorithms for comparing trees and graphs, with emphasis on algorithms in computational biology and bioinformatics.
650 0 _aComputer science
_xMathematics.
650 0 _aDiscrete mathematics.
650 0 _aAlgorithms.
650 0 _aGraph theory.
650 0 _aPython (Computer program language).
650 0 _aC++ (Computer program language).
650 1 4 _aDiscrete Mathematics in Computer Science.
650 2 4 _aAlgorithms.
650 2 4 _aGraph Theory.
650 2 4 _aPython.
650 2 4 _aC++.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783030818845
776 0 8 _iPrinted edition:
_z9783030818869
776 0 8 _iPrinted edition:
_z9783030818876
830 0 _aTexts in Computer Science,
_x1868-095X
856 4 0 _uhttps://doi.org/10.1007/978-3-030-81885-2
912 _aZDB-2-SCS
912 _aZDB-2-SXCS
942 _cSPRINGER
999 _c177795
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