Database Programming Languages: 12th International Symposium, Dbpl 2009, Lyon, France, August 23-24, 2009, Proceedings: Vol 5708

Gardner, Philippa (Editor)/ Geerts, Floris (Editor)

ISBN 10: 3642037925 / ISBN 13: 9783642037924

Editore: Springer-Verlag New York Inc, 2009

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2009 edition. 101 pages. 9.50x6.00x0.25 inches. In Stock. Codice articolo x-3642037925

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Titolo: Database Programming Languages: 12th ...

Casa editrice: Springer-Verlag New York Inc

Data di pubblicazione: 2009

Legatura: Paperback

Condizione: Brand New

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Riassunto:

This volume contains the proceedings of the 12th International Symposium on Database Programming Languages (DBPL 2009), held in Lyon, France on - gust 24, 2009,and co-locatedwith VLDB (the International Conference on Very Large Data Bases). DBPL continues to present high-quality work at the intersection of database and programming language research. This proceedings volume contains the six papersacceptedforDBPL2009,whichwereselectedbytheProgramCommittee. Every submission was reviewed by at least three members of the committee. In addition, we sought the opinions of external referees, chosen because of their expertise in a particular topic. We would like to thank all the authorswho submitted papers to DBPL 2009. We also thank the members of the Program Committee for their excellent work during the electronic selection meeting. We are grateful to Andrei Voronkov for his EasyChair system, which made these discussions comparatively straightf- ward. WewouldliketothankMarceloArenasandMichaelI.Schwartzbachfortheir assistanceandsoundcouncilasProgramChairsofDBPL2007.We?nallythank Mohand-Said Hacid and Jean-Marc Petit for their superb local organization of DBPL 2009.

Contenuti:

Semantics, Types and Effects for XML Updates.- An Automata-Theoretic Approach to Regular XPath.- The Script-Writer’s Dream: How to Write Great SQL in Your Own Language, and Be Sure It Will Succeed.- XML Security Views Revisited.- A Tractable Subclass of DTDs for XPath Satisfiability with Sibling Axes.- General Database Statistics Using Entropy Maximization.