Abstract
Web query languages promise convenient and efficient access to Web data such as XML, RDF, or Topic Maps. Xcerpt is one such Web query language with strong emphasis on novel high-level constructs for effective and convenient query authoring, particularly tailored to versatile access to data in different Web formats such as XML or RDF. However, so far it lacks an efficient implementation to supplement the convenient language features. AMaXoS is an abstract machine implementation for Xcerpt that aims at efficiency and ease of deployment. It strictly separates compilation and execution of queries: Queries are compiled once to abstract machine code that consists in (1) a code segment with instructions for evaluating each rule and (2) a hint segment that provides the abstract machine with optimization hints derived by the query compilation. This article summarizes the motivation and principles behind AMaXoS and discusses how its current architecture realizes these principles.

URL:
http://rewerse.net/publications/rewerse-publications.html#REWERSE-RP-2006-031

BibTeX:

@inproceedings{REWERSE-RP-2006-031,
	author = {Fran\c{c}ois Bry and Tim Furche and Benedikt Linse},
	title = {AMaχoS Abstract Machine for Xcerpt: Architecture and Principles},
	booktitle = {Proceedings of 4th Workshop on Principles and Practice of Semantics Web Reasoning, Budva, Montenegro (10th--11th June 2006)},
	year = {2006},
	volume = {4187},
	organization = {REWERSE},
	series = {LNCS},
	pages = {105--119},
	url = {http://rewerse.net/publications/rewerse-publications.html#REWERSE-RP-2006-031}
}