A Benchmark Collection of Deterministic Automata for XPath Queries

International audienceWe provide a benchmark collection of deterministic automatafor regular XPath queries. For this, we select the subcollection offorward navigational XPath queries from a corpus that Lick and Schmitzextracted from real-world XSLT and XQuery programs, compile them tostepwise hedge automata (SHAs), and determinize them. Large blowups by automatadeterminization are avoided by using schema-based determinization. The schemacaptures the \XML data model and the fact thatany answer of a path query must return a single node.Our collection also provides deterministic nested word automatathat we obtain by compilation from deterministic SHAs

Schema-Based Automata Determinization

International audienceWe propose an algorithm for schema-based determinization of finite automata on words and of stepwise hedge automata on nested words. The idea is to integrate schema-based cleaning directly into automata determinization. We prove the correctness of our new algorithm and show that it is always more efficient than standard determinization followed by schema-based cleaning. Our implementation permits to obtain a small deterministic automaton for an example of an XPath query, where standard determinization yields a huge stepwise hedge automaton for which schema-based cleaning runs out of memory

Subhedge Projection for Stepwise Hedge Automata

International audienceWe show how to evaluate stepwise hedge automata (SHAs) with subtree projection. Since this requires to pass finite state information top-down, we introduce the notion of downward stepwise hedge automata. We then use them in order to define an in-memory and a streaming evaluator with subhedge projection for SHAs. We tune the streaming evaluator so that it can decide membership at the earliest time point. We apply our algorithms to the problem of answering regular XPath queries on XML streams. Our experiments show that subhedge projection can indeed speed up earliest query answering on XML streams

Earliest Query Answering for Deterministic Stepwise Hedge Automata

International audienceEarliest query answering (EQA) is the problem to enumerate certain query answers on streams at the earliest events. We consider EQA for regular monadic queries on hedges or nested words defined by deterministic stepwise hedge automata (dShas). We present an EQA algorithm for dShas that requires time O(c m) per event, where m is the size of the automata and c the concurrency of the query. We show that our EQA algorithm runs efficiently on regular XPath queries in practice

A Benchmark Collection of Deterministic Automata for XPath Queries

International audienceWe provide a benchmark collection of deterministic automatafor regular XPath queries. For this, we select the subcollection offorward navigational XPath queries from a corpus that Lick and Schmitzextracted from real-world XSLT and XQuery programs, compile them tostepwise hedge automata (SHAs), and determinize them. Large blowups by automatadeterminization are avoided by using schema-based determinization. The schemacaptures the \XML data model and the fact thatany answer of a path query must return a single node.Our collection also provides deterministic nested word automatathat we obtain by compilation from deterministic SHAs

Schema-Based Automata Determinization

International audienceWe propose an algorithm for schema-based determinization of finite automata on words and of stepwise hedge automata on nested words. The idea is to integrate schema-based cleaning directly into automata determinization. We prove the correctness of our new algorithm and show that it is always more efficient than standard determinization followed by schema-based cleaning. Our implementation permits to obtain a small deterministic automaton for an example of an XPath query, where standard determinization yields a huge stepwise hedge automaton for which schema-based cleaning runs out of memory

Schema-Based Automata Determinization

International audienceWe propose an algorithm for schema-based determinization of finite automata on words and of stepwise hedge automata on nested words. The idea is to integrate schema-based cleaning directly into automata determinization. We prove the correctness of our new algorithm and show that it is always more efficient than standard determinization followed by schema-based cleaning. Our implementation permits to obtain a small deterministic automaton for an example of an XPath query, where standard determinization yields a huge stepwise hedge automaton for which schema-based cleaning runs out of memory