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Abstract: XML tree structures can conveniently be represented using ordered unranked trees. Due to the repetitiveness of XML markup these trees can be compressed effectively using dictionary-based methods, such as minimal directed acyclic graphs (DAGs) or straight-line context-free (SLCF) tree grammars. While minimal SLCF tree grammars are in general smaller than minimal DAGs, they cannot be computed in polynomial time unless . Here, we present a new linear time algorithm for computing small SLCF tree grammars, called TreeRePair, and show that it greatly outperforms the best known previous algorithm BPLEX. TreeRePair is a generalization to trees of Larsson and Moffat's RePair string compression algorithm. SLCF tree grammars can be used as efficient memory representations of trees. Using TreeRePair, we are able to produce the smallest queryable memory representation of ordered trees that we are aware of. Our investigations over a large corpus of commonly used XML documents show that tree traversals over TreeRePair grammars are 14 times slower than over pointer structures and 5 times slower than over succinct trees, while memory consumption is only 1/43 and 1/6, respectively. With respect to file compression we are able to show that a Huffman-based coding of TreeRePair grammars gives compression ratios comparable to the best known XML file compressors. [Copyright &y& Elsevier]

Abstract: Implementations that load XML documents and give access to them via, e.g., the DOM, suffer from huge memory demands: the space needed to load an XML document is usually many times larger than the size of the document. A considerable amount of memory is needed to store the tree structure of the XML document. In this paper, a technique is presented that allows to represent the tree structure of an XML document in an efficient way. The representation exploits the high regularity in XML documents by compressing their tree structure; the latter means to detect and remove repetitions of tree patterns. Formally, context-free tree grammars that generate only a single tree are used for tree compression. The functionality of basic tree operations, like traversal along edges, is preserved under this compressed representation. This allows to directly execute queries (and in particular, bulk operations) without prior decompression. The complexity of certain computational problems like validation against XML types or testing equality is investigated for compressed input trees. [Copyright &y& Elsevier]