XML TRANSFORMATION LANGUAGE BASED ON MONADIC SECOND ORDER LOGIC by

Although monadic second-order logic (MSO) has been a foundation of XML queries, little work has attempted to take MSO formulae themselves as a programming construct. Indeed, MSO formulae are capable of expressing (1) all regular queries, (2) deep matching without explicit recursion, (3) queries in a “don’t-care semantics” for unmentioned nodes and (4) nary queries for locating n-tuples of nodes. While previous frameworks for subtree extraction (path expressions, pattern matches, etc.) each had some of these properties, none has satisfied all of them. In this thesis, we have designed and implemented a practical XML transformation language called MTran that fully exploits the expressiveness of MSO. MTran is a language based on “select-and-transform” templates similar in spirit to XSLT. However, we specialize our templates for expressing structure-preserving transformation so as to avoid any recursive calls to explicitly be written. Moreover, we allow templates to be nested so as to make use of an n-ary query that depends on the n− 1 nodes selected by the preceding templates. For the implementation of the MTran language, we have developed, as the core part, an efficient evaluation strategy for n-ary MSO queries. This consists of (a) an exploitation of the existing MONA system for the translation from MSO formulae to tree automata and (b) our novel query evaluation algorithm for tree automata. Although a linear time algorithm has been known for nullary and unary queries, the best known algorithm for n-ary queries takes O(rt + s) time in the worst case where t is the size of the input document, s is that of the output, and r is the size of potential matches during the query calculation, which can grow up to tn−1 in the worst case. We have developed a more efficient O(t + s) algorithm for n-ary queries by using partially lazy evaluation of set operations.