In this study, we present experiences of parallelizing XPath queries using the Xalan XPath engine on shared-address space multi-core systems. For our evaluation, we consider a scenario where an XPath processor uses multiple threads to concurrently navigate and execute individual XPath queries on a shared XML document. Given the constraints of the XML execution and data models, we propose three strategies for parallelizing individual XPath queries: Data partitioning, Query partitioning, and Hybrid (query and data) partitioning. We experimentally evaluated these strategies on an x86 Linux multi-core system using a set of XPath queries, invoked on a variety of XML documents using the Xalan XPath APIs. Experimental results demonstrate that the proposed parallelization strategies work very effectively in practice; for a majority of XPath queries under evaluation, the execution performance scaled linearly as the number of threads was increased. Results also revealed the pros and cons of the...