Change Detection in Hierarchically Structured Information

Abstract

Detecting and representing changes to data is important for active databases, data warehousing, view maintenance, and version and conguration management. Most previous work in change management has dealt with at-le and relational data; we focus on hierarchically structured data. Since in many cases changes must be computed from old and new versions of the data, we dene the hierarchical change detection problem as the problem of nding a minimum-cost edit script that transforms one data tree to another, and we present efcient algorithms for computing such an edit script. Our algorithms make use of some key domain characteristics to achieve substantially better performance than previous, generalpurpose algorithms. We study the performance of our algorithms both analytically and empirically, and we describe the application of our techniques to hierarchically structured documents.