Comparative Analysis of XML Schema Languages for Improved Entropy Metric

The eXtensible Markup Language (XML) is a data set to represent data in a format that is both human readable and machine readable. For XML documents to provide understanding about data exchange between applications, XML schema documents should be validated against the schema language. Most existing schema metrics were implemented differently in Document Type Definition (DTD), XML Schema Definition (XSD) and Regular Language for Next Generation (RNG) but never compare XML schema languages on any metric. Hence this paper compared three different schema languages on Improved Entropy Metric (IEM) using the Number of Attributes (NA), Number of Equivalence Class (NEC), Frequency Occurrence of Class (FOCi) and Number of Elements (NE). The proposed metric was applied on real schemas documents data are acquired from Web Service Description Language (WSDL) and implemented in DTD, XSD and RNG. The result showed that RNG reduce complexity of class elements, reflect strong support for class elements to appear in any order which showed more reusability and flexibility traits and overall understanding of the schema documents becomes much easier because RNG can be algorithmically converted and partner with other schema languages therefore this reduces maintenance effort. Keywords— XML Schema Language, Schema Documents, Schema Metric