A Structured Approach to Data Reverse Engineering of Web Applications

The majority of documents on the Web are written in HTML, constituting a huge amount of legacy data: all documents are formatted for visual purposes only and with different styles due to diverse authorships and goals and this makes the process of retrieval and integration of Web contents difficult to automate. We provide a contribution to the solution of this problem by proposing a structured approach to data reverse engineering of data-intensive Web sites. We focus on data content and on the way in which such content is structured on the Web. We profitably use a Web data model to describe abstract structural features of HTML pages and propose a method for the segmentation of HTML documents in special blocks grouping semantically related Web objects. We have developed a tool based on this method that supports the identification of structure, function, and meaning of data organized in Web object blocks. We demonstrate with this tool the feasibility and effectiveness of our approach over a set of real Web sites.

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