Applying AI to Software Renovation
Automated Software Engineering
Ontology Management in Enterprises
BT Technology Journal
Wrapper-based evolution of legacy information systems
ACM Transactions on Software Engineering and Methodology (TOSEM)
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We describe a solution to the acquisition of entity relationship attribute (ERA) diagrams from data-intensive source code. In such programs, relationships between data items are often represented within imperative code, as well as within data structures, and we show that reverse engineering can be improved if both are used. This distinguishes our work from others in the field. Our method is based on formal transformations. We identify imperative constructs which improve the high-level ERA models that it is possible to capture. Suitable transformations are then briefly summarised. A series of experiments with industrial COBOL programs is described. Our results show that code-embedded relations can usefully be incorporated into data intensive reverse engineering, and enhance the designs extracted.