The problem area addressed in this thesis is extraction of a data design from existing data intensive program code. The purpose of this is to help a software maintainer to understand a software system more easily because a view of a software system at a high abstraction level can be obtained. Acquiring a data design from existing data intensive program code is an important part of reverse engineering in software maintenance. A large proportion of software systems currently needing maintenance is data intensive. The research results in this thesis can be directly used in a reverse engineering tool. A method has been developed for acquiring data designs from existing data intensive programs, COBOL programs in particular. Program transformation is used as the main tool. Abstraction techniques and the method of crossing levels of abstraction are also studied for acquiring data designs. A prototype system has been implemented based on the method developed. This involved implementing a number of program transformations for data abstraction, and thus contributing to the production of a tool. Several case studies, including one case study using a real program with 7000 Hues of source code, are presented. The experiment results show that the Entity-Relationship Attribute Diagrams derived from the prototype can represent the data designs of the original data intensive programs. The original contribution of the thesis is that the approach presented in this thesis can identify and extract data relationships from the existing code by combining analysis of data with analysis of code. The approach is believed to be able to provide better capabilities than other work in the field. The method has indicated that acquiring a data design from existing data intensive program code by program transformation with human assistance is an effective method in software maintenance. Future work is suggested at the end of the thesis including extending the method to build an industrial strength tool.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:241622 |
| Date | January 1994 |
| Creators | Yang, Hongji |
| Publisher | Durham University |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://etheses.dur.ac.uk/5161/ |
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