The theme of this thesis is to pave a path to vertically extract business intelligence (BI) from software code to business intelligence base, which is a tank of BI. Business intelligence is the atomic unit to build a piece of program comprehensibility in business logic point of view. It outstands because it covers all reverse engineering levels from code to specification. It refers to technologies for the localisation, extraction, analysis of business intelligence in software system. Such an approach naturally requires information transformation from software system to business intelligence base, and hence a novel set of automatic business intelligence recovery methods are needed. After a brief introduction of major issues covered by this thesis, the state of art of the area coined by the author as “business intelligence elicitation from software system”, in particular, the kinds of business intelligence that can be elicited from software system and their corresponding reverse engineering technical solutions are presented. Several new techniques are invented to pave the way towards realising this approach and make it light-weight. In particular, a programming-style-based method is proposed to partition a source program into business intelligence oriented program modules; concept recovery rules are defined to recover business intelligence concepts from the names embedded in a program module; formal concept analysis is built to model the recovered business intelligence and present business logic. The future research of this task is viewed as “automating business intelligence accumulation in Web” which is defined to bridge work in this thesis to nowadays Web computing trends. A prototype tool for recovering business intelligence from a Web-based mobile retailing system is then presented, followed by case study giving evaluation on the approach in different aspects. Finally, conclusions are drawn. Original contributions of this research work to the field of software reverse engineering are made explicit and future opportunities are explored.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:516054 |
| Date | January 2009 |
| Creators | Kang, Jian |
| Publisher | De Montfort University |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://hdl.handle.net/2086/2414 |
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