Research on business knowledge extraction from existing software systems

Kęstutis Normantas

Doctoral dissertation

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The dissertation addresses the problem of software maintenance and evolution. It identifies that spending within these software lifecycle phases may account for up to 80% of software’s total lifecycle cost, whereas the inability to adopt software quickly and reliably to meet ever-changing business requirements may lead to business opportunities being lost. The main reason of this phenomenon is the fact that the most of maintenance effort is devoted to understanding the software to be modified. On the other hand, related studies show that less than one-third of software source code contains business logic implemented within it, while the remaining part is intended for platform or infrastructure relevant activities. It follows that if the most of changes in software are made due to the need to adopt its functionality to changed business requirements, then facilitating software comprehension with automated business knowledge extraction methods may significantly reduce the cost of software maintenance and evolution. Therefore the main goal of this thesis is to improve business knowledge extraction process by proposing a method and supporting tool framework that would facilitate comprehension of existing software systems.

The dissertation consists of the following parts: Introduction, 4 chapters, General Conclusions, References, and 6 Annexes.

Chapter 1 presents a systematic literature review of related studies in order to summarize the state-of-the art in this research field, identify any gaps in the current research and explore possible directions for the further research. Chapter 2 formulates theoretical background for the business knowledge extraction method by introducing selected standard for the intermediate knowledge representation, defining well-formedness rules for this representation, and by revising and applying static program analysis techniques to this representation. Chapter 3 describes the proposed method for automated business knowledge extraction from existing software systems and introduces the supporting tools framework. Chapter 4 presents the case study on applying the method for knowledge extraction from the existing enterprise content management system, and evaluates study results in respect with the precision, recall, and accuracy measures. The evaluation shows that the proposed method is feasible and efficient enough to be further improved and applied in practice. The main observations are summarised and concluded within the General Conclusions chapter.

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145×205 mm
162 p.
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