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In this thesis, two methods are developed in an aid to help users capture valuable design information and knowledge and reuse them. They are the design pattern recovery (DPR) method and pattern-based redocumentation (PBR) method. The DPR method is for matching up metrics of patterns with patterns themselves in order to capture valuable design information. Patterns are used as a container for storing the information. Two new metrics, i.e., p-value and s-value are introduced. They are obtained by analysing product metrics statistically. Once patterns have been detected from a system, the system can be redocumented using these patterns. Some existing XML (extensible Markup Language) technologies are utilised in order to realise the PRB method. Next, a case study is carried out to validate the soundness and usefulness of the DPR method. Finally, some conclusions drawn from this research are summarised, and further work is suggested for the researchers in software engineering.

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In this thesis an introduction to simulation and object oriented programming discusses the need for the creation of several classes which directly support object oriented simulation. The author places no restrictions on the type of simulations that can be conducted and simulation practitioners will find that the classes provided lay the groundwork for a robust object oriented simulation language. In order to appreciate the development of the simulation classes, three examples from the literature demonstrate their use in continuous deterministic and discrete stochastic simulations. In addition to the creation of several basic simulation constructs, two advanced simulation tools were developed. Inter-object communication and intelligent simulation capabilities will increase the power and flexibility available to simulation modeler's. Programmers, scientists, and engineers will appreciate the object oriented simulation engine and generic simulation objects that were created. / Graduation date: 1993

Thesis (M.Sc.)--York University, 2007. Graduate Programme in Computer Science. / Typescript. Includes bibliographical references (leaves 153-157). Also available on the Internet. MODE OF ACCESS via web browser by entering the following URL: http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&res_dat=xri:pqdiss&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&rft_dat=xri:pqdiss:MR38783

Thesis (Ph. D.)--Lehigh University, 2001. / Includes vita. Includes bibliographical references (leaves 127-129).

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No description available.

Software can be considered a live entity, as it undergoes many alterations throughout its lifecycle. Therefore, code can become rather complex and difficult to understand. More specifically in object-oriented systems, classes may become very large and less cohesive. In order to identify such problematic cases, existing approaches have proposed the use of cohesion metrics. While metrics can identify classes with low cohesion, they usually cannot identify new or independent concepts. In this work, we propose a class decomposition method using an clustering algorithm based on the Jaccard distance between class members. The methodology is able to identify new concepts and rank the solutions according to their impact on the design quality of the system. The methodology was evaluated in terms of assessment by designers, expert assessment and metrics. The evaluation showed the ability of the method to identify new recognizable concepts and improve the design quality of the underlying system.

Thesis (M.S. in Computer Science) Naval Postgraduate School, March 1992. / Thesis Advisor: Wu, C. Thomas. "March 1992." Includes bibliographical references (p. 83-85). Also available in print.