期刊名称：International Journal of Computer Science and Information Technologies
电子版ISSN：0975-9646
出版年度：2010
卷号：1
期号：5
页码：408-413
出版社：TechScience Publications
摘要：Data Mining for Software Engineering involves Architectural mining intelligence operations, which are knowledge gathering procedures. These intelligence operations go beyond basic data collection (assembling uncorrelated information) to the point of collecting fully assimilated practical knowledge – knowledge that affects important architectural decisions. Gathering knowledge is an essential element of being a software architect. Ordinary knowledge gathering for a project requires the capture of end user requirements and perhaps the evaluation of some commercial product. Proper architectural practices go well beyond these project centric traditions, which are isolationist when used exclusively. Instead, these practices should be augmented with some additional procedures that have been found to be effective, including architectural mining, architectural iteration, and architectural judgment. Architectural mining is a practice that breaches classic intelligence barriers between projects. IT can have an intelligence scope as large as entire industry or as small as one company’s systems. Architectural mining is a conscious effort to eliminate the ignorance of silence that characterizes many system developments. Architectural iteration is a process focused upon a single architecture or specification. It tracks the architecture through its development and life cycle, improving quality through intelligence gathering on each project. Architectural judgment is a process of decision making, based upon intelligence gathering. Making quality decisions is at the very heart of being an architect. In today’s changing world of technology, it is increasingly difficult to make long-lasting judgments without a systematic process. In this paper, we want to discuss about Architectural Mining (Design Pattern Mining) strategies for Software Security Architectures, which are validated with appropriate SAO Web Services case studies.
