专题演讲嘉宾:Rick Kazman

Hawaii UniversityProfessor, Visiting Scientist at SEI/CMU, Chair IEEE Technical Activities Committee

I am Chair of the IEEE Technical Activities Committee and past Chair of the Technical Council on Software Engineering (TCSE), Professor at the University of Hawaii and a Visiting Scientist at the Software Engineering Institute of Carnegie Mellon University. My primary research interests are software architecture, design and analysis tools, software visualization, and software engineering economics. I have created several highly influential methods and tools for architecture analysis, including the SAAM (Software Architecture Analysis Method), the ATAM (Architecture Tradeoff Analysis Method), the CBAM (Cost-Benefit Analysis Method) and the Dali and Titan tools. 

I have authored over 200 publications, and co-authored several books, including Software Architecture in Practice, Designing Software Architectures.

Rick Kazman 是夏威夷大学的教授,也是卡耐基梅隆大学软件工程研究所的客座研究员。他的主要研究方向是软件架构、设计和分析工具、软件可视化和软件工程经济学。Kazman 参与创建了多个极具影响力的架构分析方法和工具,包括 ATAM(架构权衡分析法)、CBAM(成本效益分析法)以及 Dali 和 Titan 工具。他发表了200多篇论文,合著了3项专利和8本著作,包括《Technical Debt: How to Find It and Fix It》《Designing Software Architectures: A Practical Approach》《Evaluating Software Architectures: Methods and Case Studies》等。根据 Google Scholar 的数据,他的研究已被引用超过24,000次。他目前是 IEEE TAC(技术活动委员会)主席、IEEE 软件工程交易会副编辑和 ICSE 指导委员会成员。

by Rick Kazman

Hawaii University
Professor, Visiting Scientist at SEI/CMU, Chair IEEE Technical Activities Committee

As software-intensive systems continue to grow in scale and complexity the principles that we have used to design them in the past no longer suffice. In this talk we look at examples of ultra-large-scale systems—systems of unprecedented size and complexity. We examine examples of such systems that have arisen spontaneously in nature and those that have been human-constructed. We distill from these example systems the design primitives that underlie them. We capture these design primitives as a set of tactics—architectural building-blocks—and argue that to efficiently build and analyze such systems in the future we must employ such building-blocks.

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