129 Copyright © 2010, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. Chapter 7 Knowledge Engineering Support for Software Requirements, Architectures and Components Muthu Ramachandran Leeds Metropolitan University, UK INTRODuCTION The term Artificial Intelligence (AI) was coined at Dartmouth in 1958 and nearly ten years later the term Software Engineering (SE) was coined at the same place in 1968. AI can be defined as “the study of how to make computers do things at which, at the moment, people are better” (AmI, 2008). Knowledge is gained from experience and highly related to all living things and Engineering is a human activity which aims to create, innovate, and produce a product. Therefore, there are com- mon activities amongst AI, KE & KBS (Knowledge Engineering and Knowledge Based Systems), ES (Expert Systems), KM (Knowledge Management), Neural Networks, Fuzzy Logics, and SE. All these activities aim to solve a complex problem and fol- low a similar pattern, viz: identify the problem, identify common patterns, look up a similar problem which has been solved in the past, and produce a conclusion, product and result. Widely used AI methods include: ABSTRACT The demands of SE imply a growing need for using AI to support all aspects of the software develop- ment process. This chapter provides insights into the application of knowledge based approaches to the development of agile software development, software product line, software components and architec- ture. In particular, it presents three research systems that demonstrate the potential benefts of utilising knowledge based approaches to support agile methods. The frst system, called SoBA, supports the use of a story card for agile software development; the second system, called .NET designer, provides design rationale for choosing appropriate architectural solutions, and the third system, called RAIS, provides reuse assessment and improvement for designing reusable software components. DOI: 10.4018/978-1-60566-758-4.ch007