DCS SEMINAR SERIES
Rethinking Systems Thinking
Shayne Flint (DCS, ANU)
TIME: 16:00:00 - 17:00:00
LOCATION: CSIT Seminar Room, N101, Computer Science and Information Technology Building, Australian National University
Systems Thinking refers to a set of approaches that can be used to learn about and make decisions regarding improvements to dynamically complex systems. They are distinguished from other approaches by their focus on the whole and the study of interactions among the parts of a system, rather than the parts themselves. While focusing on interactions helps us understand complex systems and identify appropriate improvements, it is necessary to use detailed knowledge of the parts and other aspects of a system to implement any improvements.
This paper addresses this issue by introducing a novel Systems Thinking approach which uses detailed knowledge of the parts to both understand the whole, and to build the systems required to implement necessary improvements.
Shayne Flint is a Senior Lecturer at the Department of Computer Science, Australian National University, and is an active member of the department's Software-Intensive Systems Engineering group. Dr. Flint has broad industry experience and is the originator of Aspect-Oriented Thinking, a systematic approach to developing, managing and integrating the multi-disciplinary knowledge and expertise required to understand and improve complex systems.
From: Rethinking Systems Thinking, CECS Seminar List, ANU, 2008 (hypertext links added)
Australian Digital Theses Program
Title: Aspect-Oriented Thinking - An approach to bridging the disciplinary dividesAuthor: Flint, Shayne
Institution: The Australian National University
Engineering is often described as the application of scientific and technical knowledge to solve problems. In this thesis, I support a more general view that engineering should be treated as a continuous process of learning and action that aims to make well understood improvements within dynamically complex environments of co-evolving social, man-made and natural systems. I argue that this can only be achieved by adopting an approach that systematically develops, manages and integrates the knowledge and expertise of many disciplines to conceive, develop, modify, operate and retire systems. A novel implementation of such an approach, called Aspect-Oriented Thinking, is presented.
Aspect-Oriented Thinking begins with the development and verification of a set of domain Models. Each Domain Model represents knowledge about a separate, autonomous and possibly discipline specific concern or view within a given context. Domain models are developed by engineers, scientists, sociologists, psychologists, lawyers, philosophers, economists and others, using languages and techniques with which they are familiar. Knowledge captured in a set of Domain Models is then woven together, in accordance with a set of separately developed patterns and rules, to construct, modify, operate and retire systems, including models, hardware, software, processes and simulations. This is a continuous process which, in the first instance, involves those systems used to learn about a given context and to make decisions regarding required changes. Later, the process involves those systems used to implement and evaluate the impact of these decisions.
The significance of Aspect-Oriented Thinking lies in its broad applicability to any situation in which the expertise and knowledge of diverse disciplines is required to understand and make improvements within complex multifaceted environments such as those that involve sustainable development and national security.
A proof-of-concept within the context of software engineering is provided to demonstrate the mechanics and viability of Aspect-Oriented Thinking. The results of this demonstration are used to support an argument for future experimentation aimed at evaluating the effectiveness of Aspect-Oriented Thinking in a more general interdisciplinary environment.Aspect-Oriented Thinking - An approach to bridging the disciplinary divides, Australian Digital Theses Program, ANU