How has Japan become a major economic power, a world leader in the automotive and electronics industries? What is the secret of their success? The consensus has been that, though the Japanese are not particularly innovative, they are exceptionally skilful at imitation, at improving products that already exist. But now two leading Japanese business experts, Ikujiro Nonaka and Hiro Takeuchi, turn this conventional wisdom on its head: Japanese firms are successful, they contend, precisely because they are innovative, because they create new knowledge and use it to produce successful products and technologies. Examining case studies drawn from such firms as Honda, Canon, Matsushita, NEC, 3M, GE, and the U.S. Marines, this book reveals how Japanese companies translate tacit to explicit knowledge and use it to produce new processes, products, and services.

The knowledge-creating company : how Japanese companies create the dynamics of innovation

In 1974 an article appeared in Science magazine with the dry-sounding title “Judgment Under Uncertainty: Heuristics and Biases” by a pair of psychologists who were not well known outside their discipline of decision theory. In it Amos Tversky and Daniel Kahneman introduced the world to Prospect Theory, which mapped out how humans actually behave when faced with decisions about gains and losses, in contrast to how economists assumed that people behave. Prospect Theory turned Economics on its head by demonstrating through a series of ingenious experiments that people are much more concerned with losses than they are with gains, and that framing a choice from one perspective or the other will result in decisions that are exactly the opposite of each other, even if the outcomes are monetarily the same. Prospect Theory led cognitive psychology in a new direction that began to uncover other human biases in thinking that are probably not learned but are part of our brain’s wiring.

Thinking fast and slow.

The Object Management Group's (OMG) Model Driven Architecture (MDA) strategy envisages a world where models play a more direct role in software production, being amenable to manipulation and transformation by machine. Model Driven Engineering (MDE) is wider in scope than MDA. MDE combines process and analysis with architecture. This article sets out a framework for model driven engineering, which can be used as a point of reference for activity in this area. It proposes an organisation of the modelling 'space' and how to locate models in that space. It discusses different kinds of mappings between models. It explains why process and architecture are tightly connected. It discusses the importance and nature of tools. It identifies the need for defining families of languages and transformations, and for developing techniques for generating/configuring tools from such definitions. It concludes with a call to align metamodelling with formal language engineering techniques.

Model Driven Engineering

Will Tracz, our esteemed editor and Used-Program salesman, has written an entertaining, non-technical book dealing with the practice (and lack of) of software reuse. Its a collection of essays, mostly rehashed (reused?) and updated from various columns and papers published over the years.. Its a short (a bit over 200 pages) easy reading and enjoyable book (I read most of it in one sitting). Some of the essays discuss what was printed in the past and a discussion of the current status of the points.

Safeware: System Safety and Computers

Blink: The Power of Thinking without Thinking / Strangers to Ourselves: Discovering the Adaptive Unconscious

Many times we are faced with the proliferation of definitions, concepts, languages, and tools in certain (research) topics. But often there is a gap between what is provided by existing technologies and what is needed by their users. The strengths, limitations, and needs of the available technologies can be dubious. The same applies to software architectures, and specifically to languages designed to represent architectural models. Tens of different architectural languages have been introduced by the research and industrial communities in the last two decades. However, it is unclear if they fulfill the user's perceived needs in architectural description. As a way to plan for next generation languages for architectural description, this study analyzes practitioners' perceived strengths, limitations, and needs associated with existing languages for software architecture modeling in industry. We run a survey by interviewing 48 practitioners from 40 different IT companies in 15 countries. Each participant is asked to fill in a questionnaire of 51 questions. By analyzing the data collected through this study, we have concluded that 1) while practitioners are generally satisfied with the design capabilities provided by the languages they use, they are dissatisfied with the architectural language analysis features and their abilities to define extra-functional properties; 2) architectural languages used in practice mostly originate from industrial development instead of from academic research; 3) more formality and better usability are required of an architectural language.

http://www.ivanomalavolta.com/files/papers/TSE_2013.pdf

What Industry Needs from Architectural Languages: A Survey

A rationale-based architecture model for design traceability and reasoning

https://www.ics.uci.edu/~andre/ics223w2006/tangalibabargortonhan.pdf

A survey of architecture design rationale

https://ulir.ul.ie/bitstream/handle/10344/2101/2009_tang.pdf?sequence=2

A comparative study of architecture knowledge management tools

Architecture frameworks are methods used in architecture modeling. They provide a structured and systematic approach to designing systems. To date there has been little analysis on their roles in system and software engineering and if they are satisfactory. This study provides a model of understanding through analyzing the goals, inputs and outcomes of six architecture frameworks. It characterizes two classes of architecture frameworks and identifies some of their deficiencies. To overcome these deficiencies, we propose to use costs, benefits and risks for architecture analysis. We also propose a method to delineate architecture activities from detailed design activities.

https://researchbank.swinburne.edu.au/file/d91d160c-58d5-44b3-b4ff-1973d95d36df/1/PDF (Published version).pdf

Antony Tang

Papers

What Industry Needs from Architectural Languages: A Survey

A rationale-based architecture model for design traceability and reasoning

A survey of architecture design rationale

A comparative study of architecture knowledge management tools

A comparative analysis of architecture frameworks