How have Japanese companies become world leaders in the automotive and electronics industries, among others? What is the secret of their success? Two leading Japanese business experts, Ikujiro Nonaka and Hirotaka Takeuchi, are the first to tie the success of Japanese companies to their ability to create new knowledge and use it to produce successful products and technologies. In The Knowledge-Creating Company, Nonaka and Takeuchi provide an inside look at how Japanese companies go about creating this new knowledge organizationally. The authors point out that there are two types of knowledge: explicit knowledge, contained in manuals and procedures, and tacit knowledge, learned only by experience, and communicated only indirectly, through metaphor and analogy. U.S. managers focus on explicit knowledge. The Japanese, on the other hand, focus on tacit knowledge. And this, the authors argue, is the key to their success--the Japanese have learned how to transform tacit into explicit knowledge. To explain how this is done--and illuminate Japanese business practices as they do so--the authors range from Greek philosophy to Zen Buddhism, from classical economists to modern management gurus, illustrating the theory of organizational knowledge creation with case studies drawn from such firms as Honda, Canon, Matsushita, NEC, Nissan, 3M, GE, and even the U.S. Marines. For instance, using Matsushita's development of the Home Bakery (the world's first fully automated bread-baking machine for home use), they show how tacit knowledge can be converted to explicit knowledge: when the designers couldn't perfect the dough kneading mechanism, a software programmer apprenticed herself withthe master baker at Osaka International Hotel, gained a tacit understanding of kneading, and then conveyed this information to the engineers. In addition, the authors show that, to create knowledge, the best management style is neither top-down nor bottom-up, but rather what they call "middle-up-down," in which the middle managers form a bridge between the ideals of top management and the chaotic realities of the frontline. As we make the turn into the 21st century, a new society is emerging. Peter Drucker calls it the "knowledge society," one that is drastically different from the "industrial society," and one in which acquiring and applying knowledge will become key competitive factors. Nonaka and Takeuchi go a step further, arguing that creating knowledge will become the key to sustaining a competitive advantage in the future. Because the competitive environment and customer preferences changes constantly, knowledge perishes quickly. With The Knowledge-Creating Company, managers have at their fingertips years of insight from Japanese firms that reveal how to create knowledge continuously, and how to exploit it to make successful new products, services, and systems.

The knowledge-creating company

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

https://opus.lib.uts.edu.au/bitstream/10453/114834/4/OCC-90253_AM.pdf

A review of clustering techniques and developments

Studies have shown that good comments can help programmers quickly understand what a method does, aiding program comprehension and software maintenance. Unfortunately, few software projects adequately comment the code. One way to overcome the lack of human-written summary comments, and guard against obsolete comments, is to automatically generate them. In this paper, we present a novel technique to automatically generate descriptive summary comments for Java methods. Given the signature and body of a method, our automatic comment generator identifies the content for the summary and generates natural language text that summarizes the method's overall actions. According to programmers who judged our generated comments, the summaries are accurate, do not miss important content, and are reasonably concise.

Towards automatically generating summary comments for Java methods

Software engineering: theory and practice

Software engineering has been striving for years to improve the practice of software development and maintenance. Documentation has long been prominent on the list of recommended practices to improve development and help maintenance. Recently however, agile methods started to shake this view, arguing that the goal of the game is to produce software and that documentation is only useful as long as it helps to reach this goal.On the other hand, in the re-engineering field, people wish they could re-document useful legacy software so that they may continue maintain them or migrate them to new platform.In these two case, a crucial question arises: "How much documentation is enough?" In this article, we present the results of a survey of software maintainers to try to establish what documentation artifacts are the most useful to them.

A study of the documentation essential to software maintenance

Creating and maintaining software systems is a knowledge intensive task. One needs to have a good understanding of the application domain, the problem to solve and all its requirements, the software process used, technical details of the programming language(s), the system's architecture and how the different parts fit together, how the system interacts with its environment, etc. All this knowledge is difficult and costly to gather. It is also difficult to store and usually lives only in the mind of the software engineers who worked on a particular project. If this is a problem for development of new software, it is even more for maintenance, when one must rediscover lost information of an abstract nature from legacy source code among a swarm of unrelated details. In this paper, we submit that this lack of knowledge is one of the prominent problems in software maintenance. To try to solve this problem, we adapted a knowledge extraction technique to the knowledge needs specific to software maintenance. We explain how we explicit the knowledge discovered on a legacy software during maintenance so that it may be recorded for future use. Some applications on industry maintenance projects are reported.

Software maintenance seen as a knowledge management issue

Ontologies have been largely exploited in many domains and studies. In this paper, we present a new application of a domain ontology for generating personalized user interfaces for transportation interactive systems. The concepts, relationships and axioms of transportation ontology are exploited during the semi-automatic generation of personalized user interfaces. Personalization deals with the capacity of adaptation of a user interface, reflecting what is known about the user and the domain application. It can be performed on the interface container presentation (e.g., layout, colors, sizes) and in the content provided in their input/output (e.g., data, information, document). In this paper, the transportation ontology is used to provide the content personalization. This paper presents the ontology and how it is used for the personalization of user interfaces for developing transportation interactive systems by model-driven engineering.

Transportation ontology definition and application for the content personalization of user interfaces

Choose the best way to move from one place to another can involve different information: offers of different transport modes, their combination in the same journey and other information about services (such as restaurants, libraries, etc) that can be available in the route and useful for the passenger. Different approaches have been proposed to support the passenger's planning considering some part of this information. In this paper we present a public transportation domain ontology that considers different concepts related to the best and more relevant planning for the passenger. This ontology is formalized with OWL in Protege tool. Using real instances and inferences, we show the ontology application, its relevance and consistency.

A public transportation ontology to support user travel planning

Contemporary software systems, such as the Internet of Things (IoT), Industry 4.0, and Smart Cities are new technology paradigms that offer challenges for their construction since they are calling into question our traditional form of developing software. They are a promising paradigm for the integration of devices and communications technologies. It is leading to a shift from the classical monolithic view of development where stakeholder receive a software product at the end (that we have been doing for decades), to software systems materialized through physical objects interconnected by networks and with embedded software to support daily activities. We need therefore to revisit our way of developing software systems and start to consider the particularities required by these new sorts of applications. This paper presents research toward the definition of a framework to support the systems engineering of IoT applications, where we evolved the Zachman's Framework as an alternative to the organization of this architecture. The activities were two folded to address this goal: a) we identified leading concerns of IoT applications, recovered from technical literature, practitioners and a Government Report, in different studies; b) we structured the IoT paradigm in different facets. These activities provided 14 significant concerns and seven facets that together represent the engineering challenges to be faced both by research and practice towards the advancement of IoT in practice.

Káthia Marçal de Oliveira

Papers

A study of the documentation essential to software maintenance

Software maintenance seen as a knowledge management issue

Transportation ontology definition and application for the content personalization of user interfaces

A public transportation ontology to support user travel planning

On challenges in engineering IoT software systems