Book•
Object-Oriented Analysis and Design with Applications
01 Jan 1990-
TL;DR: This chapter discusses the development of Object-Oriented Programming Languages and the Structure of Complex Systems, and the role of Classification in this development.
Abstract: I. CONCEPTS. 1. Complexity. The Inherent Complexity of Software. The Structure of Complex Systems. Bringing Order to Chaos. On Designing Complex Systems. Sidebar: Categories of Analysis and Design Methods. 2. The Object Model. The Evolution of the Object Model. Elements of the Object Model. Applying the Object Model. Sidebar: Foundations of the Object Model. 3. Classes and Objects. The Nature of an Object. Relationships Among Objects. The Nature of a Class. Relationships Among Classes. The Interplay of Classes and Objects. On Building Quality Classes and Objects. Sidebar: Invoking a Method. 4. Classification. The Importance of Proper Classification. Identifying Classes and Objects. Key Abstractions and Mechanisms. Sidebar: A Problem of Classification. II. THE METHOD. 5 .The Notation. Elements of the Notation. Class Diagrams. State Transition Diagrams. Object Diagrams. Interaction Diagrams. Module Diagrams. Process Diagrams. Applying the Notation. 6 .The Process. First Principles. The Micro Development Process. The Macro Development Process. 7. Pragmatics. Management and Planning. Staffing. Release Management. Reuse. Quality Assurance and Metrics. Documentation. Tools. Special Topics. The Benefits and Risks of Object-Oriented Development. III. APPLICATIONS. 8. Data Acquisition: Weather Monitoring Station. Analysis. Design. Evolution. Maintenance. Sidebar: Weather Monitorint Station Requirements. 9. Frameworks: Foundation Class Library. Analysis. Design. Evolution. Maintenance. Sidebar: Foundation Class Library Requirements. 10. Client/Server Computing: Inventory Tracking. Analysis. Design. Evolution. Maintenance. Sidebar: Inventory Tracking System Requirements. 11. Artificial Intelligence Cryptanalysis. Analysis. Design. Evolution. Maintenance. Sidebar: Cryptanalysis Requirements. 12. Command and Control Traffic Management. Analysis. Design. Evolution. Maintenance. Sidebar: Traffic Management System Requirements. Afterword. Appendix: Object-Oriented Programming Languages. A.1 Concepts. A.2 Smalltalk. A.3 Object Pascal. A.4 C++. A.5 Common Lisp Object System. A.6 Ada. A.7 Eiffel. A.8 Other Object-Oriented Programming Languages. Notes. Glossary. Classified Bibliography. A. Classification. B. Object-Oriented Analysis. C. Object-Oriented Applications. D. Object-Oriented Architectures. E. Object Oriented Databases. F. Object-Oriented Design. G. Object-Oriented Programming. H. Software Engineering. I. Special References. J. Theory. K. Tools and Environments. Index. 0805353402T04062001
Citations
More filters
University of Genoa1, University of Manchester2, KEK3, CERN4, Imperial College London5, Stanford University6, Tata Institute of Fundamental Research7, Istituto Nazionale di Fisica Nucleare8, University of Pittsburgh9, Lyon College10, TRIUMF11, Northeastern University12, Thomas Jefferson National Accelerator Facility13, University of Córdoba (Spain)14, Goethe University Frankfurt15, University of Southampton16, University of Udine17, University of Alberta18, Tokyo Metropolitan University19, Helsinki Institute of Physics20, National Research Nuclear University MEPhI21, University of Bath22, Niigata University23, Naruto University of Education24, Kobe University25, University of Calabria26, University of Trieste27, European Space Agency28, University of Birmingham29, Ritsumeikan University30, Qinetiq31, École Polytechnique Fédérale de Lausanne32, Massachusetts Institute of Technology33, Brookhaven National Laboratory34
01 Jul 2003-Nuclear Instruments & Methods in Physics Research Section A-accelerators Spectrometers Detectors and Associated Equipment
TL;DR: The Gelfant 4 toolkit as discussed by the authors is a toolkit for simulating the passage of particles through matter, including a complete range of functionality including tracking, geometry, physics models and hits.
Abstract: G eant 4 is a toolkit for simulating the passage of particles through matter. It includes a complete range of functionality including tracking, geometry, physics models and hits. The physics processes offered cover a comprehensive range, including electromagnetic, hadronic and optical processes, a large set of long-lived particles, materials and elements, over a wide energy range starting, in some cases, from 250 eV and extending in others to the TeV energy range. It has been designed and constructed to expose the physics models utilised, to handle complex geometries, and to enable its easy adaptation for optimal use in different sets of applications. The toolkit is the result of a worldwide collaboration of physicists and software engineers. It has been created exploiting software engineering and object-oriented technology and implemented in the C++ programming language. It has been used in applications in particle physics, nuclear physics, accelerator design, space engineering and medical physics.
18,904 citations
Journal Article•
6,559 citations
Cites background or methods from "Object-Oriented Analysis and Design..."
...We evaluated, for example, the Booch method [26], the OMT method [28], and...
[...]
...As discussed in the following sections, the lifecycle model adopted for most domains in Geant4 is both iterative and incremental (also called the spiral approach) [26]....
[...]
TL;DR: It will be argued that the development of robust and scalable software systems requires autonomous agents that can complete their objectives while situated in a dynamic and uncertain environment, that can engage in rich, high-level social interactions, and that can operate within flexible organisational structures.
1,606 citations
TL;DR: This article will argue that analyzing, designing, and implementing complex software systems as a collection of interacting, autonomous agents (that is, as a multiagent system) affords software engineers a number of significant advantages over contemporary methods.
Abstract: uilding high-quality, industrialstrength software is difficult. Indeed, it has been argued that developing such software in domains like telecommunications, industrial control, and business process management represents one of the most complex construction tasks humans undertake. Against this background, a wide range of software engineering paradigms have been devised. Each successive development either claims to make the engineering process easier or promises to extend the complexity of applications that can feasibly be built. Although evidence is emerging to support these claims, researchers continue to strive for more effective techniques. To this end, this article will argue that analyzing, designing, and implementing complex software systems as a collection of interacting, autonomous agents (that is, as a multiagent system [4]) affords software engineers a number of significant advantages over contemporary methods. This is not to say that agent-oriented software engineering represents a silver bullet [2]—there is no evidence to suggest it will represent an order of magnitude improvement in productivity. However, the increasing number of deployed applications [4, 8] bears testament to the potential advantages that accrue from such an approach. In seeking to demonstrate the efficacy of agent-oriented techniques, the most compelling argument would be to quantitatively show how their adoption improved the development process in a range of projects. However, such data is simply not available (as it is not for approaches like patterns, application frameworks, and componentware). Given this situation, the best that can be achieved is a qualitative justification of why agent-oriented approaches are well suited to engineering complex, distributed software systems.
1,295 citations