Creating R Packages: A Tutorial

This tutorial gives a practical introduction to creating R packages. We discuss how object oriented programming and S formulas can be used to give R code the usual look and feel, how to start a package from a collection of R functions, and how to test the code once the package has been created. As running example we use functions for standard linear regression analysis which are developed from scratch

Component technologies: Java Beans, COM, CORBA, RMI, EJB and the CORBA component model

This one-day tutorial is aimed at software engineering practitioners and researchers, who are familiar with objectoriented analysis, design and programming and want to obtain an overview of the technologies that are enabling component-based development. We introduce the idea of component-based development by defining the concept and providing its economic rationale. We describe how object-oriented programming evolved into local component models, such as Java Beans and distributed object technologies, such as the Common Object Request Broker Architecture (CORBA), Java Remote Method Invocation (RMI) and the Component Object Model (COM). We then address how these technologies matured into distributed component models, in partiuclar Enterprise Java Beans (EJB) and the CORBA Component Model (CCM). We give an assessment of the maturity of each of these technologies and sketch how they are used to build distributed architectures

Static Adaptations Of Personalization Factors Included In The Development Of An Adaptive Web-Based Tutorial

The present research divides the adaptation process into dynamic and static adaptations. The present paper introduces the static adaptations of personalization factors included in the development of an Adaptive Web-based Tutorial system. The included personalization factors are: Learning styles, intelligence types, knowledge background, special interests, learning goals and beliefs. The personalization factors were determined in order to improve the teaching-learning process of Object-Oriented Programming Languages.The present research divides the adaptation process into dynamic and static adaptations. The present paper introduces the static adaptations of personalization factors included in the development of an Adaptive Web-based Tutorial system. The included personalization factors are: Learning styles, intelligence types, knowledge background, special interests, learning goals and beliefs. The personalization factors were determined in order to improve the teaching-learning process of Object-Oriented Programming Languages

Static Adaptations Of Personalization Factors Included In The Development Of An Adaptive Web-Based Tutorial

The present research divides the adaptation process into dynamic and static adaptations. The present paper introduces the static adaptations of personalization factors included in the development of an Adaptive Web-based Tutorial system. The included personalization factors are: Learning styles, intelligence types, knowledge background, special interests, learning goals and beliefs. The personalization factors were determined in order to improve the teaching-learning process of Object-Oriented Programming Languages.The present research divides the adaptation process into dynamic and static adaptations. The present paper introduces the static adaptations of personalization factors included in the development of an Adaptive Web-based Tutorial system. The included personalization factors are: Learning styles, intelligence types, knowledge background, special interests, learning goals and beliefs. The personalization factors were determined in order to improve the teaching-learning process of Object-Oriented Programming Languages

XML and Web Services for Astronomers

This tutorial will be a conceptual introduction to XML technologies and their use in Web services, with examples and applications taken from astronomy. It will be assumed that the audience is familiar with HTML as well as concepts of object-oriented programming. The programming examples will use Java, although this will be a small part of the total material. Upon completing this tutorial, the student should be able to read and write XML documents, create XML Schemas and XSL Transformations, programmatically consume and create XML documents, and build a simple Web service

Tutorial on Lisp Object- Oriented Programming for Blackboard Computation (Solving the Radar Tracking Problem)

This exposition is a tutorial on how object-oriented programming in Lisp can be used for programming a blackboard. Since we have used Franz Lisp and since object oriented programming in Franz is carried out via flavors, the exposition demonstrates how flavors can be used for this purpose. The reader should note that the different approaches to object-oriented programming share considerable similarity and, therefore, the exposition should be helpful to even those who may not wish to use flavors. We have used the radar tracking problem as a ‘medium’ for explaining the concepts underlying blackboard programming. The blackboard database is constructed solely of flavors which act as data structures as well as method-bearing objects. Flavor instances form the nodes and the levels of the blackboard. The methods associated with these flavors constitute a distributed monitor and support the knowledge sources in modifying the blackboard data. A rule-based planner is used to construct knowledge source activation records from the goals residing in the blackboard. These activation records are enqueued in a cyclic queueing system. A scheduler cycles through the queues and selects knowledge sources to fir

A TUTORIAL ON LISP OBJECT-ORIENTED PROGRAMMING FOR BLACKBOARD COMPUTATION (SOLVING THE RADAR TRACKING PROBLEM)

This exposition is a tutorial on how object-oriented programming (OOP) in Lisp can be used for programming a blackboard. Since we have used Common Lisp and the Common Lisp Object System (CLOS), the exposition demonstrates how object classes and the primary, before, and after methods associated with the classes can be used for this purpose. The reader should note that the different approaches to object-oriented programming share considerable similarity and, therefore, the exposition should be helpful to even those who may not wish to use CLOS. We have used the radar tracking problem as a \u27medium\u27 for explaining the concepts underlying blackboard programming. The blackboard database is constructed solely of classes which act as data structures as well as method-bearing objects. Class instances fonn the nodes and the levels of the blackboard. The methods associated with these classes constitute a distributed monitor and support the knowledge sources in modifying the blackboard data. A rule-based planner is used to construct knowledge source activation records from the goals residing in the blackboard. These activation records are enqueued in a cyclic queueing system. A scheduler cycles through the queues and selects knowledge sources to fire

Logic programming in the context of multiparadigm programming: the Oz experience

Oz is a multiparadigm language that supports logic programming as one of its major paradigms. A multiparadigm language is designed to support different programming paradigms (logic, functional, constraint, object-oriented, sequential, concurrent, etc.) with equal ease. This article has two goals: to give a tutorial of logic programming in Oz and to show how logic programming fits naturally into the wider context of multiparadigm programming. Our experience shows that there are two classes of problems, which we call algorithmic and search problems, for which logic programming can help formulate practical solutions. Algorithmic problems have known efficient algorithms. Search problems do not have known efficient algorithms but can be solved with search. The Oz support for logic programming targets these two problem classes specifically, using the concepts needed for each. This is in contrast to the Prolog approach, which targets both classes with one set of concepts, which results in less than optimal support for each class. To explain the essential difference between algorithmic and search programs, we define the Oz execution model. This model subsumes both concurrent logic programming (committed-choice-style) and search-based logic programming (Prolog-style). Instead of Horn clause syntax, Oz has a simple, fully compositional, higher-order syntax that accommodates the abilities of the language. We conclude with lessons learned from this work, a brief history of Oz, and many entry points into the Oz literature.Comment: 48 pages, to appear in the journal "Theory and Practice of Logic Programming

Objects and Types: A Tutorial

This paper is a tutorial explaining the concepts that surround abstract data types and object-oriented programming, and the relationships between these groups of concepts. These concepts include types (languagedefied, user-defied, abstract), instantiations, differences between operations and functions, overloading, objects, state, inheritance and, messages. Some of the these trems, e.g. "type", have been well defied. Many others are used in seveml contexts with multiple meanings. This paper is an attempt to identify consistent and meaningful definitions which are the most widely accepted

Component technologies: Java Beans, COM, CORBA, RMI, EJB and the CORBA component model

This one-day tutorial is aimed at software engineering practitioners and researchers, who are familiar with objectoriented analysis, design and programming and want to obtain an overview of the technologies that are enabling component-based development. We introduce the idea of component-based development by dening the concept and providing its economic rationale. We describe how objectoriented programming evolved into local component models, such as Java Beans and distributed object technologies, such as the Common Object Request Broker Architecture (CORBA), Java Remote Method Invocation (RMI) and the Component Object Model (COM). We then address how these technologies matured into distributed component models, in partiuclar Enterprise Java Beans (EJB) and the CORBA Component Model (CCM). We give an assessment of the maturity of each of these technologies and sketch how they are used to build distributed architectures