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2006 | Buch

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Foundations and Applications of Mis

A Model Theory Approach

verfasst von: Yasuhiko Takahara, Yongmei Liu

herausgegeben von: George J. Klir

Verlag: Springer New York

Buchreihe : IFSR International Series in Systems Science and Systems Engineering

Enthalten in: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

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Über dieses Buch

Foundations and Applications of MIS presents a unique systems theory approach to management information system (MIS) development. The development is driven by the need to eliminate ambiguity in specification, design and construction of the application software. Further, the authors show that the considerable effort being expanded nowadays on validation, verification and testing, as required in current software engineering practices, will be reduced. The approach also reinforces the belief that MIS development is independent of software development.

The work presents an approach that provides a theoretical foundation for MIS development from the systems theoretic viewpoint along with practical applications ranging from a transaction processing system to a solver system. Both formal systems theory and automatic system generation based on the authors' newly extended Prolog offer a significant increase in the efficiency of specification, design and production of the application software, as well as an increase in the functional reliability of the software produced.

The book assumes a working knowledge of elementary set theory, logic, and familiarity with some systems concepts, such as the automaton model.

Inhaltsverzeichnis

Frontmatter

New Paradigm of Systems Development

Frontmatter

1. New Systems Development Methodology: The Model Theory Approach

Abstract

This chapter introduces the new systems development platform presented in this book. This new development methodology for management information systems (MISs) is based on a formal model-theoretic structure derived from the systems concepts of general systems theory (GST). The model is represented in set theory and implemented in a fourth-generation programming language, extProlog, by automated system generation. The extProlog language is an extension of standard Prolog that allows for the implementation of an MIS. As discussed in Section 1.2, the new methodology provides a platform for the development of both transaction processing systems and problemsolving systems as the two principal components of an MIS.

Model Construction Language and Systems Implementation Language

Frontmatter

2. Computer-Acceptable Set Theory for Model Construction

Abstract

To realize an information system by the model theory approach, a user model in set theory as introduced in Chapter 1 must be described in a form that can be accepted by a computer. For example, the symbol “∉” cannot be accepted by a computer, and must be replaced by an appropriate term, in this case “notmember”. The system-defined predicates and functions are used to describe the predicates and functions necessary for the user model with greatest efficiency. Set theory created in this way is described here as computer-acceptable set theory, and is the focus of this chapter.

3. Implementation Language: extProlog

Abstract

This chapter introduces extended Prolog (extProlog). Although primarily used as an implementation language for the model theory approach in a hidden manner similar to a machine language, knowledge of this language is also helpful for understanding the model theory approach, for the following reasons:

(1)

Input-output operations are provided by predicates of extProlog as well as HTML.

(2)

Advanced control schemes, such as those used in Chapter 13, are implemented with direct support of extProlog.

(3)

The standardized components of extSLV and TPS are implemented in extProlog.

(4)

An efficient user model can be directly constructed in extProlog if a system developer is familiar with extProlog.

Model Theory Approach to Solver Systems Development

Frontmatter

4. Model Theory Approach to Solver System Development: Outlines

Abstract

This chapter outlines the process of problem-solving system development by the model theory approach as a preliminary for Chapter 5. Specifically, development of extSLV is the target. A problem classification system is introduced for development. Throughout this book, extSLV development is carried out based on this classification scheme.

5. User Model and Standardized Goal-Seeker

Abstract

This chapter presents detailed explanations of the design stages of Fig. 4.6 and theoretical results from the user models and standardized goal-seekers featured in Fig. 4.5. The theoretical results can be omitted if readers are interested in practical aspects of the model theory approach. There are eight cases of user models according to the classification of Section 4.3. This chapter investigates two extreme cases: the E-C-C case and the I-O-O case. The other cases can be considered as combinations of these two extreme cases.

Solver System Applications

Frontmatter

6. Traveling Salesman Problem: E-C-C Problem

Abstract

This chapter examines the case E-C-C of the problem classification presented in Table 4.1. The famous traveling salesman problem is used as a typical example of the case. We develop extSLV for the problem following the development procedure of Chapter 4.

7. Regulation Problem: E-O-C Problem

Abstract

Chapters 7 and 8 discuss a control engineering problem. Control engineering problems are interesting for three reasons. First, although control is a type of management, because a target of control engineering is a continuous dynamic physical system, a control engineering problem is naturally different from a management problem. On the other hand, the methodology of this book has been developed and aimed at management problems. However, because it is based on the concepts of general systems theory (GST), it should be a general theory, which implies that our methodology must be applicable to control problems. It is interesting to see how our theory can work as a general theory in a field that is considered outside the scope of the original intention.

8. Linear Quadratic Optimization Problem: E-C-O and E-O-O Problems

Abstract

Chapter 7 introduced a simple dynamic system as a control engineering problem and investigated it as an E-O-C problem. This chapter formalizes an optimization problem for a general second-order dynamic system and examines it as an E-C-O problem. The goal is defined as a traditional quadratic problem. Because the goal of the optimization problem has parameters that can be modified by a user, the problem can also be considered as an E-O-O problem. This chapter introduces a constraint condition to investigate the significance of backtracking, which is the most basic characteristic for distinguishing the goal-seeker from conventional controllers.

9. Cube Root Problem: I-C-C Problem

Abstract

This chapter discusses a cube root problem as a simple case of an I-C-C problem. As shown below, an extended solver (extSLV) for this problem can be easily developed when the model theory approach is applied because the problem is simple. It is, however, puzzling to see that we cannot find a nontrivial problem for the case of I-C-C, although there are many tough problems for its neighboring cases of E-O-C, I-O-C, E-C-O, and I-C-O. For example, the regulation problem of Chapter 7, an E-O-C problem, can become a tough problem if the number of bodies, which must be controlled, increases. The magic square problem of I-O-C is quite difficult if its size becomes large. The conventional dynamic optimization problem, in Chapter 8 falls into the E-C-O class. The famous knapsack problem described in Chapter 10 is an I-C-O problem.

10. Knapsack Problem: I-C-O Problem

Abstract

This chapter discusses the well-known knapsack problem. This problem is another classical problem and is quoted as often in the problem-solving literature as the traveling salesman problem of Chapter 6. According to the problem classification of the model theory approach, the knapsack problem is more difficult than the traveling salesman problem because the former is less structured than the latter. Since the target state is not well specified except that it should be an optimal state, the stopping condition of the knapsack problem requires an involved expression to secure optimality.

11. Class Schedule Problem: I-O-C Problem

Abstract

This chapter discusses a class schedule problem as an I-O-C problem. The problem relates to the design of a class schedule for a college and includes assignment of instructors, subjects, and classrooms to slots of a weekly timetable. In order to simplify the problem, we will consider the class schedule for one grade of a specific department.

12. Data Mining Problem: I-O-O Problem

Abstract

This chapter discusses a data mining system as a nontrivial example of the model theory approach. Needless to say, the system has a special significance for the model theory approach due to its role in the intelligent management information system of Fig. 1.2. Because a data mining system is not usually considered as a problem-solving system, this trial may seem strange. This trial has three objectives. First, from a theoretical viewpoint, this trial demonstrates how the model theory approach is applicable to a more realistic system than a simple academic example. It is shown thatalthough a data mining problem is the least structured, the model theory approach is applicable to it in constructing a solver. Second, from a practical viewpoint, because the model theory approach is strong in exploration of the structure of a target system, good insight into a data mining system can be obtained throughout the trial. This is beneficial in practice because a data mining system has become crucial for sofisticated management. Third, this chapter shows how tuning of stage 6 of Fig. 4.6 can be performed using the insights. Because the goal-seeker of the model theory approach is developed on a general level, it is desirable in practice that a generated solver be tuned according to specific properties of the target.

13. Task Skeleton Model: Intelligent Data Mining System

Abstract

Because the problem classification of Chapter 4 is a general one, any problem can be covered by it. Furthermore, because the methodology of Chapters 4 and 5 is also general, in principle every problem can be attacked by it. It is obvious, however, that there are problems that cannot be solved by it in practical sense. Extension of the basic extSLV of Fig. 4.5 is necessary to address more difficult problems. In the model theory approach there are two ways for extension: introduction of a hierarchical multilevel system [Takahara and Liu, 2005] and extension to a task skeleton model. This chapter introduces the task skeleton model. An intelligent data mining system is developed as a demonstration of the model.

Model Theory Approach to Transaction Processing Systems Development

Frontmatter

14. Transaction Processing System on Browser-Based Standardized User Interface

Abstract

This chapter presents the model theory approach to development of a transaction processing system (TPS), which is the main target of current systems engineering. With this approach, the system developer constructs the specification for the target system based on the relational structure of the TPS (presented in Section 1.2). The specification is described in computer-acceptable set theory (introduced in Chapter 2) and then compiled into an executable TPS in extProlog. The system is executed under the control of a standardized user interface (UI) designed in PHP. The UI has been developed on several levels of sophistication. For the sake of simplicity, this chapter discusses TPS development using the simplest UI.

15. Browser-Based Intelligent Management Information System: Temporary Staff Recruitment System

Abstract

This chapter presents an example of systems development involving a combination of the methodologies for developing a transaction processing system and a solver system treated separately in previous chapters. The user model includes a solver-type atomic process as well as transaction-type processes. The target system is a temporary staff recruitment system (employment system) that must perform optimum matching between job-seeking applicants and job-offering clients as a typical problem-solving activity. The development leads to a browser-based intelligent management information system (MIS), which is a modification of Fig. 1.2 in Chapter 1.

16. Database Connectivity for the Model Theory Approach

Abstract

The target of the model theory approach is development of an intelligent MIS, as illustrated in Fig. 1.2 and in Fig. 15.2. The lower part of the system, a transaction processing system (TPS), constitutes the infrastructure of an MIS. Its main task is management of data. Although a simple file system is used for TPS development in Chapters 14 and 15, the model theory approach requires implementation of database connectivity because the file system is, in fact, supported by a database system. The language extProlog and hence the model theory approach are extended to implement that function.

Theoretical Basis for extProlog

Frontmatter

17. extProlog as Logic Programming Language

Abstract

This chapter presents the theoretical base of extProlog. It is discussed as a logic programming language. It would therefore be convenient to start with the definition of logic programming; however, there is no formal definition of a logic programming language. It is commonly understood that a logic programming language is one that has the ultimate goal of providing clarity and declarativeness for programming. In general, a programming activity consists of two parts: design of the algorithm (heuristic) and its implementation in a language. The algorithm part can be further decomposed into a logic aspect and a control aspect. The logic aspect refers to the facts or data and the rules and requirements specifying what the algorithm does. The control aspect refers to how the algorithm can be implemented by arranging the rules and requirements in a particular order. The latter aspect becomes serious when the algorithm is modified.

18. Implementation of extProlog

Abstract

An extProlog program is executed by the extProlog interpreter. This chapter discusses how the interpreter is designed for extProlog. Chapter 17 indicated that the main functions of a Prolog interpreter are unification and backtracking. A Prolog program is executed by these functions. Then, it is natural to guess that a generalization of a pushdown automaton (PDA) can be a model for the interpreter, where the push-down stack of a PDA can handle the backtracking while the head can perform unification, provided an appropriate Prolog database for matching is supplied [Takahara and Iijima, 1990]. The Prolog interpreter of this book is constructed as a generalized PDA with a Prolog database.

Backmatter

Titel: Foundations and Applications of Mis
verfasst von: Yasuhiko Takahara
Yongmei Liu
herausgegeben von: George J. Klir
Verlag: Springer New York
Electronic ISBN: 978-0-387-35840-6
Print ISBN: 978-0-387-31414-3
DOI: https://doi.org/10.1007/978-0-387-35840-6