Software Engineering Learn Karanna Kamati Ayata..Systems Analysis and Design

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2.7.11

  • This Tutorial Create By Our Lecturer Mr:S.P.K. Ranatunga/ Sabaragamuwa University of Sri Lanka/Software Engineering/Systems Analysis and Design/If U Using This Any Other  Reason Plz Ask Me.071-3012797
Systems Analysis and Design - Lecture Note 01

INTRODUCTION TO SYSTEMS-
In this topic, the material highlights a number of concepts of systems, the workload and reasons behind the workload in a system's life cycle. In this part, you'll get to know the techniques applied in studying survey methods, topic discussions, specification of systems' requirement and analysis skills. After reading this part, you'll gain more experience in dealing with systems issues which managers, users of different levels, and technicians, consider through different views


Definition of System-
There are many common types of systems that we come into contact with every day. It is important to be familiar with different kinds of systems for at least two reasons:
First, even though your work as a systems analyst will probably focus on one kind of system – an automated, computerized information system – it will generally be a part of a larger system. For example, you may be working on a payroll system, which is part of a larger “human resources” system, which is, in turn, part of an overall business organization (which is itself, a system), which is, in turn, part of all larger economic system, and so on. Thus, to make your system successful, you must understand the other systems with which it will interact. Many of the computer systems that we build are replacements, or new implementations of, non-computerized systems that are already in existence. Also, most computer systems interact with, or interface with, a variety of existing systems (some of which may be computerized and some which may not). If our new computer system is to be successful, we must understand, in reasonable detail, how the current system behaves.
Second, even though many types of systems appear to be quite different, they turn out to have many similarities. There are common principles and philosophies and theories that apply remarkably well to virtually all kinds of systems. Thus, we can often apply to systems that we build in the computer field, what we have learned about other systems, based on our own day-to-day experience, as well as the experience of scientists and engineers in a variety of fields.
Thus, if we understand something of general systems theory, it can help us better understand computerized (automated) information systems. Today, this is more and more important, because we want to build stable, reliable systems that will function well in our complex society, and of course, there are many examples of non-computer systems that have survived for thousands of years.
And now, we can consider a definition of the basic term "system". It provides several definitions:
  • A regularly interacting or interdependent group of items forming a unified whole.
  • An organized set of doctrines, ideas, or principles, usually intended to explain the arrangements or working of a systematic whole.
  • An organized or established procedure.
  • Harmonious arrangement or pattern: order.
  • An organized society or social situation regarded as stultifying establishment.
Common types of systems-
There are many different types of systems, but indeed, virtually everything that we come into contact with during our day-to-day life is either a system or a component of a system (both).
It is useful to organize the many different kinds of systems into useful categories. Because our ultimate focus is on computer systems, we will divide all systems into two categories: natural systems and man-made systems.

Natural systems
There are a lot of systems that are not made by people: they exist in nature and, by and large, serve their own purpose. It is convenient to divide natural systems into two basic subcategories: physical systems and living systems.
Physical systems include such diverse example as:
Stellar systems: galaxies, solar systems, and so on.
Geological systems: rivers, mountain ranges, and so on.
Molecular systems: complex organizations of atoms.

Keep in mind that many man-made systems (and automated systems) interact with living systems. In some cases, automated systems are being designed to replace living systems. And in other cases, researchers are considering living systems as components of automated systems.

Man-made system-
Man-made systems include such things as:
  • Social systems: organizations of laws, doctrines, customs, and so on.
  • An organized, disciplined collection of ideas.
  • Transportation systems: networks of highways, canals, airlines and so on.
  • Communication systems: telephone, telex, and so on.
  • Manufacturing systems: factories, assembly lines, and so on.
  • Financial systems: accounting, inventory, general ledger and so on.
Most of these systems include computers today. As a systems analyst, you will naturally assume that every system that you come in contact with should be computerized. And the customer or user, with whom you interact will generally assume that you have such a bias. A systems analyst will analyze, or study, the system to determine its essence: and understand the system's required behavior, independent of the technology used to implement the system. In most case, we will be in a position to determine whether it makes sense to use a computer to carry out the functions of the system only after modeling its essential behavior.
Some information processing systems may not be automated because of these common reasons: Cost; Convenience; Security; Maintainability; Politics.

Automated systems.
Automated systems are the man-made systems that interact with or are controlled by one or more computers. We can distinguish many different kinds of automated systems, but they all tend to have common components:
  • Computer hardware (CPUs, disks, terminals, and so on).
  • Computer software: system programs such as operating systems, database systems, and so on.
  • People: those who operate the system, those who provide its inputs and consume its outputs, and those who provide manual processing activities in a system.
  • Data: the information that the system remembers over a period of time.
  • Procedures: formal policies and instructions for operating the system.
A more useful categorization of automated systems is as follows:
1.   Batch system: A batch system is one which in it, the information is usually retrieved on a sequential basis, which means that the computer system read through all the records in its database, processing and updating those records for which there is some activity.
2.   On-line systems: An on-line system is one, which accepts input directly from the area where it is created. It is also a system in which the outputs, or results of computation, are returned directly to where they are required.
3.   Real-time systems: A real-time system may be defined as one which controls an environment by receiving data, processing them, and returning the results sufficiently quickly to affect the environment at that time.
4.   Decision-support systems: These computer systems do not make decisions on their own, but instead help managers and other professional “knowledge workers” in an organization make intelligent, informed decisions about various aspects of the operation. Typically, the decision-support systems are passive in the sense that they do not operate on a regular basis: instead, they are used on an ad hoc basis, whenever needed.
5.   Knowledge-based systems: The goal of computer scientists working in the field of artificial intelligence is to produce programs that imitate human performance in a wide variety of “intelligent” tasks. For some expert systems, that goal is close to being attained. For others, although we do not yet know how to construct programs that perform well on their own, we can begin to build programs that significantly assist people in their performance of a task.


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Copyright By: Sabaragamuwa University of SrLanka/Software Engineering 2010- 2011
Lecturer Mr:S.P.K. Ranatunga

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