Software Engineering-Basic Concepts

The Encyclopedia of Software Engineering defines formal methods in the following manner: Formal methods used in developing computer system...

The Encyclopedia of Software Engineering defines formal methods in the following manner:

Formal methods used in developing computer systems are mathematically based techniques for describing system properties. Such formal methods provide frameworks within which people can specify, develop, and verify systems in a systematic, rather than ad hoc manner.

A method is formal if it has a sound mathematical basis, typically given by a formal specification language. This basis provides a means of precisely defining notions like consistency and completeness, and more relevantly, specification, implementation and correctness.

The desired properties of a formal specification—consistency, completeness, and lack of ambiguity—are the objectives of all specification methods. However, the use of formal methods results in a much higher likelihood of achieving these ideals. The formal syntax of a specification language enables requirements or design to be interpreted in only one way, eliminating ambiguity that often occurs when a natural language (e.g., English) or a graphical notation must be interpreted by a reader. The descriptive facilities of set theory and logic notationenable clear statement of facts (requirements). To be consistent, facts stated in one place in a specification should not be contradicted in another place. Consistency is ensured by mathematically proving that initial facts can be formally mapped (using inference rules) into later statements within the specification.

Completeness is difficult to achieve, even when formal methods are used. Some aspects of a system may be left undefined as the specification is being created; other characteristics may be purposely omitted to allow designers some freedom in choosing an implementation approach; and finally, it is impossible to consider every operational scenario in a large, complex system. Things may simply be omitted by mistake.

Although the formalism provided by mathematics has an appeal to some software engineers, others (some would say, the majority) look askance at a mathematical view of software development. To understand why a formal approach has merit, we must first consider the deficiencies associated with less formal approaches.

Deficiencies of Less Formal Approaches

The methods discussed for analysis and design made heavy use of natural language and a variety of graphical notations. Although careful application of analysis and design methods, coupled with thorough review can and does lead to high-quality software, sloppiness in the application of these methods can create a variety of problems. A system specification can contain contradictions, ambiguities, vagueness, incomplete statements, and mixed levels of abstraction.

Contradictions are sets of statements that are at variance with each other. For example, one part of a system specification may state that the system must monitor all the temperatures in a chemical reactor while another part, perhaps written by another member of staff, may state that only temperatures occurring within a certain
range are to be monitored. Normally, contradictions that occur on the same page of a system specification can be detected easily. However, contradictions are often separated by a large number of pages.

Ambiguities are statements that can be interpreted in a number of ways. For example, the following statement is ambiguous:

The operator identity consists of the operator name and password; the password consists of six digits. It should be displayed on the security VDU and deposited in the login file when an operator logs into the system.

In this extract, does the word it refer to the password or the operator identity?

Vagueness often occurs because a system specification is a very bulky document. Achieving a high level of precision consistently is an almost impossible task. It can lead to statements such as “The interface to the system used by radar operators should be user-friendly” or “The virtual interface shall be based on simple overall concepts that are straightforward to understand and use and few in number.” A casual perusal of these statements might not detect the underlying lack of any useful information.

Incompleteness is probably one of the most frequently occurring problems with system specifications. For example, consider the functional requirement:

The system should maintain the hourly level of the reservoir from depth sensors situated in the reservoir. These values should be stored for the past six months. This describes the main data storage part of a system. If one of the commands for the system was

The function of the AVERAGE command is to display on a PC the average water level for a particular sensor between two times.

Assuming that no more detail was presented for this command, the details of the command would be seriously incomplete. For example, the description of the command does not include what should happen if a user of a system specifies a time that was more than six months before the current hour.

Mixed levels of abstraction occur when very abstract statements are intermixed randomly with statements that are at a much lower level of detail. For example, statements such as

The purpose of the system is to track the stock in a warehouse. 
might be intermixed with

When the loading clerk types in the withdraw command he or she will communicate the order number, the identity of the item to be removed, and the quantity removed. The system will respond with a confirmation that the removal is allowable.

While such statements are important in a system specification, specifiers often manage to intermix them to such an extent that it becomes very difficult to see the overall functional architecture of a system.

Each of these problems is more common than we would like to believe. And each represents a potential deficiency in conventional and object-oriented methods for specification.

Mathematics in Software Development

Mathematics has many useful properties for the developers of large systems. One of its most useful properties is that it is capable of succinctly and exactly describing a physical situation, an object, or the outcome of an action. Ideally, the software engineer should be in the same position as the applied mathematician. A mathematical specification of a system should be presented, and a solution developed in terms of a software architecture that implements the specification should be produced.

Another advantage of using mathematics in the software process is that it provides a smooth transition between software engineering activities. Not only functional specifications but also system designs can be expressed in mathematics, and of course, the program code is a mathematical notation—albeit a rather long-winded one.

The major property of mathematics is that it supports abstraction and is an excellent medium for modeling. Because it is an exact medium there is little possibility of ambiguity: Specifications can be mathematically validated for contradictions and incompleteness, and vagueness disappears completely. In addition, mathematics can be used to represent levels of abstraction in a system specification in an organized way.

Mathematics is an ideal tool for modeling. It enables the bare bones of a specification to be exhibited and helps the analyst and system specifier to validate a specification for functionality without intrusion of such issues as response time, design directives, implementation directives, and project constraints. It also helps the designer, because the system design specification exhibits the properties of a model, providing only sufficient details to enable the task in hand to be carried out.

Finally, mathematics provides a high level of validation when it is used as a software development medium. It is possible to use a mathematical proof to demonstrate that a design matches a specification and that some program code is a correct reflection of a design. This is preferable to current practice, where often little effort is put into early validation and where much of the checking of a software system occurs during system and acceptance testing.

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Software Engineering-Basic Concepts
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