At the end of this lesson the student will be able to:
- ·
Identify the scope
and necessity of software engineering.
- ·
Identify the causes of and solutions for software crisis.
- · Differentiate a piece of program from a software product.
Scope and necessity of software engineering
Software engineering is an engineering approach for software development. We can alternatively view it as a systematic collection of past experience. The experience is arranged in the form of methodologies and guidelines. A small program can be written without using software engineering principles. But if one wants to develop a large software product, then software engineering principles are indispensable to achieve a good quality software cost effectively. These definitions can be elaborated with the help of a building construction analogy.
Suppose you have a friend who asked you to build a small wall as shown in fig.
1.1. You would be able to do that using your common sense. You will get building materials like bricks; cement etc. and you will then build the wall.
Fig. 1.1: A Small Wall
But what would happen if the same friend asked you to build a large multistoried building as shown in fig. 1.2?
Fig. 1.2: A Multistoried Building
You don't have a very good idea about building such a huge complex. It would be very difficult to extend your idea about a small wall construction into constructing a large building. Even if you tried to build a large building, it would collapse because you would not have the requisite knowledge about the strength of materials, testing, planning, architectural design, etc. Building a small wall and building a large building are entirely different ball games. You can use your intuition and still be successful in building a small wall, but building a large building requires knowledge of civil, architectural and other engineering principles.
Without using software engineering principles it would be difficult to develop large programs. In industry it is usually needed to develop large programs to accommodate multiple functions. A problem with developing such large commercial programs is that the complexity and difficulty levels of the programs increase exponentially with their sizes as shown in fig. 1.3. For example, a program of size 1,000 lines of code has some complexity. But a program with
10,000 LOC is not just 10 times more difficult to develop, but may as well turn out to be 100 times more difficult unless software engineering principles are used. In such situations software engineering techniques come to rescue. Software engineering helps to reduce the programming complexity. Software engineering principles use two important techniques to reduce problem complexity: abstraction and decomposition.
Fig. 1.3: Increase in development time and effort with problem size
The principle of abstraction (in fig.1.4) implies that a problem can be simplified by omitting irrelevant details. In other words, the main purpose of abstraction is to consider only those aspects of the problem that are relevant for certain purpose and suppress other aspects that are not relevant for the given purpose. Once the simpler problem is solved, then the omitted details can be taken into consideration to solve the next lower level abstraction, and so on. Abstraction is a powerful way of reducing the complexity of the problem.
The other approach to tackle problem complexity is decomposition. In this technique, a complex problem is divided into several smaller problems and then the smaller problems are solved one by one. However, in this technique any random decomposition of a problem into smaller parts will not help. The problem has to be decomposed such that each component of the decomposed problem can be solved independently and then the solution of the different components can be combined to get the full solution. A good decomposition of a problem as
shown in fig.1.5 should minimize interactions among various components. If the different sub-components are interrelated, then the different components cannot be solved separately and the desired reduction in complexity will not be realized.
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