Empirical Evaluation

We calculate the value of the proposed factors for the component used in a Classroom- Based Project called the College Information System. This project has following three modules:

  • • Attendance system.
  • • Fees management system.
  • • Results system.

All these modules require the same Component Calendar which displays date, time, month, year, and some more facilities. To select these Components we visited two sites, www.componentsource.com and www.jars.com, and calculated the value of five factors as follows:

Selection Effort Rule Viewer

FIGURE 4.9 Selection Effort Rule Viewer.

Reusability: the value of reusability is given on the site. Each component that is on this site has stars attached to it. The higher the number of stars, the higher is the reusability.

Another method of calculating reusability is proposed by Sharma Arun (2009) and is based on the Artificial Neural Network (ANN)-based approach.

Portability: A component which is supported by most operating systems has higher portability.

Functionality: The functionality of a component can be calculated by the number of different tasks or facilities provided by the components.

Security: This factor can be calculated by seeing the security mechanism implemented on the particular component.

Performance: Performance can be calculated by the size of the component. The value of the factors is then supplied to the fuzzy rule base and the results are found as follows shown in Table 4.5.

Weight Assignment Factors for Component Selection Efforts

On the basis of this component-related technology some surveys were performed on software and professionally taught projects to evaluate the live analysis. In the case of teachers, the ranking will be from lecturer to professor and for software

TABLE 4.5

Results Using All Five Factors

Reusability

Portability

Functionality

Security

Performance

Selection

Efforts

0.50

0.50

0.50

0.50

0.50

0.51

0.17

0.45

0.23

0.62

0.18

0.472

0.12

0.20

0.09

0.13

0.10

0.902

0.72

0.90

0.75

0.85

0.97

0.311

0.58

0.85

0.62

0.32

0.90

0.541

professionals from senior to project manager. The experience of these professionals will be different, between five and 12 years. The five factors that were given in the proposed model will be contained in the survey form. The professionals were invited to provide their respective preferences for these five factors on considering their related application.

By utilizing the Analytical Hierarchy Process (AHP) technique the response collected from the professionals will be analyzed. The design of the above-mentioned model was by Saaty (1994). This technique is designed mainly for decision-making purposes. The various problems can be through this decision-making approach. They can be used in evaluating choices in multi-objective decision situations, quantifying intangible factors, and decision makers in structuring complex decisions. For the set of elements, the related value can be obtained through this rational decisionmaking framework. This is why it is referred to as a powerful technology. In cases of comparison decision making, which is a tedious process, the AHP technique can also be used. This technique has numerous applications which include marketing, corporate planning, portfolio selection, and transportation planning. The application is mentioned as follows:

  • • The relative importance existing between the attributes can be developed by means of exhaustive paired comparison analysis or expert opinion.
  • • For every attribute, by means of certain algorithms the weight age will be developed.
  • • For every attribute, a similar analysis will be carried out for alternative solution strategies.
  • • In cases of every alternate strategy solution the single entire score will be developed.

In this survey 125 professionals were considered, the analysis was carried out in three phases and at least 25 persons were selected. In every phase the analysis was carried out with the help of the AHP technique and in the obtained result 8% variation was found. The operation of the data created was done using MS Excel. For every main parameter, the weight value is illustrated in Table 4.6. The values will be in the range of 0 to 1. The summation of the weighed values is will be 1.

TABLE 4.6

Weight Values Assignment for Each Factor

Factors

Reusability

Portability

Functionality

Security

Performance

Weights

0.21875

0.210938

0.175781

0.167969

0.226563

Correlation: Correlation is one of the most widely used statistical techniques. It is very useful in the fields of biology, economics, agriculture, psychology, etc. where there are certain relationships between pairs of variables. These relationships enable us to predict certain things. For example, an increase in production of a thing will raise the fall in price.

 
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