## Saturday, July 27, 2013

### PPT On TEST POINT ANALYSIS

Presentation On TEST POINT ANALYSIS

TEST POINT ANALYSIS Presentation Transcript:
1.TEST POINT ANALYSIS

2.Introduction
The goal of this technique is to outline all major factors that affect testing projects and to ultimately do an accurate test efforts estimation.

On time project delivery cannot be achieved without an accurate and reliable test effort estimate.

TPA is one such method which can be applied for estimating test effort in black box testing. It is a 6 step approach to test estimation and planning. We believe that our approach has a good potential for providing test estimation for various projects.

3.METHODOLOGY
TPA Philosophy
The effort estimation technique TPA, is based on three fundamental elements.
Size of the information system to be tested.
Test strategy.
Productivity
Size denotes the size of the information system to be tested.
Test strategy implies the quality characteristics that are to be tested on each subsystem.

4.TPA Model
Calculation of static test points :
St depends upon total FP of the information system and static quality characteristics of the system.
ISO 9126 has listed the following quality characteristics as static :
Functionality
Usability
Efficiency
Portability
Maintainability
Reliability
Method of calculation of Static Points:- ST  =  (FP * Qi)

5.Calculation of dynamic test points :
DT  =  FPf  * Df  * QD
DT     = Dynamic test points.
FPf    = Number of function points assigned to          the function .
Df    = Weighing factor for function dependent        factors.
QD    = Weighing factor for dynamic  quality            characteristics.

6.User importance
It implies how important is the function to the users related to other system functions.

Rule : “about 25% of functions should be placed in the high category, 50% in normal category and 25% in low category.”

7.Usage Intesity

8.Interfacing
It implies how much does one function affect other parts of the system. The degree of interfacing is determined by first ascertaining the logical data sets which the function in question can modify, then the other functions which access these LDSs. An interface rating is assigned to a function by reference to a table in which the number of LDSs affected by the function are arranged vertically and the number of the other functions accessing LDSs are arranged horizontally.

9.Complexity
The complexity of a function is determined on the basis of its algorithm i.e., how complex is the algorithm in a specific function.

The complexity rating of the function depends on the number of conditions in the functions algorithm.

10.Uniformity
It checks the reusability of the code. A uniformity factor of 0.6  is assigned in case of 2nd occurrence of unique function, clone and dummy functions. Otherwise in all cases a uniformity factor 1 is assigned.

Method of calculation of Df  : the factor is calculated by adding together the rating of first-four functions dependent variables i.e., Up, Ui I and C and then dividing it by 20 (sum of median/nominal weight of these factors).