QAI Global Institute is happy to bring you the Software Size Estimation Using FPA course. You can access this course anytime‚ anywhere‚ through the Internet.

Introduction

Software size is an important input for estimating the effort‚ schedule‚ and cost of software. However‚ factors such as ever-expanding user requirements and the variety of software tools available today make it difficult to estimate the software size.

Function point analysis (FPA) is a structured technique for software size estimation and helps overcome these difficulties. The FPA technique involves viewing the functionality of software from the users’ perspective and then estimating the size based on the required functionality.

Software Size Estimation Using FPA course includes:

• An Overview of FPA
• Detailed FPA Technique

Course Benefits

This course will enable you to:

• Explain the basic concepts of function point analysis (FPA).
• Estimate software size by using the Detailed FPA technique.

You receive a certificate of completion after successfully completing this course.

Content Brief

FPA is a technique for estimating software size in function points. Allan J. Albrecht developed this technique to overcome the difficulties associated with using lines of code (LOC) to estimate software size.

FPA enables you to estimate software size by quantifying the functionality that the software provides to users. Some variants of the standard FPA technique are Detailed FPA (DFPA)‚ Quick FPA (QFPA)‚ Mark II FPA‚ Cosmic FPA‚ and Feature points.

DFPA is the most common FPA technique. It involves estimating software size on the basis of user-identifiable elementary processes in the software. DFPA includes a set of definitions and rules to first identify and classify the elementary processes into two types—data at rest and data in motion—and then‚ estimate their size.

Data at rest refers to the data stored by an application for processing at a later time. Data at rest can either be stored in an internal logical file (ILF) or in an external interface file (EIF).

Each application is uniquely affected by factors such as performance issues‚ data communication issues‚ or complex processing. When the FP count is derived only on the basis of application functionality‚ it fails to account for such characteristics‚ and therefore‚ is considered ‘unadjusted‘.

Calculating the value adjustment factor (VAF) is the third step in DFPA. VAF is a factor for calibrating the application FP count to account for the overall complexity of the application.

VAF is obtained by evaluating the degree of influence of 14 general system characteristics (GSCs) that affect the overall complexity of a typical software application. The degree of influence of a GSC is rated on a six-point scale‚ from zero to five. In this scale‚ a rating of zero implies that the GSC has no influence on the functionality of the application functionality and a rating of five implies strong influence.

Calculating the final FP count‚ the concluding step in DFPA step‚ involves adjusting the size of an application by multiplying the application FP count with the VAF value.