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Function Point - Step by Step Guide with Numerical Examples
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In this video, you will learn
1. What is Functional Point in software engineering?
2. How to calculate the FP for project estimation?
3. Examples of the FP calculation with its uses.
It’s really difficult to weigh the real values or worth of software. One of the best ways to estimate the software development cost and time is based on the previous software development experience. To measure the standard worth of the software, as a unit of software worth, Function Point was developed. Functional Point was first defined by Allan Albrecht of IBM in 1977. It is used effectively as a means for measuring the functionality delivered by a system.
FP measures functionality from the User’s point of view like what the user receives from the software and what the user requests from the software. It focuses on what functionality is being delivered.
According to Wiki
“A Functional Point” is a unit of measurement to express the amount of business functionality an information system provides to a user.”
Using historical data, the FP metric can then be used to
1. Estimate the cost or effort required to design, code, and test the software.
2. Predict the number of errors that will be encountered during testing
3. Forecast the number of components and/or the number of projected source lines in the implemented system.
FPs are derived using an empirical relationship based on countable measures of software’s information domain and qualitative assessments of software complexity. The five functional units which is consider as information domain as input to calculate the FP are.
1. Internal Logic Files (ILF) – The control info or logically related data that is present within the system.
2. External Interface Files (EIF) – The control data or other logical data i.e referenced by the system but present in another system.
3. External Inputs (EI) – Data / control info that comes from outside our system
4. External Outputs (EO) – data that goes out of the system after generation
5. External Enquired (EQ) – Combination of i/o – o/p resulting data retrieval
To compute FP, the following relationship is used:
FP = UFP X CAF
Where
UFP is Unadjusted Functional Point
CAF is Complexity Adjustment Factor
Step 1: Calculating UFP
Each Function point is ranked according to complexity. There exist pre-defined weights for each F.P in each category. Organizations that use function point methods develop criteria for determining whether a particular entry is simple, average, or complex. Nonetheless, the determination of complexity is somewhat subjective.
UFP = Sum of all the Complexities of all the EI’s, EO’s EQ’s, ILF’s and EIF’s
Step 2: Calculating CAF
CAF = 0.65 + (0.01 x submission Fi)
Where Fi is value adjustment factors based on responses to the 14 questions
Complexity Adjustment Factor is calculated using 14 aspects of processing complexity and these 14 questions answered on a scale of 0 – 5
0 – No Influences or no important or no applicable
1 – Incidental
2 – Moderate
3 – Average
4 – Significant
5 – Essential
To illustrate the use of the FP metric let’s see a simple analysis model
SafeHome
The function manages user interaction, accepting a user password to activate or deactivate the system, and allows inquiries on the status of security zones and various security sensors. The function displays a series of prompting messages and sends appropriate control signals to various components of the security system. The data flow diagram is evaluated to determine a set of the key information domain measures required for computation of the function point metric.
Three external inputs—password, panic button, and activate/deactivate
Two external inquiries—zone inquiry and sensor inquiry.
One ILF (system configuration file)
Two external outputs - (messages and sensor status)
and four EIFs (test sensor, zone setting, activate/deactivate, and alarm alert)
Now calculating Unadjusted FP with the simple weighting factor
Therefore, UFP is equal to 50
Now moving to calculate CAF
As we know
CAF = 0.65 + (0.01 x Submission Fi)
Let’s calculate in a moderately complex product
Then Submission Fi = 14X2 = 28
CAF = 0.93
Fp = 50 x 0.93 =
Therefore, FP is equal to 46.5
In this way we can calculate the unadjusted functional point, Complexity factor, and finally Functional Point and from which we can estimate the lines of code required to develop the software, the number of probability errors, the effort required, development time, etc concerning previous data.
SUBSCRIBE to our YouTube channel for more videos:
1. What is Functional Point in software engineering?
2. How to calculate the FP for project estimation?
3. Examples of the FP calculation with its uses.
It’s really difficult to weigh the real values or worth of software. One of the best ways to estimate the software development cost and time is based on the previous software development experience. To measure the standard worth of the software, as a unit of software worth, Function Point was developed. Functional Point was first defined by Allan Albrecht of IBM in 1977. It is used effectively as a means for measuring the functionality delivered by a system.
FP measures functionality from the User’s point of view like what the user receives from the software and what the user requests from the software. It focuses on what functionality is being delivered.
According to Wiki
“A Functional Point” is a unit of measurement to express the amount of business functionality an information system provides to a user.”
Using historical data, the FP metric can then be used to
1. Estimate the cost or effort required to design, code, and test the software.
2. Predict the number of errors that will be encountered during testing
3. Forecast the number of components and/or the number of projected source lines in the implemented system.
FPs are derived using an empirical relationship based on countable measures of software’s information domain and qualitative assessments of software complexity. The five functional units which is consider as information domain as input to calculate the FP are.
1. Internal Logic Files (ILF) – The control info or logically related data that is present within the system.
2. External Interface Files (EIF) – The control data or other logical data i.e referenced by the system but present in another system.
3. External Inputs (EI) – Data / control info that comes from outside our system
4. External Outputs (EO) – data that goes out of the system after generation
5. External Enquired (EQ) – Combination of i/o – o/p resulting data retrieval
To compute FP, the following relationship is used:
FP = UFP X CAF
Where
UFP is Unadjusted Functional Point
CAF is Complexity Adjustment Factor
Step 1: Calculating UFP
Each Function point is ranked according to complexity. There exist pre-defined weights for each F.P in each category. Organizations that use function point methods develop criteria for determining whether a particular entry is simple, average, or complex. Nonetheless, the determination of complexity is somewhat subjective.
UFP = Sum of all the Complexities of all the EI’s, EO’s EQ’s, ILF’s and EIF’s
Step 2: Calculating CAF
CAF = 0.65 + (0.01 x submission Fi)
Where Fi is value adjustment factors based on responses to the 14 questions
Complexity Adjustment Factor is calculated using 14 aspects of processing complexity and these 14 questions answered on a scale of 0 – 5
0 – No Influences or no important or no applicable
1 – Incidental
2 – Moderate
3 – Average
4 – Significant
5 – Essential
To illustrate the use of the FP metric let’s see a simple analysis model
SafeHome
The function manages user interaction, accepting a user password to activate or deactivate the system, and allows inquiries on the status of security zones and various security sensors. The function displays a series of prompting messages and sends appropriate control signals to various components of the security system. The data flow diagram is evaluated to determine a set of the key information domain measures required for computation of the function point metric.
Three external inputs—password, panic button, and activate/deactivate
Two external inquiries—zone inquiry and sensor inquiry.
One ILF (system configuration file)
Two external outputs - (messages and sensor status)
and four EIFs (test sensor, zone setting, activate/deactivate, and alarm alert)
Now calculating Unadjusted FP with the simple weighting factor
Therefore, UFP is equal to 50
Now moving to calculate CAF
As we know
CAF = 0.65 + (0.01 x Submission Fi)
Let’s calculate in a moderately complex product
Then Submission Fi = 14X2 = 28
CAF = 0.93
Fp = 50 x 0.93 =
Therefore, FP is equal to 46.5
In this way we can calculate the unadjusted functional point, Complexity factor, and finally Functional Point and from which we can estimate the lines of code required to develop the software, the number of probability errors, the effort required, development time, etc concerning previous data.
SUBSCRIBE to our YouTube channel for more videos:
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