Functional Point (FP) Analysis - Software Engineering

Functional Point Analysis (FPA) is a software measurement technique used to assess the size and complexity of a software system based on its functionality. It involves categorizing the functions of the software, such as input screens, output reports, inquiries, files, and interfaces, and assigning weights to each based on their complexity. By quantifying these functions and their associated weights, FPA provides an objective measure of the software's size and complexity.

What is Functional Point Analysis?

Function Point Analysis was initially developed by Allan J. Albrecht in 1979 at IBM and has been further modified by the International Function Point User's Group (IFPUG) in 1984, to clarify rules, establish standards, and encourage their use and evolution. Allan J. Albrecht gave the initial definition, Functional Point Analysis gives a dimensionless number defined in function points which we have found to be an effective relative measure of function value delivered to our customer. A systematic approach to measuring the different functionalities of a software application is offered by function point metrics. Function point metrics evaluate functionality from the perspective of the user, that is, based on the requests and responses they receive.

Objectives of Functional Point Analysis

1. Encourage Approximation: FPA helps in the estimation of the work, time, and materials needed to develop a software project. Organizations can plan and manage projects more accurately when a common measure of functionality is available.
2. To assist with project management: Project managers can monitor and manage software development projects with the help of FPA. Managers can evaluate productivity, monitor progress, and make well-informed decisions about resource allocation and project timeframes by measuring the software's functional points.
3. Comparative analysis: By enabling benchmarking, it gives businesses the ability to assess how their software projects measure up to industry standards or best practices in terms of size and complexity. This can be useful for determining where improvements might be made and for evaluating how well development procedures are working.
4. Improve Your Cost-Benefit Analysis: It offers a foundation for assessing the value provided by the program concerning its size and complexity, which helps with cost-benefit analysis. Making educated judgements about project investments and resource allocations can benefit from having access to this information.
5. Comply with Business Objectives: It assists in coordinating software development activities with an organization's business objectives. It guarantees that software development efforts are directed toward providing value to end users by concentrating on user-oriented functionality.

Types of Functional Point Analysis

There are two types of Functional Point Analysis:

1. Transactional Functional Type

• External Input (EI): EI processes data or control information that comes from outside the application’s boundary. The EI is an elementary process.
• External Output (EO): EO is an elementary process that generates data or control information sent outside the application’s boundary. 
• External Inquiries (EQ): EQ is an elementary process made up of an input-output combination that results in data retrieval. 

2. Data Functional Type

• Internal Logical File (ILF): A user-identifiable group of logically related data or control information maintained within the boundary of the application.
• External Interface File (EIF): A group of users recognizable logically related data allusion to the software but maintained within the boundary of another software.

Benefits of Functional Point Analysis

Following are the benefits of Functional Point Analysis:

1. Technological Independence: It calculates a software system's functional size independent of the underlying technology or programming language used to implement it. As a result, it is a technology-neutral metric that makes it easier to compare projects created with various technologies.
2. Better Accurate Project Estimation: It helps to improve project estimation accuracy by measuring user interactions and functional needs. Project managers can improve planning and budgeting by using the results of the FPA to estimate the time, effort and resources required for development.
3. Improved Interaction: It provides a common language for business analysts, developers, and project managers to communicate with one another and with other stakeholders. By communicating the size and complexity of software in a way that both technical and non-technical audiences can easily understand this helps close the communication gap.
4. Making Well-Informed Decisions: FPA assists in making well-informed decisions at every stage of the software development life cycle. Based on the functional requirements, organizations can use the results of the FPA to make decisions about resource allocation, project prioritization, and technology selection.
5. Early Recognition of Changes in Scope: Early detection of changes in project scope is made easier with the help of FPA. Better scope change management is made possible by the measurement of functional requirements, which makes it possible to evaluate additions or changes for their effect on the project's overall size.

Disadvantage of Functional Point Analysis

Given below are some disadvantages of Functional Point Analysis:

1. Subjective Judgement: One of the main disadvantages of Functional Point Analysis is it's dependency on subjective judgement i.e. relying on personal opinions and interpretations instead of just using clear, measurable standards.
2. Low Accuracy: It has low evaluation accuracy as it's dependency on subjective judgement.
3. Time Consuming: Functional Point Analysis is a time consuming process, particularly during the initial stages of implementation.
4. Steep Learning Curve: Learning FPA can be challenging due to its complexity and the length of time required to gain proficiency.
5. Less Research Data: Compared to LOC-based metrics, there is relatively less research data available on function points.
6. Costly: The need for thorough analysis and evaluation can result in increased project timelines and associated costs.

Characteristics of Functional Point Analysis

• We can calculate the functional point with the help of the number of functions and types of functions used in applications. These are classified into five types:

Types of FP Attributes or Information Domain Characteristics

• Functional Point helps in describing system complexity and also shows project timelines.
• It is majorly used for business systems like information systems.
• FP is language and technology independent, meaning it can be applied to software systems developed using any programming language or technology stack.
• All the factors mentioned above are given weights, and these weights are determined through practical experiments in the following table.

Weights of 5 Functional Point Attributes

Functional Complexities help us in finding the corresponding weights, which results in finding the Unadjusted Functional point (UFp) of the Subsystem. Consider the complexity as average for all cases. Below-mentioned is the way how to compute FP.

From the above tables, Functional Point is calculated with the following formula

FP = Count-Total * [0.65 + 0.01 * ⅀(fi)]

= Count * CAF

Here, the count-total is taken from the chart.

CAF = [0.65 + 0.01 * ⅀(fi)]

1. ⅀(fi) = sum of all 14 questions and it also shows the complexity factor - CAF.
2. CAF varies from 0.65 to 1.35 and ⅀(fi) ranges from 0 to 70.
3. When ⅀(fi) = 0, CAF = 0.65 and when ⅀(fi) = 70, CAF = 0.65 + (0.01*70) = 0.65 + 0.7 = 1.35

Questions on Functional Point

1. Consider a software project with the following information domain characteristic for the calculation of function point metric.

Number of external inputs (I) = 30

Number of external output (O) = 60

Number of external inquiries (E) = 23

Number of files (F) = 08

Number of external interfaces (N) = 02

It is given that the complexity weighting factors for I, O, E, F, and N are 4, 5, 4, 10, and 7, respectively. It is also given that, out of fourteen value adjustment factors that influence the development effort, four factors are not applicable, each of the other four factors has value 3, and each of the remaining factors has value 4. The computed value of the function point metric is _____. [GATE CS 2015]

(A) 612.06
(B) 404.66
(C) 305.09
(D) 806.9

Solution: Correct Answer is (A).

For more, refer to GATE CS 2015 | Question 65.

2. While estimating the cost of the software, Lines of Code(LOC) and Function Points (FP) are used to measure which of the following? [UGC-NET CSE 2013]

(A) Length of Code

(B) Size of Software

(C) Functionality of Software

(D) None of the Above

Solution: Correct Answer is (B).

3. In functional point analysis, the number of complexity adjustment factors is [UGC-NET CS 2014]

(A) 10

(B) 12

(C) 14

(D) 20

Solution: Correct Answer is (C).

Conclusion

Functional Point Analysis (FPA) offers a structured approach to measure the size and complexity of software systems based on their functionality. By categorizing functions and assigning weights, FPA provides an objective measurement that helps in estimating project timelines, resource requirements, and overall system complexity. It focuses on user-centric features, making it valuable for business systems like management information systems (MIS).