Function Point Analysis in Software Engineering - Mini Project: Build & Apply

Function Point Analysis

📖 Scenario: You are a software analyst working on a new project. You need to estimate the size of the software using Function Point Analysis (FPA). This method helps you understand the complexity and effort required by counting different types of functions in the system.

🎯 Goal: Build a simple Function Point Analysis model by listing function types, assigning complexity weights, calculating unadjusted function points, and applying a value adjustment factor to get the final function point count.

📋 What You'll Learn

Create a dictionary with function types and their counts

Create a dictionary with complexity weights for each function type

Calculate the unadjusted function points by multiplying counts by weights and summing

Apply a value adjustment factor to calculate the final function points

💡 Why This Matters

🌍 Real World

Function Point Analysis helps project managers estimate software size and effort before development starts, improving planning and budgeting.

💼 Career

Software analysts, project managers, and developers use function points to communicate project scope and complexity clearly.

1

DATA SETUP: Define function counts

Create a dictionary called function_counts with these exact entries: 'External Inputs': 10, 'External Outputs': 7, 'Internal Logical Files': 5, 'External Interface Files': 3, and 'External Inquiries': 4.

Software Engineering

# Create the function_counts dictionary with exact entries
# Your code here

Need a hint?

Use a Python dictionary with the exact keys and values given.

2

CONFIGURATION: Define complexity weights

Create a dictionary called complexity_weights with these exact entries: 'External Inputs': 4, 'External Outputs': 5, 'Internal Logical Files': 10, 'External Interface Files': 7, and 'External Inquiries': 3.

Software Engineering

function_counts = {
    'External Inputs': 10,
    'External Outputs': 7,
    'Internal Logical Files': 5,
    'External Interface Files': 3,
    'External Inquiries': 4
}
# Create the complexity_weights dictionary with exact entries
# Your code here

Need a hint?

Use a dictionary with the exact keys and weights given.

3

CORE LOGIC: Calculate unadjusted function points

Create a variable called unadjusted_fp and set it to the sum of the products of counts and weights for each function type using a for loop over function_counts.items().

Software Engineering

function_counts = {
    'External Inputs': 10,
    'External Outputs': 7,
    'Internal Logical Files': 5,
    'External Interface Files': 3,
    'External Inquiries': 4
}

complexity_weights = {
    'External Inputs': 4,
    'External Outputs': 5,
    'Internal Logical Files': 10,
    'External Interface Files': 7,
    'External Inquiries': 3
}

# Calculate unadjusted_fp by summing count * weight for each function type
# Your code here

Need a hint?

Use a for loop to multiply each count by its weight and add to unadjusted_fp.

4

COMPLETION: Apply value adjustment factor

Create a variable called value_adjustment_factor and set it to 1.1. Then create a variable called final_function_points and set it to unadjusted_fp multiplied by value_adjustment_factor.

Software Engineering

function_counts = {
    'External Inputs': 10,
    'External Outputs': 7,
    'Internal Logical Files': 5,
    'External Interface Files': 3,
    'External Inquiries': 4
}

complexity_weights = {
    'External Inputs': 4,
    'External Outputs': 5,
    'Internal Logical Files': 10,
    'External Interface Files': 7,
    'External Inquiries': 3
}

unadjusted_fp = 0
for function_type, count in function_counts.items():
    unadjusted_fp += count * complexity_weights[function_type]

# Set value_adjustment_factor to 1.1 and calculate final_function_points
# Your code here

Need a hint?

Multiply unadjusted_fp by value_adjustment_factor to get final_function_points.