Functional vs non-functional requirements in Software Engineering - Performance Comparison
When we analyze requirements, we want to understand how the effort to meet them grows as the system gets bigger or more complex.
We ask: How does the work needed change when adding more features or improving qualities?
Analyze the time complexity of handling functional and non-functional requirements.
// Pseudocode example
function handleRequirements(requirements) {
for (let req of requirements) {
if (req.type === 'functional') {
processFunctional(req);
} else {
processNonFunctional(req);
}
}
}
function processFunctional(req) {
// Steps to implement feature
}
function processNonFunctional(req) {
// Steps to ensure quality
}
This code goes through each requirement and processes it based on its type.
Look for repeated actions that take time.
- Primary operation: Looping through all requirements once.
- How many times: Once for each requirement in the list.
As the number of requirements grows, the work grows too.
| Input Size (n) | Approx. Operations |
|---|---|
| 10 | 10 steps |
| 100 | 100 steps |
| 1000 | 1000 steps |
Pattern observation: The work increases directly with the number of requirements.
Time Complexity: O(n)
This means the effort grows in a straight line as you add more requirements.
[X] Wrong: "Non-functional requirements take no extra time because they are not features."
[OK] Correct: Non-functional requirements often need careful work and testing, so they add to the total effort just like functional ones.
Understanding how requirement types affect project effort helps you explain planning and prioritization clearly in real work situations.
"What if non-functional requirements required checking every existing feature? How would the time complexity change?"