Function Point Estimate Calculator

Work out function point estimate instantly with clear inputs, formula shown and shareable results.

About Function Point Estimate Calculator

IFPUG function point analysis counts five function types and weights them by average complexity: external inputs at 4, outputs at 5, inquiries at 4, internal logical files at 10 and external interface files at 7. The result measures delivered functionality independently of technology, which is what makes it usable for cross-project productivity comparison where SLOC is not.

Formula

Function point count

UFP = 4 x inputs + 5 x outputs + 10 x internal files + 7 x external interfaces (average complexity weights)

Worked example

With the default values below, Function Point Estimate Calculator returns Unadjusted function points of 430. Change any input above and every figure here is recalculated in your browser.

Inputs used

External inputsminimum 0: 32
External outputsminimum 0: 24
Internal logical filesminimum 0: 14
External interface filesminimum 0: 6

Results

Unadjusted function points: 430
Adjusted function points: 430
Share from data functions: 42.3%
Transactional functions counted: 56

Step by step

1Values used
2Function point count
3Unadjusted function points= 430
4Adjusted function points= 430
5Share from data functions= 42.3
6Transactional functions counted= 56

Assumptions and limits

The result is derived only from the 4 inputs listed above. Anything not among them is not part of the calculation.
In particular, this calculator does not take inflation, tax, fees or charges or compounding frequency into account.
Figures are rounded for display to 1 decimal place, so totals built from several rounded parts can differ slightly from the unrounded arithmetic.

How these calculators are built and tested is described on the Methodology page. If a figure looks wrong, please report it.

Frequently Asked Questions

What is the value adjustment factor?

A multiplier from 0.65 to 1.35 derived from fourteen general system characteristics such as performance and reusability. Many modern practitioners omit it as unreliable.

Do function points work for modern systems?

They apply well to transactional business applications. They fit poorly to algorithmic, real-time or infrastructure work where complexity is not proportional to data movement.