A function point is a unit of measurement to express the amount of business functionality an information system provides to a user.

Function points are an ISO recognized software metric to size an information system based on the functionality that is perceived by the user of the information system, independent of the technology used to implement the information system. ISO has many meanings: Iso is the stem of the Latin transliteration of the Greek word ίσος (ísos, meaning equal). The iso- prefix in English derives from this and means equality or similarity. ... A software metric is a measure of some property of a piece of software or its specifications. ... It has been suggested that this article or section be merged with Information systems. ...

Function Points were defined in 1979 (Function Points: A New Way of Looking at Tools) by Alan Albrecht at IBM. For other uses, see IBM (disambiguation) and Big Blue. ...

The method of measuring the size of an information system and expressing it in a number of function points is called Function Point Analysis. The method is kept up to date by worldwide cooperating FPA user groups like NESMA and IFPUG. Function point analysis (FPA) is a method used to gauge the size and complexity of computer software, employing a function point as a unit of measure. ... International Function Point Users Group, a US based organization of users of the software metric Function point analysis ...

Basic function points are categorized into five groups: outputs, inquiries, inputs, files, and Interfaces. A function point is defined as one end-user business function, such as a query for an input. This distinction is important because it tends to make a function point map easily into user-oriented requirements, but it also tends to hide internal functions, which also require resources to implement. To make up for this (and other) weaknesses, some refinements to and/or variations of the basic Albrecht definition have been devised, including

• Early and easy function points. Adjusts for problem and data complexity with two questions that yield a somewhat subjective complexity measurement; simplifies measurement by eliminating the need to count data elements.
• Engineering function points. Elements (variable names) and operators (e.g., arithmetic, equality/inequality, Boolean) are counted. This variation highlights computational function [Umholtz 94]. The intent is similar to that of the operator/operand-based Halstead measures (see Halstead Complexity Measures).
• Bang measure. Defines a function metric based on twelve primitive (simple) counts that affect or show Bang, defined as "the measure of true function to be delivered as perceived by the user" [DeMarco 82]. Bang measure may be helpful in evaluating a software unit's value in terms of how much useful function it provides, although there is little evidence in the literature of such application. The use of Bang measure could apply when reengineering (either complete or piecewise) is being considered, as discussed in Maintenance of Operational Systems--An Overview.
• Feature points. Adds changes to improve applicability to systems with significant internal processing (e.g., operating systems, communications systems). This allows accounting for functions not readily perceivable by the user, but essential for proper operation.

Criticisms of Function Points

Function points, and many other software metrics, have been criticized as adding little value relative to the cost and complexity of the effort.^[1][2] The effort in computing function points has only a marginal error reduction, in part, because much of the variance in software cost estimates are not considered (such as business changes, scope changes, unplanned resource constraints or reprioritizations, etc.). Also, if the measurement is used for the decision of whether to invest in the software, then a given measurement effort, it is argued, is more valuable if it is applied to measure benefits than costs. Applied Information Economics, which computes the economic value of such measures, often leads users to spend measurement efforts on other issues. The creator of or main contributor to this page may have a conflict of interest with the subject of this article. ...

References

1. ^ Douglas Hubbard The IT Measurement Inversion, CIO Magazine, 1999
2. ^ Douglas Hubbard "How to Measure Anything: Finding the Value of Intangibles in Business" John Wiley & Sons, 2007

See also

• Function Point Analysis
• Source lines of code
• COCOMO

Function point analysis (FPA) is a method used to gauge the size and complexity of computer software, employing a function point as a unit of measure. ... Source lines of code (SLOC) is a software metric used to measure the amount of code in a software program. ... This article or section is in need of attention from an expert on the subject. ...

External links

• Function Points: A New Way of Looking at Tools" article in Computer magazine by Capers Jones.
• Resource Standard Metrics Use Lines of Code to back fire function points and create cross correlated estimates - Available for limited free use that is ideal for computer science course.
• The Netherlands Software Metrics users Association (NESMA)
• The International Function Point Users Group (IFPUG)
• The COmmon Software Measurement International Consortium
• Function Point Analysis in FOLDOC
• Function Point Analysis in Software Technology Roadmap
• Function Point Training Manual