Function point: Difference between revisions

Revision as of 16:27, 6 February 2017

Revision as of 03:51, 4 March 2017

Line 23:

* Engineering function points – Elements (variable names) and operators (e.g., arithmetic, equality/inequality, Boolean) are counted. This variation highlights computational function.<ref>Engineering Function Points and Tracking System, [http://www.stsc.hill.af.mil/crosstalk/1994/11/xt94d11e.asp Software Technology Support Center], Retrieved on May 14, 2008</ref> The intent is similar to that of the operator/operand-based [[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." 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 re-engineering (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 essentialbutessential for proper operation.

* [[Weighted Micro Function Points]] – One of the newer models (2009) which adjusts function points using weights derived from program flow complexity, operand and operator vocabulary, object usage, and algorithmic intricacy.

* Fast Function Points Analysis (FFPA) – A similar system to IFPUG that was designed by [[Gartner]] as a way of calculating function points at a faster rate to deliver higher client benefit. It is presumably much faster than the traditional IFPUG method and only roughly 2% less accurate.

== Benefits ==