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A function point is a unit of measurement to express the amount of business functionality an information system (as a product) provides to a user. Function points measure software size. The cost (in dollars or hours) of a single unit is calculated from past projects.〔Thomas Cutting, (Estimating Lessons Learned in Project Management - Traditional ), Retrieved on May 28, 2010〕 , there are several recognized standards and/or public specifications for sizing software based on Function Point 1. ISO Standards * COSMIC: ISO/IEC 19761:2011 Software engineering. A functional size measurement method. * FiSMA: ISO/IEC 29881:2008 Information technology - Software and systems engineering - FiSMA 1.1 functional size measurement method. * IFPUG: (ISO/IEC 20926:2009 ) Software and systems engineering - Software measurement - IFPUG functional size measurement method. * Mark-II: ISO/IEC 20968:2002 Software engineering - Ml II Function Point Analysis - Counting Practices Manual * NESMA: (ISO/IEC 24570:2005 ) Software engineering - NESMA function size measurement method version 2.1 - Definitions and counting guidelines for the application of Function Point Analysis 2. OMG Specification for Automated Function Point OMG, an open membership and not-for-profit computer industry standards consortium, has adopted the Automated Function Point (AFP) specification led by the Consortium for IT Software Quality. It provides a standard for automating the Function Point counting according to the guidelines of the International Function Point User Group (IFPUG).〔OMG/CISQ Specification “Automated Function Points”,February 2013, OMG Document Number ptc/2013-02-01 http://www.omg.org/spec/AFP/1.0〕 == Introduction == Function points were defined in 1979 in ''Measuring Application Development Productivity'' by Allan Albrecht at IBM.〔A. J. Albrecht, “Measuring Application Development Productivity,” Proceedings of the Joint SHARE, GUIDE, and IBM Application Development Symposium, Monterey, California, October 14–17, IBM Corporation (1979), pp. 83–92.〕 The functional user requirements of the software are identified and each one is categorized into one of five types: outputs, inquiries, inputs, internal files, and external interfaces. Once the function is identified and categorized into a type, it is then assessed for complexity and assigned a number of function points. Each of these functional user requirements maps to an end-user business function, such as a data entry for an Input or a user query for an Inquiry. This distinction is important because it tends to make the functions measured in function points map easily into user-oriented requirements, but it also tends to hide internal functions (e.g. algorithms), which also require resources to implement. There is currently no ISO recognized FSM Method that includes algorithmic complexity in the sizing result. Recently there have been different approaches proposed to deal with this perceived weakness, implemented in several commercial software products. The variations of the Albrecht based IFPUG method designed to make up for this (and other weaknesses) include: * 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.〔Engineering Function Points and Tracking System, (Software Technology Support Center ), Retrieved on May 14, 2008〕 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 essential 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. 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Function point」の詳細全文を読む スポンサード リンク
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