The 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 are used to compute a functional size measurement (FSM) of software. The cost (in dollars or hours) of a single unit is calculated from past projects.
There are several recognized standards and/or public specifications for sizing software based on Function Point.
ISO Standards
FiSMA: ISO/IEC 29881:2010 Information technology – Systems and software 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 24570:2018 Software engineering – Nesma functional size measurement method version 2.3 – Definitions and counting guidelines for the application of Function Point Analysis
COSMIC: ISO/IEC 19761:2011 Software engineering. A functional size measurement method.
OMG: ISO/IEC 19515:2019 Information technology — Object Management Group Automated Function Points (AFP), 1.0
The first five standards are implementations of the over-arching standard for Functional Size Measurement ISO/IEC 14143. The OMG Automated Function Point (AFP) specification, led by the Consortium for IT Software Quality, provides a standard for automating the Function Point counting according to the guidelines of the International Function Point User Group (IFPUG) However, the current implementations of this standard have a limitation in being able to distinguish External Output (EO) from External Inquiries (EQ) out of the box, without some upfront configuration.
Function points were defined in 1979 in Measuring Application Development Productivity by Allan Albrecht at IBM. 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.
This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.
In software development, effort estimation is the process of predicting the most realistic amount of effort (expressed in terms of person-hours or money) required to develop or maintain software based on incomplete, uncertain and noisy input. Effort estimates may be used as input to project plans, iteration plans, budgets, investment analyses, pricing processes and bidding rounds. Published surveys on estimation practice suggest that expert estimation is the dominant strategy when estimating software development effort.
Cost estimation in software engineering is typically concerned with the financial spend on the effort to develop and test the software, this can also include requirements review, maintenance, training, managing and buying extra equipment, servers and software. Many methods have been developed for estimating software costs for a given project.
In software engineering and development, a software metric is a standard of measure of a degree to which a software system or process possesses some property. Even if a metric is not a measurement (metrics are functions, while measurements are the numbers obtained by the application of metrics), often the two terms are used as synonyms. Since quantitative measurements are essential in all sciences, there is a continuous effort by computer science practitioners and theoreticians to bring similar approaches to software development.
, ,
In this letter, we present a trajectory optimization framework for whole-body motion planning through contacts. We demonstrate how the proposed approach can be applied to automatically discover different gaits and dynamic motions on a quadruped robot. In c ...
FPGAs (Field Programmable Gate Array) are an attractive technology for high-speed data processing in space missions due to their unbeatable flexibility and best performance-to-power ratio in comparison to software. However FPGAs suffer from 3 major drawbac ...
IEEE2018
To reach a given destination safely and accurately, a micro aerial vehicle needs to be able to avoid obstacles and minimize its state estimation uncertainty at the same time. To achieve this goal, we propose a perception-aware receding horizon approach. In ...