Studies in four different organizations developing different types of software show conclusively that sizes of sprints or iterations measured using standardized COSMIC Function Points correlate much better with effort than Story Points do. This means that standardized size measurements are a better predictor for estimating Agile activities than the commonly used Story Points.
The Price of IT
This blog is about the aspects that make up the price of IT solutions and services in the widest context. So from methods to substantiate a cost calculation to the value IT solutions and services represent to their various stakeholders.
November 17, 2017
Studies in four different organizations developing different types of software show conclusively that sizes of sprints or iterations measured using standardized COSMIC Function Points correlate much better with effort than Story Points do. This means that standardized size measurements are a better predictor for estimating Agile activities than the commonly used Story Points.
October 22, 2017
The use of functional size as a measure to make like-for-like comparisons between different software development or maintenance contracts has been common practice in administrative software for decades. In real-time software this practice is now starting to develop. Why did it take the real-time software community so long to catch up?
February 3, 2016
Estimation for Mobile and Cloud Environments
Estimation
of cost, effort and schedule is a very important aspect in commercial software
development and maintenance. For most types of development and maintenance, effort
is usually the predominant cost driver in software development. Until recently,
estimation was not an issue for mobile and cloud software. Mobile was the
domain of young developers who crafted the first version of an app and
distributed it to the world, bringing software to the cloud was usually a
boardroom decision where the result was more important than the estimation of
cost and effort.
But mobile
and cloud are maturing as fast as they gain market share. For all business software
that requires serious computing power, cloud is becoming the standard. Mobile
is no longer the exclusive domain of hip young techies, since more and more
business software is available on mobile platforms, backed up by the computing
power of a back-office in the cloud. Now mobile and cloud has become serious
business, the estimation of cost, effort and schedule requires serious
attention as well.
For all
types of software, the dominant determinant for effort is the size of the
software. Organizations engaged in software engineering have struggled for
years in search of acceptable quantitative methods for measuring process
efficiency and effectiveness, and for managing software costs, for the systems
they acquire, develop, enhance or maintain. One critical, and particularly
elusive, aspect of this measurement requirement has been the need to determine
software size. In the late 1970’s the concept of ‘functional size’ was
developed, which enabled companies to build estimates on that figure before any
code was written. IFPUG and Nesma established function point analysis methods
to formalize the way functional size was calculated. These methods are based on
the model that storage, processing and presentation of data takes place within
a single application.
Mobile and
cloud software use architectures in which these elements are separated. Apps
present functionality to end-users without knowledge how this data has been
assembled and processed and totally oblivious about where the base data might
be stored. In the cloud, storage and processing of data are – at least
logically – separated, offering functionality to all or authorized mobile
devices by means of an API. Traditional methods to determine functional size
have very limited use in these environments.
The basic COSMIC principles |
For mobile
and cloud environments the COSMIC method is well-suited to serve as a basis for
estimating cost, effort and schedule. The basic principles on which the method
is built, are architecture-independent. This means that all software, whether
it is only a small component or a full-range business system, can be sized with
this method. This size can be used to estimate the investment in money,
development capacity and time to realize this software. The method is developed
and maintained by an open-source community from all over the world and is
actively supported by a number of companies and research institutions.
Last week,
the latest book in the series on Advances in Systems Analysis, Software
Engineering, and High Performance Computing was released: Modern Software Engineering Methodologies for Mobile and Cloud Environments. It also contains a
chapter how the development and maintenance of these types of software can be
estimated by using the COSMIC method. If you are responsible for estimating
mobile or cloud software, this chapter will give you the basics you need,
illustrated with examples.
If you want to know more about the COSMIC method,
please visit their website cosmic-sizing.org.
September 30, 2013
Succesful IT projects really do exist
We regularly encounter failed IT projects in the news headlines, feeding the perception that it is virtually impossible to finish an IT project succesfully.
Succesful IT projects really do exist!
It is true that still (too) many IT projects fail, but there are plenty examples that have completed succesfully. From those succesful IT projects we could learn a lot about the factors that lead to success, rather than trying to avoid known pitfalls. That's why I have done a retrospect and noted several observations that can support more IT projects to be succesful.
Succesful IT projects really do exist!
June 19, 2013
Adoption of the EPS-framework for packaged software estimation
On the IWSM 2012 conference in Assisi in October last year the NESMA presented the EPS-framework for the estimation of packaged software. A working group of NESMA has developed this estimating framework which supports the estimation of all costs related to the implementation and maintenance of packaged software. This framework can be the reference for comparison and benchmarking of package software estimates. The details for all six stages will be ready at the end of this year, but Comarch from Poland has already adopted the framework for some of their package implementation offers.
February 28, 2013
From rules to principles : COSMIC
Up to 1998 all methods to express functional size of software were rule-based. Performing the measurement rules led to a number of points that we call the size. Whether they were object points, use case points or function points, all these methods have a measurement procedure to award a part of the Fuctional User Requirements that satisfies a number of assessment criteria, with a defined number of points. To determine the number of points you must apply the rules. A group of people who were involved in the conception of ISO/IEC 14143 wanted to use the principles they had described to create a new generation of Functional Size Measurement method with a clear and defined measurement unit. Based on that unit a method could be created, based on principles to identify instances of that unit, rather than on rules. Out of that process, COSMIC was born.
Here is a piece of COSMIC history.
February 14, 2013
What is a second generation FSM method
Every now and again there is debate amongst
practitioners of Functional Size Measurement about the best Functional Size
Measurement method. In essence there is nothing wrong with such a debate.
Professionals should always be
seeking ways to improve their profession. Discussions about the best way to do
so are a logical part of such a quest. But they should be done based on the
right arguments. And one of those arguments is often wrong in my point of view.
That is the generation argument. I notice that there is a lot of misconception
about what is meant with generation in relation to Functional Size Measurement. In my blogpost of January I discussed the first generation. In this one I will discuss the second generation of Functional Size Measurement.
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