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Unit 4: Introduction to Validation, Metrics

its relative quality. It is a qualitative metric, understood in a qualitative manner. Qualitative Notes
metrics are relative to some quantitative measure; however, exact position on the quantitative
scale may not be possible with the given data due to the use of a weak ordering. A qualitative
metric still provides relevant indication of quality. This is an important aspect of metrics for
software since the abstract nature of software can often preclude quantitative measures of certain
quality attributes.

4.1 Function Point and Quality Metrics

Software systems, except they are thoroughly unspoken, can be like an ice berg. They are flattering
more and more difficult to understand. Development of coding tools allows software developers
to manufacture large amounts of software to get together an ever increasing need from users.
As systems grow a method to understand and converse size needs to be used. Function Point
Analysis is a structured technique of problem solving. It is a method to break systems into
smaller components, so they can be better understood and analyzed.
4.1.1 Function Point Analysis

Function points are a unit calculate for software a great deal like an hour is to measuring time,
miles are to measuring distance or Celsius is to measuring temperature. Function Points are
an ordinal measure much like other measures such as kilometres, Fahrenheit, hours, so on and
so forth.
Human beings solve problems by breaking them into smaller understandable pieces. Problems
that may appear to be difficult are simple once they are broken into smaller parts dissected into
classes. Classifying things, placing them in this or that category is a familiar process. Everyone
does it at one time or another shopkeepers when they take stock of what is on their shelves,
librarians when they catalogue books, secretaries when they file letters or documents. When
objects to be classified are the contents of systems, a set of definitions and rules must be used
to place these objects into the appropriate category, a scheme of classification. Function Point
Analysis is a structured technique of classifying components of a system. It is a method to break
systems into smaller components, so they can be better understood and analyzed. It provides
a structured technique for problem solving.
In the world of Function Point Analysis, systems are divided into five large classes and general
system characteristics. The first three classes or components are External Inputs, External Outputs
and External Inquires each of these components transact against files therefore they are called
transactions. The next two Internal Logical Files and External Interface Files are where data is
stored that is combined to form logical information. The general system characteristics assess
the general functionality of the system.

Function Point Analysis was an attempt to overcome difficulties associated with lines of code as
a measure of software size, and to assist in developing a mechanism to predict effort associated
with software development. The method was first published in 1979, then later in 1983. In 1984
Albrecht refined the method and since 1986, when the International Function Point User Group
(IFPUG) was set up, several versions of the Function Point Counting Practices Manual have
been published by IFPUG.

Objectives of Function Point Analysis
Frequently the term end user or user is used without specifying what is meant. This container,
the user is a sophisticated user. Someone that would understand the system from a functional
perspective more than likely someone that would provide requirements or does acceptance
testing.
Since Function Points measures systems from a functional viewpoint they are self-governing of
technology. Regardless of language, growth method, or hardware platform used, the number

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