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Weakness of Function Point Analysis

Function Point Analysis is seen as a very important and useful technique for requirements estimation, and for numerous other benefits (see previous post for more details). However, even such a famous method has its detractors, with a number of people / studies pointing out issues with the technique. Here are some of these issues / weaknesses / problems:

– FPA is seen as not being fully suited for object oriented work with an objection that the core of the technique, function points cannot be reasonably counted for object-oriented requirements specifications. The problems are that several constructs of object oriented specifications representation can be interpreted in various ways in the spirit of FPA, depending on the context.
– Function point counts are affected by project size; ideally Function Points should not be affected by project size since they measure each function, but this does not work out in actual practise
– Function Point Counting techniques have been found to be not easy to apply to systems with very complex internal processing or massively distributed systems
– Difficult to define logical files from physical files
– The validity of the weights that were present in the initial technique that the founder of FPA, Albrecht, set up as well as the consistency of their application has been challenged
– Different companies do calculate function points slightly different (actually depending on the process and people who do the actual Function Counts), making intercompany comparisons questionable and negating one of the core benefits of having standardised Function Counts
– There is a conflict in the usage of FPA for project size purposes, this conflict being with another standard measure of counting – The number of lines of code is the traditional way of gauging application size and is claimed to be still relevant because it measures what software developers actually do, that is, write lines of code. At best it can be used along with Function Counts.
– Doing FPA means that you are depending on converting back the available information to actually do essentially the same thing as requirements specification, and should end up with the same types of errors. This process is touted as a big error prone area.
– Function points, and many other software metrics, have been criticized as adding little value relative to the cost and complexity of the effort which are major factors in decision making
– The effort in computing function points has some base errors inherent because much of the variance in software cost estimates are not considered (such as business changes, scope changes, unplanned resource constraints or reprioritizations, etc.).
– Function points don’t solve the problems of team variation, programming tool variation, type of application, etc.
– FP was originally designed to be applied to business information systems applications. So, the data dimension was emphasized and as a result, FPA was inadequate for many engineering and embedded systems.
– Another problem, this one dealing with the technical process of FPA comes up when assessing the size of a system in unadjusted function points (UFPs). The
classification of all system component types as simple, average and complex is not sufficient for all needs.
– Counting FP’s is a major factor, requiring the presence of a skilled counter. Many companies get this work done by people not having the desired skill level (this happens for other tools as well, but counting correct FP’s is critical to the whole system)
Inspite of these problems, FPA is a very useful tool, and probably a very good fitment for doing estimation.

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