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Measuring the Software Process: Statistical Process Control for Software Process Improvement
Published:
1999
Pages:
0
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User Comments
As any engineer who works with the "manufacturing department" identified above will tell you, a "measurement" is a single number, a raw datum, one dimension of a vector. It is "metrics" that make measurement useful, by combining two or more measurements arithmetically to derive a metric.
A typical metric is a rate: number of labor hours to deliver one widget; number of defective widgets discovered in a batch of 1,000; number of customer complaints or returns per 1,000 widgets shipped. In other words, a typical metric is a fraction whose numerator or denominator is a measure of the quantity of product delivered.
One of the key differences between software engineering and manufacturing is that we do not deliver generic widgets. Almost every project has a unique deliverable. Therefore, in order to derive metrics, we need a unit of measurement that can be applied to unique deliverables rather than one that simply counts generic deliverables.
The cornerstone of any software metrics program is the Function Point methodology, which not only measures software with satisfactory accuracy but does so in units that can be understood in both the developer's and the end user's context.
This book appears to be well grounded in the SEI Capability Maturity Model, whose long-term goal is the "continual software process improvement based upon real measurement" noted by the reviewer. One would hope that it introduces the Function Point methodology to those who may not already be familiar with it -- a rather large percentage of the IT community. One would assume that the reviewer's failure to mention this merely reflects his own membership in the more enlightened community who have already adopted Function Points.