SOFTWARE PROJECT ESTIMATION

Software cost and effort estimation will never be an exact science. Too many variables—
human, technical, environmental, political—can affect the ultimate cost of
software and effort applied to develop it. However, software project estimation can
be transformed from a black art to a series of systematic steps that provide estimates
with acceptable risk.
To achieve reliable cost and effort estimates, a number of options arise:
1. Delay estimation until late in the project (obviously, we can achieve
100% accurate estimates after the project is complete!).
2. Base estimates on similar projects that have already been completed.
3. Use relatively simple decomposition techniques to generate project cost and
effort estimates.
4. Use one or more empirical models for software cost and effort estimation.
Unfortunately, the first option, however attractive, is not practical. Cost estimates
must be provided "up front." However, we should recognize that the longer we wait,
the more we know, and the more we know, the less likely we are to make serious
errors in our estimates.
The second option can work reasonably well, if the current project is quite similar
to past efforts and other project influences (e.g., the customer, business conditions,
the SEE, deadlines) are equivalent. Unfortunately, past experience has not
always been a good indicator of future results.
The remaining options are viable approaches to software project estimation. Ideally,
the techniques noted for each option should be applied in tandem; each used as a cross-check for the other. Decomposition techniques take a "divide and conquer"
approach to software project estimation. By decomposing a project into major functions
and related software engineering activities, cost and effort estimation can be
performed in a stepwise fashion. Empirical estimation models can be used to complement
decomposition techniques and offer a potentially valuable estimation
approach in their own right. A model is based on experience (historical data) and
takes the form
d = f (vi)
where d is one of a number of estimated values (e.g., effort, cost, project duration)
and vi are selected independent parameters