Aussie AI
Project Estimation
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Book Excerpt from "Generative AI in C++"
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by David Spuler, Ph.D.
Project Estimation
Estimating project time and space requirements is an important part of software project management. Although estimating the efficiency of a proposed project is important in ascertaining its feasibility, it is difficult to find anything concrete to say about arriving at these estimates. Producing advance estimates is more of an art than a science, and a typical process goes like this:
1. Pick a random date.
2. Deny programmers sleep until this date.
3. Slip the date.
4. Time-box out all useful features.
5. Ship it!
Experience is probably the best source of methods for producing an accurate estimate. Hence, it is wise to seek out others who have implemented a similar project, or to perform a literature search for relevant papers and books. Unfortunately, neither of these methods is guaranteed to succeed and the implementor may be forced to go it alone. The only other realistic means of estimation relies on a good understanding of the various data structures and algorithms that will be used by the program. Making realistic assumptions about the input can provide some means of examining the performance of a data structure. How a data structure performs under worst case assumptions may also be of great importance.
An alternative to these methods of plucking estimates out of the air is to code up a prototype version of the program, which implements only the most important parts of the project (especially those which will have the biggest impact). The efficiency of the prototype can then be measured using the various techniques. Even if the prototype is too inefficient, at least the problem has been identified early in the development cycle, when the investment in the project is relatively low.
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