The decomposition techniques and empirical estimation models are available as part of a wide variety of software tools. These automated est...
The decomposition techniques and empirical estimation models are available as part of a wide variety of software tools. These automated estimation tools allow the planner to estimate cost and effort and to perform "what-if" analyses for important project variables such as delivery date or staffing.
Although many automated estimation tools exist, all exhibit the same general characteristics and all perform the following six generic functions [JON96]:
1. Sizing of project deliverables. The “size” of one or more software work products is estimated. Work products include the external representation of software (e.g., screen, reports), the software itself (e.g., KLOC), functionality delivered (e.g., function points), descriptive information (e.g. documents).
2. Selecting project activities. The appropriate process framework is selected and the software engineering task set is specified.
3. Predicting staffing levels. The number of people who will be available to do the work is specified. Because the relationship between people available and work (predicted effort) is highly nonlinear, this is an important input.
4. Predicting software effort. Estimation tools use one or more models that relate the size of the project deliverables to the effort required to produce them.
5. Predicting software cost. Given the results of step 4, costs can be computed by allocating labor rates to the project activities noted in step 2.
6. Predicting software schedules. When effort, staffing level, and project activities are known, a draft schedule can be produced by allocating labor across software engineering activities based on recommended models for effort distribution .
When different estimation tools are applied to the same project data, a relatively large variation in estimated results is encountered. More important, predicted values sometimes are significantly different than actual values. This reinforces the notion that the output of estimation tools should be used as one "data point" from which estimates are derived—not as the only source for an estimate.
