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Empirical Estimation

In this model, empirically derived formulas are used to predict data that are a required part of the software project-planning step. The empirical data are derived from a limited sample of projects.

Resource models consist of one or more empirically derived equations. These equations are used to predict effort (in person-month), project duration, or other pertinent project data. There are four classes of resource models:

• Static single-variable models

• Static multivariable models

• Dynamic multivariable models

• Theoretical models

Static single-variable model has the following form

Resource = c1 X (estimated characteristics c2)

Where,
Resource could be effort, project duration, staff size, or lines of software documentation.

c1 and c2 are constants derived from data of past projects.

Estimated characteristics is line of code, effort (if estimated), or other software characteristics.

The basic version of the Constructive Cost Model, or COCOMO, presented in the next section is an example of a static-variable model.

Static multivariable models also use historical data to derive empirical relationships. A typical model of this category takes the form

Resource = c11e1 + c12e2+ .................

Where ei is the ith software characteristics and ci1,ci2 are empirically derived constants for the ith characteristics.

In dynamic multivariable models, resource requirements are projected as a function of time. If the model is derived empirically, resources are defined in a series of time steps that allocate some percentage of effort (or other resource) to each step in the software engineering process. Further, each step may be divided into tasks. A theoretical approach to dynamic multivariable modeling hypothesizes a continuous "resource expenditure curve" and from it, derives equations that model behavior of the resource.


  

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