The Software Development Effort Estimation Exponent: An Effort Estimation Model Accounting for Learning and Integration

The study of estimation of the effort required for software development has progressed to the point where most currently used models employ an equation of the form y = ax°, which relates the effort to the lines of code, or size of a program, exponentially through a constant, e. That constant, e, the effort estimation exponent, has been referred to as an entropy constant by Randall Jensen1 and is the subject of many analyses, both theoretical and empirical, to estimate its value. In fact, many models indicate that its value is greater than one, meaning that the effort estimation curve bends upward, or that larger programs take proportionally more effort to develop. Yet, some estimates of the exponent’s value are less than one, and some SEL experience indicates a value of 0.92 and a curve that bends downward. This implies that larger programs take proportionally less effort to develop. Furthermore, if an exponent greater than one is employed, then the effort estimated to develop a large program will be greater than the sum of the effort required to develop each of its submodules individually.