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This paper explores software sizing at a finer level of granularity by taking into account the structural aspect of a sequence diagram in order to quantify its structural size.
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This paper explores the relationship between software size, development effort and team size.
We also find increasing returns to scale relationship between software size and team size with software development effort.
The models consist of specification-based software size metrics and development team's productivity metric.
With the explosion of software size, checking conformance of implementation to specification becomes an increasingly important but also hard problem.
There are a number of techniques used to derive software size, with function points being amongst the most documented.
Previous industry surveys have concluded that software size and cost estimation is a significant technical area of concern.
Their computational complexity is very high and dramatically increases with the software size, thus limiting their applications in practice.
In this paper we study whether software development effort exhibits Cobb Douglas functional form with respect to team size and software size.
The results of our experiments indicate that the hypothesized Cobb Douglas function form for software development effort with respect to team size and software size is true.
In this paper, we present a model for software effort (person-month) estimation based on three levels Bayesian network and 15 components of COCOMO and software size.
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