Function point distribution using maximum entropy principle

Abstract

Software cost is estimated through the effort and number of functioning components measured in terms of person month (p-m) and function points (FPs) respectively. In this paper we have considered the software cost based on the FPs because FPs is independent of the technologies. Initially function point analysis (FPA) was designed without any reference to the theoretical foundation which is based on the measurement done by the expert team. Function point data is described for more than hundred software development projects in the literature. It was also discussed about limitations of the resulting model in estimating development effort. This paper attempts to study and quantify the software cost in case of multiple projects or set of softwares. In case of single project or software, we attempt to study and quantify the function point counts (FPCs) for different components of the software or function types (FTs). Maximum Entropy Principle (MEP) is a very popular technique to estimate the maximum information or entropy subject to the given constraints. This paper presents an application of Maximum Entropy Principle (MEP) to distribute the Unadjusted Function Point Counts (UFPCs) subject to a given software cost. Thereafter, this application is applied over set of softwares to allocate the individual software cost when total cost to the software was given. In this paper we have also analyzed the proportionate of Unadjusted Function Point Counts (UFPCs), Number of FPs (# FPs), and weight of the different functional components or FTs for given software cost.