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Function Point Analysis (FPA) was a valuable techniquedeveloped by A. J. Albrecht, in 1977. FPA assigns a point to each function in an application. Various modifiers then act upon the function points in order to adjust for the product environmental. Modifiers typically included applying weighted percentages or multipliers that would simply increase or decrease the point values. Environment factors included modifiers for complexity of technical issues, developer skill level, and risk. One problem organizations attempting to use this method would run into was consistent definition of a function and consistent definition of environmental factors across multiple projects and multiple development languages. In order to produce reliably accurate estimates, FPA relies heavily on historical data to derive weighting values and modifiers.

COCOMO (COnstructive COst MOdel) has been designed in 1981 by Barry Boehm to given an estimate of the number of man-months it will take to develop a software product and it is referred as COCOMO 81. A new model called COCOMO II was designed in 1990 and the need for this model came up as software development technology moved from mainframe and overnight batch processing to desktop development, code re-usability and the use of off-the-shelf software components. COCOMO used statistical returns to calculate project cost and duration within a given probability. The model sought to provide a tool for predictably estimating cost, and continues to evolve today under the sponsorship of the University of Southern California. The model was/is interesting and produced worthy merits in applying statistical analysis to the problem of cost estimating. However, a major defining point in statistics is sample set size. The underlying assumption for COCOMO (like FPA) is that a statistically significant