Use Of Genetic Algorithm In Generating Internal Logical Files Complexity Weights For Function Point Analysis

Zahriah, Sahri (2005) Use Of Genetic Algorithm In Generating Internal Logical Files Complexity Weights For Function Point Analysis. Masters thesis, UPM.

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Genetic Algorithms (GA) are stochastic search techniques for approximating optimal solutions within complex search spaces (Goldberg 1989). The technique is based upon an analogy with biological evolution, in which the fitness or individual determines its ability to survive and reproduce. GA in various forms have been applied to many scientific and engineering problems. They have been used in a wide variety or optimization tasks. including numerical optimization and combinatorial optimization Function Point Analysis was de eloped first by Allan J. Albrecht in the mid 1970s. It' as an attempt to overcome difficulties associated with lines or code as a measure or software size. and to assist in developing a mechanism to predict effort associated with software development. The method was first published in 1979. then later in 1983 . In 1984 Albrecht refined the method and since 1986, when the International Function Point User Group (IFPUG) ' as set up. several versions of the Function Point Counting Practices Manual have been published by IFPUG. The purpose of this project will be to establish a new Internal Logical Files ILF complexity weights of FP based on Genetic Algorithm (GA) technique.

Item Type: Thesis (Masters)
Uncontrolled Keywords: Genetic algorithms, Evolutionary programming (Computer science)
Subjects: Q Science > Q Science (General)
Q Science > QA Mathematics
Divisions: Library > Tesis > FTMK
Depositing User: Siti Syahirah Ab Rahim
Date Deposited: 08 Jul 2014 06:36
Last Modified: 28 May 2015 04:27
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