[KSCI] Korea Science Citation Index Service

http://dx.doi.org/10.9708/jksci.2020.25.06.119

A Case Study on Function Point Method applying on Monte Carlo Simulation in Automotive Software Development

Do, Sung Ryong (Industry Academy Cooperation Foundation, SangMyung University)

Publication Information

Journal of the Korea Society of Computer and Information / v.25, no.6, 2020 , pp. 119-129 More about this Journal

Abstract

Software development activities are influenced by stochastic theory rather than deterministic one due to having process variability. Stochastic methods factor in the uncertainties associated with project activities and provides insight into the expected project outputs as probability distributions rather than as deterministic approximations. Thus, successful software projects systematically manage and balance five objectives based on historical probability: scope, size, cost, effort, schedule, and quality. Although software size estimation having much uncertainty in initial development has traditionally performed using deterministic methods: LOC(Lines Of Code), COCOMO(COnsructive COst MOdel), FP(Function Point), SLIM(Software LIfecycle Management). This research aims to present a function point method based on stochastic distribution and a case study based on Monte Carlo Simulation applying on an automotive electrical and electronics system software development. It is expected that the result of this paper is used as guidance for establishing of function point method in organizations and tools for helping project managers make decisions correctly.

Keywords

Function Point Method; Software Size Estimation; Monte Carlo Simulation; Quantitative Management; Stochastic Distribution;

Citations & Related Records

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