Providing a model to estimate the probability of the complexity of software projects
Function Point Analysis (FPA) is most used technique for estimating the size of a computerized business information system which was developed by Allan Albrecht. Various studies proposed new methods to extent FPA algorithm; mainly they tried to make it more precise but they are based on the similari...
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my.utm.381782017-10-25T03:33:32Z http://eprints.utm.my/id/eprint/38178/ Providing a model to estimate the probability of the complexity of software projects Marzoughi, Foad Farhangian, Mohammad Mehdi Sim, Alex Tze Hiang QA75 Electronic computers. Computer science Function Point Analysis (FPA) is most used technique for estimating the size of a computerized business information system which was developed by Allan Albrecht. Various studies proposed new methods to extent FPA algorithm; mainly they tried to make it more precise but they are based on the similarity of previous projects so this paper is proposed. This paper, presents a statistical simulation method that can be applied for each generic project. The proposed method is a new method to assess estimation of size and effort of software projects by a stochastic and Markov chain approach. Based on Metropolis-hasting simulation algorithm, we formulate a Probabilistic Function Point Analysis (PFPA). Moreover, A Bayesian belief network approach is used for determination of complexity of system. It determines the function weights utilizing Markov chain theory to support estimating the effort of software projects. As a case study, this new method is applied in online publication domain. This method can increase the chance of implementation of generic projects on time. Recent Science 2010 Article PeerReviewed Marzoughi, Foad and Farhangian, Mohammad Mehdi and Sim, Alex Tze Hiang (2010) Providing a model to estimate the probability of the complexity of software projects. International Journal of Computer and Network Security (IJCNS) , 2 (10). pp. 203-206. ISSN 0975-8283 |
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QA75 Electronic computers. Computer science Marzoughi, Foad Farhangian, Mohammad Mehdi Sim, Alex Tze Hiang Providing a model to estimate the probability of the complexity of software projects |
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Function Point Analysis (FPA) is most used technique for estimating the size of a computerized business information system which was developed by Allan Albrecht. Various studies proposed new methods to extent FPA algorithm; mainly they tried to make it more precise but they are based on the similarity of previous projects so this paper is proposed. This paper, presents a statistical simulation method that can be applied for each generic project. The proposed method is a new method to assess estimation of size and effort of software projects by a stochastic and Markov chain approach. Based on Metropolis-hasting simulation algorithm, we formulate a Probabilistic Function Point Analysis (PFPA). Moreover, A Bayesian belief network approach is used for determination of complexity of system. It determines the function weights utilizing Markov chain theory to support estimating the effort of software projects. As a case study, this new method is applied in online publication domain. This method can increase the chance of implementation of generic projects on time. |
format |
Article |
author |
Marzoughi, Foad Farhangian, Mohammad Mehdi Sim, Alex Tze Hiang |
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Marzoughi, Foad Farhangian, Mohammad Mehdi Sim, Alex Tze Hiang |
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Marzoughi, Foad |
title |
Providing a model to estimate the probability of the complexity of software projects
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title_short |
Providing a model to estimate the probability of the complexity of software projects
|
title_full |
Providing a model to estimate the probability of the complexity of software projects
|
title_fullStr |
Providing a model to estimate the probability of the complexity of software projects
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Providing a model to estimate the probability of the complexity of software projects
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title_sort |
providing a model to estimate the probability of the complexity of software projects |
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Recent Science |
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2010 |
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http://eprints.utm.my/id/eprint/38178/ |
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13.211869 |