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Fuzzy Rules and SVM Approach to the Estimation of Use Case Parameters

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 237))

Abstract

Many decisions that are needed for the planning of the software development project are based on previous experience and competency of project manager. One of the most important questions is how much effort will be necessary to complete the task. In our case, the task is described by the use case and manger has to estimate the effort to implement it. However, such estimations are not always correct, not estimated extra work has to be done sometimes. Our intent is to support manager’s decision by the estimation tool that uses know parameters of the use cases to predict other parameters that has to be estimated. This paper focuses on the usage of our method on the real data and evaluates its results in real development. The method uses parameterized use case model trained from the previously done use cases to predict extra work parameter. Estimation of test use cases is done several times according to the managers needs during the project execution.

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Correspondence to Svatopluk Štolfa .

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Štolfa, S., Štolfa, J., Krömer, P., Koběrský, O., Kopka, M., Snášel, V. (2014). Fuzzy Rules and SVM Approach to the Estimation of Use Case Parameters. In: Abraham, A., Krömer, P., Snášel, V. (eds) Innovations in Bio-inspired Computing and Applications. Advances in Intelligent Systems and Computing, vol 237. Springer, Cham. https://doi.org/10.1007/978-3-319-01781-5_4

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  • DOI: https://doi.org/10.1007/978-3-319-01781-5_4

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-01780-8

  • Online ISBN: 978-3-319-01781-5

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