2014 | OriginalPaper | Chapter
Fuzzy Rules and SVM Approach to the Estimation of Use Case Parameters
Authors : Svatopluk Štolfa, Jakub Štolfa, Pavel Krömer, Ondřej Koběrský, Martin Kopka, Václav Snášel
Published in: Innovations in Bio-inspired Computing and Applications
Publisher: Springer International Publishing
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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.