Improving estimation accuracy prediction of software development effort: a proposed ensemble model

Software effort estimation is an essential feature of software engineering for effective planning, controlling and delivering successful software projects. The overestimation and underestimation both are the key challenges for future software development. The failure to acknowledge the effort estima...

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Bibliographic Details
Main Authors: Mahmood, Y., Kama, N., Azmi, A., Ali, M.
Format: Conference or Workshop Item
Language:English
Published: 2020
Subjects:
Online Access:http://eprints.utm.my/id/eprint/92900/1/YasirMahmood2020_ImprovingEstimationAccuracyPrediction.pdf
http://eprints.utm.my/id/eprint/92900/
http://dx.doi.org/10.1109/ICECCE49384.2020.9179279
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Summary:Software effort estimation is an essential feature of software engineering for effective planning, controlling and delivering successful software projects. The overestimation and underestimation both are the key challenges for future software development. The failure to acknowledge the effort estimation accuracy may lead to customer disappointment, inaccurate estimation and hence, contribute to either poor software development process or project failure. The main aim of this research is to optimize the estimation accuracy prediction of software development effort to support software development firms and practitioners. In this paper, we propose an ensemble software effort estimation model based on Use Case Points (UCP), expert judgment and Case-Based Reasoning (CBR) techniques. This research is conducted through primary (a multi-case involving software companies) study to make an ensemble model. The estimation accuracy prediction of the proposed model will be evaluated by selecting projects from primary studies as case selections in applying a quantitative approach through industrial experts, archival data about estimates and evaluation metrics. The proposed model produced at the end of this research will be used by software development firms and practitioners as an instrument to estimate the effort required to develop new software projects at an earlier stage.