Source and Test Code Size Prediction - A Comparison between Use Case Metrics and Objective Class Points
Mourad Badri, Linda Badri, William Flageol
2016
Abstract
Source code size, in terms of SLOC (Source Lines of Code), is an important parameter of many parametric software development effort estimation methods. Moreover, test code size, in terms of TLOC (Test Lines of Code), has been used in many studies to indicate the effort involved in testing. This paper aims at comparing empirically the Use Case Metrics (UCM) method, a use case model based method that we proposed in previous work, and the Objective Class Points (OCP) method in terms of early prediction of SLOC and TLOC for object-oriented software. We used both simple and multiple linear regression methods to build the prediction models. An empirical comparison, using data collected from four open source Java projects, is reported in the paper. Overall, results provide evidence that the multiple linear regression model, based on the combination of the use case metrics, is more accurate in terms of early prediction of SLOC and TLOC than: (1) the simple linear regression models based on each use case metric, and (2) the simple linear regression model based on the OCP method.
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Paper Citation
in Harvard Style
Badri M., Badri L. and Flageol W. (2016). Source and Test Code Size Prediction - A Comparison between Use Case Metrics and Objective Class Points . In Proceedings of the 11th International Conference on Evaluation of Novel Software Approaches to Software Engineering - Volume 1: ENASE, ISBN 978-989-758-189-2, pages 172-180. DOI: 10.5220/0005857601720180
in Bibtex Style
@conference{enase16,
author={Mourad Badri and Linda Badri and William Flageol},
title={Source and Test Code Size Prediction - A Comparison between Use Case Metrics and Objective Class Points},
booktitle={Proceedings of the 11th International Conference on Evaluation of Novel Software Approaches to Software Engineering - Volume 1: ENASE,},
year={2016},
pages={172-180},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005857601720180},
isbn={978-989-758-189-2},
}
in EndNote Style
TY - CONF
JO - Proceedings of the 11th International Conference on Evaluation of Novel Software Approaches to Software Engineering - Volume 1: ENASE,
TI - Source and Test Code Size Prediction - A Comparison between Use Case Metrics and Objective Class Points
SN - 978-989-758-189-2
AU - Badri M.
AU - Badri L.
AU - Flageol W.
PY - 2016
SP - 172
EP - 180
DO - 10.5220/0005857601720180