A Hybrid Complexity Metric in Automatic Software Defects Prediction

Laura Cernău, Laura Dioșan, Camelia Șerban

2022

Abstract

Nowadays, software systems evolve in vast and complex applications. In such a complex system, a minor change in one part may have unexpected degradation of the software system design, leading to an unending chain of bugs and defects. Therefore, to keep track of implications that could appear after a change has been applied, the assessment of the software system is of utmost importance. As a result, in this direction, software metrics are suitable for quantifying various aspects of system complexity and predicting as early as possible those parts of the system that could be error-prone. Thus, in this paper, we propose a comparative study of two complexity metrics, Weighted Method Count and Hybrid Cyclomatic Complexity, regarding the prediction of software defects. Specifically, the objective is to investigate whether using a hybrid metric that measures the complexity of a class improves the performance of the fault prediction model. We conduct a series of several experiments on five open source projects datasets. The preliminary results of our research indicate that the proposed metric performs better than the standard complexity metric of a class, Weighted Method Count. Moreover, the Hybrid Cyclomatic Complexity metric can be seen as a base for building a more complex and robust complexity metric.

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Paper Citation


in Harvard Style

Cernău L., Dioșan L. and Șerban C. (2022). A Hybrid Complexity Metric in Automatic Software Defects Prediction. In Proceedings of the 17th International Conference on Software Technologies - Volume 1: ICSOFT, ISBN 978-989-758-588-3, pages 433-440. DOI: 10.5220/0011269700003266


in Bibtex Style

@conference{icsoft22,
author={Laura Cernău and Laura Dioșan and Camelia Șerban},
title={A Hybrid Complexity Metric in Automatic Software Defects Prediction},
booktitle={Proceedings of the 17th International Conference on Software Technologies - Volume 1: ICSOFT,},
year={2022},
pages={433-440},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011269700003266},
isbn={978-989-758-588-3},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Conference on Software Technologies - Volume 1: ICSOFT,
TI - A Hybrid Complexity Metric in Automatic Software Defects Prediction
SN - 978-989-758-588-3
AU - Cernău L.
AU - Dioșan L.
AU - Șerban C.
PY - 2022
SP - 433
EP - 440
DO - 10.5220/0011269700003266