Empirical analysis of object-oriented design metrics for predicting high, medium and low severity faults using mallows Cp

Authors:
Rajender Singh Chhillar; Nisha
Affiliations:
Maharshi Dayanand University, Rohtak-124001 [Haryana], India;Govt. College for Women, Rohtak-124001 [Haryana] India
Venue:
ACM SIGSOFT Software Engineering Notes
Year:
2011

Citing 12
Cited 0

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Empirical Validation of Object-Oriented Metrics on Open Source Software for Fault Prediction

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Empirical Analysis of Object-Oriented Design Metrics for Predicting High and Low Severity Faults

IEEE Transactions on Software Engineering
Empirical validation of object-oriented metrics for predicting fault proneness models

Software Quality Control

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Abstract

An object-oriented approach has become a commonly-used method in software-related activities. Many design metrics for object-oriented systems have been proposed and also employed for predicting and managing the quality of processes and products. To enhance the practical utility of object-oriented metrics in software industry, various researchers have tried to find relations between these metrics and fault proneness, but very few focus on relating them with the number-offaults in different levels as per their severity rating. In this study, empirical validation is carried out on object-oriented design metrics (i.e. Chidamber and Kemerer CK-metrics suite and source lines of codes) for predicting number-of-faults in different severity levels. Different statistical methods are used to analyze the data, including correlation.