New Quality Inheritance Metrics for Object-Oriented Design

Mal, Sandip; Rajnish, Kumar

doi:10.14257/ijseia.2013.7.6.16

Cited by 11 publications

(7 citation statements)

References 13 publications

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“…In this paper an attempt has been made to present a theoretical evaluation on Inheritance Metrics proposed by Rajnish et al [5][6] and Sandip et al [3][4] satisfy necessary properties of Briand et al [2]. At the end of this paper in Appendix B, summarizes the results found in this paper and another related paper [7].…”

Section: Conclusion and Future Scopementioning

confidence: 89%

“…This section presents the brief description of Depth of Inheritance Tree of a Class (DITC) metric and Class Inheritance Tree (CIT) metric presented by Rajnish et al [5][6] AND ICC (Inheritance Complexity of Class), and ICT (Inheritance Complexity of Tree) presented by Sandip et al [3][4] for evaluation.…”

Section: Inheritance Metrics For Evaluationmentioning

confidence: 99%

“…Metrics exist for measurement of inheritance at the higher levels of abstraction in OO systems has been given in [3][4][5][6]. Rajnish had presents a new class complexity metric of an OO program which is used to predict the understandability of classes in software projects.…”

Section: Introductionmentioning

confidence: 99%

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Theoretical Validation of Inheritance Metrics for Object-Oriented Design against Briand's Property

Rajnish

2014

IJIEEB

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Abstract-Many inheritance metrics can be found in the literature, but most of those are validated theoretically by using Weyuker's property. Theoretical validation of inheritance metrics using Briand's property is rare in the literature. This paper considers the metrics proposed by Rajnish and Sandip and presents a theoretical validation of the inheritance metrics using the Briand's size and length properties of an inheritance hierarchy. This paper also gives the projection and viewpoint of the inheritance metrics.

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Section: Conclusion and Future Scopementioning

confidence: 89%

Section: Inheritance Metrics For Evaluationmentioning

confidence: 99%

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Theoretical Validation of Inheritance Metrics for Object-Oriented Design against Briand's Property

Rajnish

2014

IJIEEB

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“…6) Number of Methods Overridden (NMO) [56], [57]. A larger quantity of methods overridden points out a issue in design, signaling these methods overridden as a lastminute design.…”

Section: ) Number Of Methods Inherited (Nmi)mentioning

confidence: 99%

Efficacy of Inheritance Aspect in Software Fault Prediction—A Survey Paper

2020

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Software fault prediction (SFP) is a research area that helps development and testing process deliver software of good quality. Software metrics are of various types and are used in SFP for measurements. Inheritance is a prominent feature, which measures the depth, breadth, and complexity of object-oriented software. A few studies exclusively addressed the efficacy of inheritance in SFP. This provokes the need to identify the potential ingredients associated with inheritance, which can be helpful in SFP. In this paper, our aim is to collecting, organizing, categorizing, and investigating published fault prediction studies. Findings include identification of 54 inheritance metrics, 78 public datasets with various combinations of 10 inheritance metrics, 60% use of method level & use of private datasets, an increased number of studies using machine learning approaches. This study will facilitate scholars to studying previous literature on software fault prediction having software metrics, with their methods, public data sets, performance evaluation of machine learning algorithms, and findings of experimental results in a comfortable, and efficient way, emphasizing the inherited aspect specifically.

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“…Interface metrics measure the complexity of communicating modules, whereas Dynamic metrics measure the software quality as it is executed. Sandip et al [22][23] presented in his paper to analytically evaluate against the Weyuker's property [24] and empirically validate a proposed inheritance metrics (against a three versions of the same project) that can be used to measure the quality (especially focus on the quality factors -Reuse‖ and -Design Complexity‖) of an OO systems in terms of the using class inheritance tree.…”

Section: Introductionmentioning

confidence: 99%

Class Complexity Metric to Predict Understandability

Rajnish

2014

IJIEEB

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-This paper presents a new class complexity metric of an Object-Oriented (OO) program which is used to predict the understandability of classes. The propose complexity metric is evaluated theoretically against Weyuker's properties to analyze the nature of metric and empirically evaluated against three small projects developed by Post Graduate (PG)/Under Graduate (UG) teams. Least Square Regression Analysis technique is performed to arrive at the result and find correlation coefficient of propose metric with the Degree of Understandability. The result indicates that the propose metric is a good predictor of understandability of classes. JHAWK TOOL (Java Code Metrics Tool) were used to evaluate the parameters values involved in propose metric and for analyzing the results of projects, Matlab6.1 and IBM SPSS software were used.

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New Quality Inheritance Metrics for Object-Oriented Design

Cited by 11 publications

References 13 publications

Theoretical Validation of Inheritance Metrics for Object-Oriented Design against Briand's Property

Theoretical Validation of Inheritance Metrics for Object-Oriented Design against Briand's Property

Efficacy of Inheritance Aspect in Software Fault Prediction—A Survey Paper

Class Complexity Metric to Predict Understandability

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