• Journal of Korea Society of Digital Industry and Information Management
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• v.7 no.3
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• pp.37-42
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• 2011

Nowadays software developers are moving from conventional software process technologies to the object-oriented paradigm. To develope the object-oriented softwares efficiently, various software metrics have been suggested. Coupling refers to the degree of independence between components of the system. It has long been well known that good software practice calls for minimizing coupling interaction. Many researches have been studied coupling metrics of the object- oriented systems. We review Chidamber and Kemerer's work & Li's work. In this paper, we study the coupling of the overall structures of object-oriented systems by analyzing the class diagram of UML. We propose four coupling metrics for object-oriented softwares. First, we use an established coupling metric for object- oriented systems as a basic coupling metric. Then we modify the basic coupling metric by including indirect coupling between classes, We also suggest two relative coupling metrics to measure coupling between subsystems. We investigate the theoretical soundness of the proposed metrics by the axioms of Briand et al. Finally, we apply the presented metrics to a practical case study. This coupling metric will be helpful to the software developers for their designing tasks by evaluating the coupling metric of the structures of object-oriented system and redesigning tasks of the system.

• Journal of Information Technology Services
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• v.10 no.4
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• pp.219-227
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• 2011

Service Oriented Architecture (SOA) is rapidly emerging as the efficient approach in contemporary complex, heterogeneous computing environments. SOA increases the adaptability by loose coupling and its main feature is that three elements such as service provider, service requester and service registry are connected with each other systematically. To design the service-oriented system efficiently, a metric to measure the coupling between services accurately is needed. In this paper, we propose four coupling metrics for SOA based softwares. First, we suggest a coupling metric for service-oriented systems by modifying an established coupling metric of object-oriented systems. Then we suggest another coupling metric which includes indirect coupling between services. We also suggest two relative coupling metrics to measure coupling between subsystems. We investigate the theoretical soundness of the proposed metrics by the axioms of Briand et al. Finally, we apply the presented metrics to an industrial-scale case study.

• Journal of the Korea Society of Computer and Information
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• v.12 no.3
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• pp.75-84
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• 2007

Due to the increasing complexity and shorter life cycle of web applications, web applications need to be restructured to improve flexibility and extensibility. These days approaches are being used where systems are understood and restructured through clustering techniques. In this paper, the coupling metrics are proposed for clustering web pages more effectively. To achieve this, web application models are defined, where the relationship between web pages and the numbers of parameters are included. Considering direct and indirect coupling strength based on these models, coupling metrics are defined. The more direct relations between two pages and the more parameters they have, the stronger direct coupling is. The higher indirect connectivity strength between two pages is, the more similar the patterns of relationships among other web pages are. We verify the suggested metrics according to the well known verification framework and provide a case study to show that our metrics complements some existing metrics.

• Journal of KIISE:Software and Applications
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• v.27 no.6
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• pp.595-606
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• 2000

Software metrics evaluate the development process, measure the software development effort, and control the software quality effectively. Moreover in a current status to emphasize reusability, it is necessary to study of cohesion and coupling that plays an important role in evaluating reusability. Object oriented methodology to use the concept like encapsulation, inheritance, and polymorphism demands metrics that are different from existing procedural methodology, so a study for object oriented metrics is in progress at the present time. In this paper, we propose cohesion and coupling metrics for object oriented program, evaluate the proposed metrics by using the complexity properties proposed by Weyuker and Briand, and extract cohesion and coupling from C++ code.

• The KIPS Transactions:PartD
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• v.10D no.5
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• pp.745-752
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• 2003

The component-based development methodology becomes famous as the reuse technology for independence and productivity of software development It is necessary component metrics for component-based systems, because It should be measurable to improve the quality of the software. Hence, in this paper, we propose component cohesion and coupling metrics which is reflected in characteristics of component. The operation use value is calculated by the information of classes interface commonly uses to offer the component's service. And, the operation similarity value is calculated by the operations use value. Component cohesion and coupling is calculated by the operation similarity and based of the information which is extracted in the analysis phase. And, we examine the necessity of component metrics in comparison with object-oriented metrics.

• The Journal of Society for e-Business Studies
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• v.15 no.2
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• pp.19-35
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• 2010

In response to an increased need, various methods for ontology modularization have been proposed. However, few studies have focused on evaluative methods for ontology modules. In this study, we devise novel metrics to measure ontology modularity. To evaluate the ontology modules, we introduce cohesion and coupling based on the theory of software metrics. A cohesion metric and two coupling metrics were used to measure cohesion and coupling for ontology modules. These metrics were also used to check consistency between the ontology modules and the original ontology. The new metrics support a more detailed relationship between classes in ontology modules. We validate the proposed metrics using the well known verification framework and perform the empirical experiments to complement previous investigations. This study offers ontology engineers valuable criteria with which to select and use ontology modules and modularization techniques.

• Journal of Applied Reliability
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• v.16 no.1
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• pp.48-55
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• 2016

Purpose: The purpose of this study is to identify the object-oriented metrics which have strong impact on the reliability and fault-proneness of software products. The reliability and fault-proneness of software product is closely related to the design properties of class diagrams such as coupling between objects and depth of inheritance tree. Methods: This study has empirically validated the object-oriented metrics to determine which metrics are the best to predict fault-proneness. We have tested the metrics using logistic regressions and artificial neural networks. The results are then compared and validated by ROC curves. Results: The artificial neural network models show better results in sensitivity, specificity and correctness than logistic regression models. Among object-oriented metrics, several metrics can estimate the fault-proneness better. The metrics are CBO (coupling between objects), DIT (depth of inheritance), LCOM (lack of cohesive methods), RFC (response for class). In addition to the object-oriented metrics, LOC (lines of code) metric has also proven to be a good factor for determining fault-proneness of software products. Conclusion: In order to develop fault-free and reliable software products on time and within budget, assuring quality of initial phases of software development processes is crucial. Since object-oriented metrics can be measured in the early phases, it is important to make sure the key metrics of software design as good as possible.

• The KIPS Transactions:PartD
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• v.11D no.3
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• pp.625-634
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• 2004

When constructing a component based system, It is understood that identifying reusable and independent business components is of utmost importance. However, according to conventional component based developing methodologies, most of developers depend on their experience and/or intuition for identification of business components. Furthermore, there are no criteria to evaluate whether the identified business components are more independently defined or not. Therefore, we propose a component identification metrics to apply to component properties In order to complement the difficulties of identifying business components through developers' experience and/or intuition. The metrics defined are the criteria for identifying the business Components and/or for evaluating the Identified components. We propose both a cohesion metric, and a coupling metric, to which component properties are applied, wherein those properties can be understood by high cohesion in, and low coupling between, components. Moreover, we propose an independence metric that can evaluate the degree of independence for a particular component by ratio of the cohesion and coupling of components. The metrics that we propose are applied to case study which demonstrates the identification of more independent business components and the validity of our metrics.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.1
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• pp.81-85
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• 2008

The coupling measurements of object oriented programs can be valuable information for various maintenance tasks and there exists a variety of metrics proposed by numerous researchers. Those metrics, however, cannot measure the strength of dependencies between classes, but only imply the existence of dependencies. Hence they are of limited value for assisting maintenance tasks such as refactoring and system decomposition, which requires information about the strength of dependency. In this paper, a coupling metric which can measure the strength of dependence as well as detect the existence of dependencies is proposed. Our coupling metric is evaluated based on the cost required for performing the maintenance tasks. We have applied the proposed coupling metric to an example of system decomposition in an effort to assess the potential benefits of our approach for maintenance tasks.

• The KIPS Transactions:PartD
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• v.12D no.4 s.100
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• pp.609-616
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• 2005

The component-based development methodology becomes famous as the reuse technology to improve the high productivity of software development. It is necessary component metrics for component-based systems, because the designed components should be measurable to improve the quality of the software. Therefore this paper propose a coupling metric for component design which is reflected in characteristics of component. This paper suggest a case study and comparative analysis result about conventional metrics to verify the accuracy of our coupling metric. The Uoposed coupling metric measure the quality of components accurately and satisfies necessary conditions of coupling metric suggested by Briand and others.