Class Cohesion Measures Research Articles

Exploring community structure of software Call Graph and its applications in class cohesion measurement

Many complex networked systems exhibit natural divisions of network nodes. Each division, or community, is a densely connected subgroup. Such community structure not only helps comprehension but also finds wide applications in complex systems. Software networks, e.g., Class Dependency Networks, are such networks with community structures, but their characteristics at the function or method call granularity have not been investigated, which are useful for evaluating and improving software intra-class structure. Moreover, existing proposed applications of software community structure have not been directly compared or combined with existing software engineering practices. Comparison with baseline practices is needed to convince practitioners to adopt the proposed approaches. In this paper, we show that networks formed by software methods and their calls exhibit relatively significant community structures. Based on our findings we propose two new class cohesion metrics to measure the cohesiveness of object-oriented programs. Our experiment on 10 large open-source Java programs validate the existence of community structures and the derived metrics give additional and useful measurement of class cohesion. As an application we show that the new metrics are able to predict software faults more effectively than existing metrics.

Accounting for data encapsulation in the measurement of object-oriented class cohesion

Intuitively, in a certain class, a pair of methods that share an attribute of an object type is potentially more cohesive than those that share an attribute of a primitive type because the attribute of a reference type could implicitly refer to multiple data. Existing class cohesion measures ignore the implicit access to or sharing of attributes due to the encapsulation feature. As a result, the obtained cohesion values can be inaccurate and could lead to incorrect quality indications. This paper aims at demonstrating how to account for data encapsulation DE in cohesion measurement and reports empirical studies that investigate the impact of considering DE in cohesion measurement on cohesion values and the abilities of cohesion measures to predict class fault proneness. To differentiate between attributes and parameters of different types, we propose a weight assignment algorithm. The weight that is assigned to an attribute or a parameter of a type depends on the number of encapsulated attributes of the type. Seven cohesion measures are extended to consider the assigned weights in cohesion measurement. The results of the empirical study show that the cohesion values and the corresponding fault-proneness prediction results can significantly change when accounting for DE in cohesion measurement. Copyright © 2015 John Wiley & Sons, Ltd.

Effects of incorporating special methods into cohesion measurement on class instantiation reuse‐proneness prediction

The previously proposed class cohesion measures employ different approaches to assess the strength of the relations between the attributes and methods in a class. Access methods, constructors and destructors are special types of methods with special characteristics that can falsely alter the class cohesion measurement. In this study, the authors empirically explored the impact of considering special methods (SPs) on the cohesion measures’ abilities to predict the classes that can be intensively reused via instantiation (IRI). They considered classes in the JHotDraw and Eclipse systems. For each class, they obtained cohesion results using 17 measures in four different scenarios of considering or ignoring SPs. They collected the instantiation reusability data and applied a statistical technique to build a prediction model using each measure in each considered scenario. They investigated the significance of the changes in the prediction results. The authors’ results demonstrated that cohesion had a negative impact on class instantiation reuse-proneness and that SPs had significant impacts on cohesion values and the abilities of the cohesion measures to predict IRI classes. In practice, when applying cohesion measures to predict IRI classes, the results suggest that SPs must be included in cohesion measurement.

Qualitative Analysis for the Impact of Accounting for Special Methods in Object-Oriented Class Cohesion Measurement

Class cohesion is a key object-oriented software quality attribute. It refers to the degree of relatedness of class attributes and methods. Several class cohesion metrics are proposed in the literature. However, the impact of considering the special methods (i.e., constructors, destructors, and access and delegation methods) in cohesion calculation is not thoroughly theoretically studied for most of the existing cohesion metrics. An incorrect determination of whether to include or exclude the special methods in cohesion measurement can lead to improper refactoring decisions according to the misleading class cohesion values that are obtained. In this paper, we qualitatively analyze the impact of including or excluding the special methods in cohesion measurement on the values that are obtained by applying 19 popular class cohesion metrics. The study is based on analyzing the definitions and formulas that are proposed for the metrics. The results show that including/excluding special methods has a considerable effect on the cohesion values that are obtained and that this effect varies from one metric to another. The study shows the importance of considering the types of methods that must be accounted for when proposing a cohesion metric.

Incorporating transitive relations in low‐level design‐based class cohesion measurement

SUMMARYClass cohesion metrics apply different approaches to quantify the relatedness of the attributes and methods in a class. These relations can be direct or transitive. Method invocations are among the key sources of potential transitive attribute–method relations. That is, a method is not only related to the attributes that it references, but it may also be transitively related to the attributes referenced by the methods that it invokes. A few of the existing class cohesion metrics capture this potential transitive cohesion aspect. In this paper, we classify the method invocations as direct or transitive. The definitions of the class representative models used by 16 existing low‐level design (LLD) metrics are extended to incorporate the cohesion caused by the two types of method invocations. The impact of incorporating the transitive relations because of the two types of method invocations on the cohesion values and on the ability of the LLD metrics to predict faulty classes are studied empirically. The results show that the transitive relations because of both types of method invocations featured a considerable degree of cohesion that is not captured by most of the existing LLD metrics. However, practically, incorporating transitive relations in cohesion measurement was found to be ineffective in improving the fault‐prediction powers of most of the LLD metrics. Copyright © 2012 John Wiley & Sons, Ltd.

The impact of accounting for special methods in the measurement of object-oriented class cohesion on refactoring and fault prediction activities

Class cohesion is a key attribute that is used to assess the design quality of a class, and it refers to the extent to which the attributes and methods of the class are related. Typically, classes contain special types of methods, such as constructors, destructors, and access methods. Each of these special methods has its own characteristics, which can artificially affect the class cohesion measurement. Several metrics have been proposed in the literature to indicate class cohesion during high- or low-level design phases. The impact of accounting for special methods in cohesion measurement has not been addressed for most of these metrics. This paper empirically explores the impact of including or excluding special methods on cohesion measurements that were performed using 20 existing class cohesion metrics. The empirical study applies the metrics that were considered to five open-source systems under four different scenarios, including (1) considering all special methods, (2) ignoring only constructors, (3) ignoring only access methods, and (4) ignoring all special methods. This study empirically explores the impact of including special methods in cohesion measurement for two applications of interest to software practitioners, including refactoring and predicting faulty classes. The results of the empirical studies show that the cohesion values for most of the metrics considered differ significantly across the four scenarios and that this difference significantly affects the refactoring decisions, but does not significantly affect the abilities of the metrics to predict faulty classes.

DMC: a more precise cohesion measure for classes

In object-oriented systems, a single class consists of attributes and methods and its cohesion denotes the degree of relatedness among these elements. To quantify the cohesiveness of a class, a large number of measures that only depict method–attribute reference relationships have been proposed in last decade. However, the flow-dependence relationships among attributes, the direction of method–attribute references, and the potential dependence relationships among the elements in the class are ignored. To address this problem, this paper first depicts four types of explicit dependence relationships and uses a class element dependence graph to represent all dependencies among the elements in a class. Then, a dependence matrix that reflects the degree of direct dependence and indirect dependence among the elements in a class is computed. Finally, a more precise cohesion measure for classes is proposed.

A comparative study of graph theory-based class cohesion measures

Among a large number of cohesion measures for classes proposed in last decade, many measures abstract a class by an undirected or directed graph, in which the nodes represent the class members and the edges represent the relationships among these members. This paper compares six typical graph theory-based cohesion measures for classes, and states what problems should be addressed during the development of new cohesion measures.

More comments on ‘A cohesion measure for object‐oriented classes’ by Heung‐Seok Chae, Yong‐Rae Kwon and Doo‐Hwan Bae (Softw. Pract. Exper. 2000; 30:1405–1431)

AbstractChae et al. believe that the improved CBMC measures class cohesion from the viewpoint of the usage criteria of instance variables and that it cannot allow meaningful interpretations about classes. This paper exemplifies that it characterizes the interaction patterns better than the original one does and that it could also be used as a guideline for quality evaluation so as to enable the restructuring of poorly designed classes. Copyright © 2003 John Wiley & Sons, Ltd.

Response to ‘More comments on: A cohesion measure for object‐oriented classes’

AbstractThe authors insist that monotonicity is a necessary property of a good cohesion metric and the violation of the monotonicity property limits the application of CBMC. They also state that the augmented CBMC can also be used as a guideline for quality evaluation and restructuring of poorly designed classes. This paper raises the question about the necessity of monotonicity by analyzing the reason that causes CBMC to violate the monotonicity property. In addition, we give a detailed description of the restructuring procedure based on CBMC. Copyright © 2003 John Wiley & Sons, Ltd.

A framework to measure class cohesion

Classes are the basic modules in Object-Oriented (OO) software, which consist of attributes and methods. Thus, in OO environment, the cohesion is mainly about how tightly the attributes and methods of classes cohere with each other. This letter discusses the relationships between attributes and attributes, attributes and methods, methods and methods of a class, and the properties of these relationships. Based on these properties, the letter proposes a new framework to measure the cohesion of a class. The approach overcomes the limitations of previous class cohesion measures, which consider only one or two of the three relationships in a class.

Comments on ‘A cohesion measure for object‐oriented classes’ by Heung Seok Chae, Yong Rae Kwon and Doo Hwan Bae (Softw. Pract. Exper. 2000; 30:1405–1431)

AbstractAlthough H. S. Chae's class cohesion measure considers not only the number of interactions, but also the patterns of the interactions among the constitute members of a class (which overcomes the limitations of previous class cohesion measures) it, however, only partly considers the patterns of interactions, and might cause the measuring results to be inconsistent with intuition in some cases. This paper discusses the demerits and proposes constructive amendments to Chae's cohesion measure. Copyright © 2001 John Wiley & Sons, Ltd.

A cohesion measure for object-oriented classes

In object-oriented systems, cohesion refers to the degree of the relatedness of the members in a class and strong cohesion has been recognized as a highly desirable property of classes. We note that the existing cohesion measures do not take into account some characteristics of classes, and thus often fail to properly reflect the cohesiveness of classes. To cope with such a problem, we propose a new cohesion measure where the characteristics of classes are incorporated. Our cohesion measure takes into account the members that actually have impact on the cohesiveness of a class, and is defined in terms of the degree of the connectivity among those members. We develop a cohesion measurement tool for C++ programs, and perform a case study on a well-known class library in order to demonstrate the effectiveness of our new measure. By performing principal component analysis, we also demonstrate that our measure captures a new aspect of class properties which is not captured by the existing cohesion measures. Copyright © 2000 John Wiley & Sons, Ltd.