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

J. Softw. Evol. and Proc.

2015

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.

Section: Related Workmentioning

confidence: 99%

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

J. Softw. Evol. and Proc.

2015

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

2012

Softw Pract Exp

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.

Predicting object-oriented class reuse-proneness using internal quality attributes

Morasca

2012

Empir Software Eng

Class reuse-proneness is the likelihood that a class can be reused and is a key quality characteristic in object-oriented design. Because it is clearly impossible to know with certainty when, where, how, and how often a class will be reused, this likelihood can only be estimated when a class is developed. At that stage, the internal quality attributes of a class such as cohesion, coupling, and size can be measured. In this paper, we empirically study the ability of 29 internal class quality measures, individually and in combination, to estimate class reuse-proneness. Specifically, we take into account both class inheritance and class instantiation, which are two ways in which a class can be reused. Our results show that most of the considered measures are predictors for the considered reuseproneness attributes to some degree. The capability of the considered internal quality measures to predict class reuseproneness is enhanced when the measures are combined using an optimized multivariate statistical model. The results also show that the size and coupling attributes of a class have positive impacts on its reuse-proneness via inheritance and instantiation. The cohesion of a class has a negative impact on its inheritance reuse-proneness and a positive impact on its instantiation reuse-proneness. The overall results of the empirical study show that software developers can use a number of predictors to assess the reuse-proneness of classes and possibly improve the reuse-proneness of the classes by controlling their internal quality attributes. Our results contribute to the evaluation of the quality of a class, but a comprehensive evaluation of the quality of a class should take into account many more qualities. Also, not all classes in a software system are built with reuse-proneness in mind, so our results should be applied only to those that are designed and implemented to be reusable