The quality of a software system is partially determined by its structure（topological structure）,so the need to quantitatively analyze the quality of the structure has become eminent.In this paper a novel metric cal...The quality of a software system is partially determined by its structure（topological structure）,so the need to quantitatively analyze the quality of the structure has become eminent.In this paper a novel metric called software quality of structure（SQoS） is presented for quantitatively measuring the structural quality of object-oriented（OO） softwares via bug propagation analysis on weighted software networks（WSNs）.First,the software systems are modeled as a WSN,weighted class dependency network（WCDN）,in which classes are nodes and the interaction between every pair of classes if any is a directed edge with a weight indicating the probability that a bug in one class will propagate to the other.Then we analyze the bug propagation process in the WCDN together with the bug proneness of each class,and based on this,a metric（SQoS） to measure the structural quality of OO softwares as a whole is developed.The approach is evaluated in two case studies on open source Java programs using different software structures（one employs design patterns and the other does not） for the same OO software.The results of the case studies validate the effectiveness of the proposed metric.The approach is fully automated by a tool written in Java.展开更多
We investigate a problem of object-oriented (OO) software quality estimation from a multi-instance (MI) perspective. In detail,each set of classes that have an inheritance relation,named 'class hierarchy',is r...We investigate a problem of object-oriented (OO) software quality estimation from a multi-instance (MI) perspective. In detail,each set of classes that have an inheritance relation,named 'class hierarchy',is regarded as a bag,while each class in the set is regarded as an instance. The learning task in this study is to estimate the label of unseen bags,i.e.,the fault-proneness of untested class hierarchies. A fault-prone class hierarchy contains at least one fault-prone (negative) class,while a non-fault-prone (positive) one has no negative class. Based on the modification records (MRs) of the previous project releases and OO software metrics,the fault-proneness of an untested class hierarchy can be predicted. Several selected MI learning algorithms were evalu-ated on five datasets collected from an industrial software project. Among the MI learning algorithms investigated in the ex-periments,the kernel method using a dedicated MI-kernel was better than the others in accurately and correctly predicting the fault-proneness of the class hierarchies. In addition,when compared to a supervised support vector machine (SVM) algorithm,the MI-kernel method still had a competitive performance with much less cost.展开更多
There is a growing tendency for people in the community of object-oriented methods to use preand post-conditions to write formal specifications for opera- tions （methods） of classes. The motivation for trying to tak...There is a growing tendency for people in the community of object-oriented methods to use preand post-conditions to write formal specifications for opera- tions （methods） of classes. The motivation for trying to take advantage of well established formalism in precisely defining the functionality of operations is laudable, but unfortunately this exercise may be flawed because the use of pre- and post-conditions containing method calls （or similar） with side effects are likely to cause confusion in the interpretation of specifications. This paper analyzes, with comprehensible examples, why using pre-post notation is not effective to specify operations in objectoriented systems in general, discusses existing approaches to using pre-post notation for object-oriented systems, and offers some solutions to the problem.展开更多
基金supported by the National Basic Research 973 Program of China under Grant No.2007CB310801the National Natural Science Foundation of China under Grant Nos.60873083,60803025,60703009 and 60703018+3 种基金the Natural Science Foundation of Hubei Province under Grant No.2008ABA379the Natural Science Foundation of Hubei Province for Distinguished Young Scholars under Grant No.2008CDB351the Research Fund for the Doctoral Program of Higher Education of China under Grant Nos.20070486065 and 20090141120022the Fundamental Research Funds for the Central Universities of China under Grant No.6082005
文摘The quality of a software system is partially determined by its structure（topological structure）,so the need to quantitatively analyze the quality of the structure has become eminent.In this paper a novel metric called software quality of structure（SQoS） is presented for quantitatively measuring the structural quality of object-oriented（OO） softwares via bug propagation analysis on weighted software networks（WSNs）.First,the software systems are modeled as a WSN,weighted class dependency network（WCDN）,in which classes are nodes and the interaction between every pair of classes if any is a directed edge with a weight indicating the probability that a bug in one class will propagate to the other.Then we analyze the bug propagation process in the WCDN together with the bug proneness of each class,and based on this,a metric（SQoS） to measure the structural quality of OO softwares as a whole is developed.The approach is evaluated in two case studies on open source Java programs using different software structures（one employs design patterns and the other does not） for the same OO software.The results of the case studies validate the effectiveness of the proposed metric.The approach is fully automated by a tool written in Java.
文摘We investigate a problem of object-oriented (OO) software quality estimation from a multi-instance (MI) perspective. In detail,each set of classes that have an inheritance relation,named 'class hierarchy',is regarded as a bag,while each class in the set is regarded as an instance. The learning task in this study is to estimate the label of unseen bags,i.e.,the fault-proneness of untested class hierarchies. A fault-prone class hierarchy contains at least one fault-prone (negative) class,while a non-fault-prone (positive) one has no negative class. Based on the modification records (MRs) of the previous project releases and OO software metrics,the fault-proneness of an untested class hierarchy can be predicted. Several selected MI learning algorithms were evalu-ated on five datasets collected from an industrial software project. Among the MI learning algorithms investigated in the ex-periments,the kernel method using a dedicated MI-kernel was better than the others in accurately and correctly predicting the fault-proneness of the class hierarchies. In addition,when compared to a supervised support vector machine (SVM) algorithm,the MI-kernel method still had a competitive performance with much less cost.
文摘There is a growing tendency for people in the community of object-oriented methods to use preand post-conditions to write formal specifications for opera- tions （methods） of classes. The motivation for trying to take advantage of well established formalism in precisely defining the functionality of operations is laudable, but unfortunately this exercise may be flawed because the use of pre- and post-conditions containing method calls （or similar） with side effects are likely to cause confusion in the interpretation of specifications. This paper analyzes, with comprehensible examples, why using pre-post notation is not effective to specify operations in objectoriented systems in general, discusses existing approaches to using pre-post notation for object-oriented systems, and offers some solutions to the problem.
