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EXAMPLE 12.4
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Calculate the coupling factor on the object model shown in Fig. 12-3 for the bedand-breakfast problem (Problem 11.4). Only assume a relationship if it is required by the associations shown on the diagram.
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B&B 1 1 1..n calendar 1 0..n 0..n reservation 1..n bedroom 1 0..n payment expense 1 0..n 1 0..n transaction
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TC 7
Class B&B calendar bedroom customer transaction payment expense
is_client classes calendar, bedroom, customer, transaction reservation reservation reservation none none none
CF 7=42
12.3.4 POLYMORPHISM FACTOR
The polymorphism factor (PF) is a measure of the potential for polymorphism. Let Mo Ci be the number of overriding methods in class i. Let Mn Ci be the number of new methods in class i. Let DC Ci be the number of descendants of class i. PTC M C PF PTC i 1 o i i 1 Mn Ci DC Ci
EXAMPLE 12.5
Calculate the polymorphism factor on the C code from Example 12.3.
Class A B C
Mn x(),y() w(),z() v()
Mo none y() none
DC 2 1 0
PF 1= 2 2 2 1 1 0 1=6
CHAPTER 12 Object-Oriented Metrics
Review Questions
1. Why are McCabe s cyclomatic number and Halstead s software science not readily applicable to object-oriented software 2. What abstractions are available in object-oriented design to be used as the basis of object-oriented metrics 3. When should a metric for a whole system be di erent than either the sum or the average of metrics calculated for each class 4. Is a high LCOM good or bad 5. Some people have suggested that, in LCOM, just using the di erence between the size of P and Q. That is, the use of the maximum of zero and this di erence is not e ective. What would be the e ect of this change
Problems
1. Calculate the Chidamber metrics for the following code that maintains an array of people/students: class person{ char* name; char* ssn; public: person(){name = new char[NAMELENGTH]; ssn = new char[SSNLENGTH];} ~person(){delete name; delete ssn;} void addName(char* newname){strcpy(name, newname);} void addSsn(char* newssn){strcpy(ssn, newssn);} char* getName(){return name;} void virtual display(){cout << the person s name is <<name;} }; class student public person { oat gpa; public: void addGpa( oat newgpa){gpa = newgpa;} void display(){cout<< the student s name is <<getName()<< and gpa is << gpa;} };
Object-Oriented Metrics
class personlist { person* list[MAX]; int listIndex; public: personlist(){listIndex = 0;} void addPerson(char* newname, char* newssn){list[listIndex]=new person; list[listIndex]->addName(newname); list[listIndex] ->addSsn(newssn); listIndex++;} void addStudent(char* newname, char* newssn, oat gpa) {student* temp = new student; temp->addName(newname); temp->addSsn(newssn); temp->addGpa(newgpa);list[listIndex++]=temp;} void display(){int j; for(j=0; j<listIndex; j++) list[j] ->display();} };
Answers to Review Questions
1. Why are McCabe s cyclomatic number and Halstead s software science not readily applicable to object-oriented software These two metrics are based on the size and complexity of an algorithm written as a single function. Object-oriented functions are usually spread over a number of methods, often in di erent classes. Each object-oriented function is often small and relatively simple. Thus, these two metrics will probably not give a good measure of the complexity of the object-oriented system. 2. What abstractions are available in object-oriented design to be used as the basis of object-oriented metrics The standard abstractions are the UML diagrams: object models, use case diagrams, state models, and sequence diagrams. None of these appear to capture the essential notion of complexity in object-oriented software. 3. When should a metric for a whole system be di erent than either the sum or the average of metrics calculated for each class If the metric for the individual class is basically a size metric, such as LOC or number of children, then it would make sense to sum those individual metric values to obtain a metric value for the whole system or an average size per class. If the individual class metric was an average, then an average of the averages might be reasonable for instance, the average number of parameters per function.
CHAPTER 12 Object-Oriented Metrics
However, neither the sum nor the average will be a good metric of the interactions between classes. 4. Is a high LCOM good or bad Bad, since it implies a high lack of cohesion. 5. Some people have suggested that, in LCOM, just using the di erence between the size of P and Q. That is, the use of maximum of zero and this di erence is not e ective. What would be the e ect of this change It would allow discrimination between the more cohesive classes. Now a cohesive class just maps to zero.
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