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Software Engineering

Software Engineering. Object Oriented Metrics. Objectives. To describe the distinguishing characteristics of Object-Oriented Metrics. To introduce metrics suitable for design, testing and project management. To focus on OO metrics at a class and method level. Distinguishing Characteristics.

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Software Engineering

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  1. Software Engineering Object Oriented Metrics

  2. Objectives • To describe the distinguishing characteristics of Object-Oriented Metrics. • To introduce metrics suitable for design, testing and project management. • To focus on OO metrics at a class and method level.

  3. Distinguishing Characteristics • The following characteristics require that special OO metrics be developed: • Encapsulation—the packaging of data and processing. Conventional paradigms organize programs around data or function, OO does both. Concentrate on classes rather than functions. • Information hiding—the way in which information about operational details is hidden by a secure interface. An information hiding metric will provide an indication of quality. • Inheritance—the manner in which the responsibilities of one class are propagated to another. A pivotal indication of complexity. • Abstraction—the mechanism that allows a design to focus on essential details. Metrics need to measure a class at different levels of abstraction and from different viewpoints. • Conclusion: the class is the fundamental unit of measurement.

  4. CK Metrics Suite • Weighted Methods per Class (WMC): Assume that n methods with cyclomatic complexity are defined for a class C: • Depth of the Inheritance Tree (DIT): The maximum length from a leaf to the root of the tree. Large DIT leads to greater design complexity but promotes reuse. • Number of Children (NOC): Total number of children for each class. Large NOC may dilute abstraction and increase testing. • Coupling between Object Classes (CBO): Total number of collaborations listed for each class in CRC cards. Keep COB low because high values complicate modification and testing. • Response For a Class (RFC): Set of methods potentially executed in response to a message received by a class. High RFC implies test and design complexity. • Lack of Cohesion in Methods (LCOM): Number of methods in a class that access one or more of the same attributes. High LCOM means tightly coupled methods.

  5. Lorenz and Kidd Metrics • Class Size (CS): total number of methods and attributes (both inherited and private) encapsulated by a class. Public methods and attributes are weighted more heavily. Large CS may imply too much responsibility. • Number of Operations Overridden by a subclass (NOO): If many methods are replaced in a subclass this indicates a design problem. Specialization should lead to extension not replacement. • Number of Operations Added by a subclass (NOA): Too many additional methods mean that a subclass is drifting away from its parent. • Specialization Index (SI): A rough indication of the degree of specialization of a class. SI = [NOO x classlevel] / totalmethods.

  6. Method-Oriented Metrics • Average Operation Size: Number of messages sent by a method. Too many messages means that responsibilities have not been evenly distributed. • Operation Complexity: Cyclomatic complexity of a method. Strive to keep operation complexity low. • Average Number of Parameters per Operation: The larger the number of method parameters, the more complex the collaboration between objects.

  7. Testability Metrics • Encapsulation Related • lack of cohesion in methods (LCOM): The higher the value of LCOM, the more states must be tested to ensure that methods do not generate side effects. • Percent Public and Protected (PAP): Percentage of attributes that are public. Public attributes can be inherited and accessed externally. High PAP means more side effects. • Public Access to Data members (PAD): Number of classes that access another classes attributes. Violates encapsulation. • Inheritance Related • Number of Root Classes (NRC): Count of distinct class hierarchies. Must all be tested separately. • Fan In (FIN): The number of superclasses associated with a class. FIN > 1 indicates multiple inheritance. Must be avoided. • Number of Children (NOC) and Depth of Inheritance Tree (DIT): Superclasses need to be retested for each subclass.

  8. Project Management Metrics • Number of Scenario Scripts: Number of use-cases is directly proportional the number of classes needed to meet requirements. A strong indicator of program size. • Number of Key Classes: A key class focuses directly on the business domain for the problem and is less likely to be implemented via reuse. Typically 20-40% of all classes are key, the rest support infrastructure (e.g. GUI, communications, databases). • Number of Subsystems: Provides insight into resource allocation, scheduling for parallel development and overall integration effort.

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