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Software Engineering

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Software Engineering Object Oriented Metrics – PowerPoint PPT presentation

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Title: Software Engineering


1
Software Engineering
  • Object Oriented Metrics

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

3
Distinguishing Characteristics
  • The following characteristics require that
    special OO metrics be developed
  • Encapsulationthe packaging of data and
    processing. Conventional paradigms organize
    programs around data or function, OO does both.
    Concentrate on classes rather than functions.
  • Information hidingthe way in which information
    about operational details is hidden by a secure
    interface. An information hiding metric will
    provide an indication of quality.
  • Inheritancethe manner in which the
    responsibilities of one class are propagated to
    another. A pivotal indication of complexity.
  • Abstractionthe 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 gt 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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