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Metrics Reference

V(G) | LOC | DIT | NOA | NRM | NLM | WMC | RFC | DAC | FANOUT | CBO | LCOM | NOC

Cyclomatic Complexity - V(G)

This metric was introduced in the 1970s to measure the amount of control flow complexity or branching complexity in a module such as a subroutine. It gives the number of paths that may be taken through the code, and was initially developed to give some measure of the cost of producing a test case for the module by executing each path.

Methods with a high cyclomatic complexity tend to be more difficult to understand and maintain. In general the more complex the methods of an application, the more difficult it will be to test it, and this will adversely affect its reliability.

V(G) is a measure of the control flow complexity of a method or constructor. It counts the number of branches in the body of the method, defined as:

  • while statements;
  • if statements;
  • for statements.
The metric can also be configured to count each case of a switch statement as well.

Lines of Code - LOC

This is perhaps the simplest of all the metrics to define and compute. Counting lines has a long history as a software metric dating from before the rise of structured programming, and it is still in widespread use today. The size of a method affects the ease with which it can be understood, its reusability and its maintainability. There are a variety of ways that the size can be calculated. These include counting all the lines of code, the number of statements, the blank lines of code, the lines of commentary, and the lines consisting only of syntax such as block delimiters.

This metric can also be used for sizing other constructs as well, for example, the overall size of a Java class or package can be measured by counting the number of source lines it consists of.

LOC can be used to determine the size of a compilation unit (source file), class or interface, method, constructor, or field. It can be configured to ignore:

  • blank lines;
  • lines consisting only of comments;
  • lines consisting only of opening and closing braces.

Depth of Inheritance Hierarchy - DIT

This metric calculates how far down the inheritance hierarchy a class is declared. In Java all classes have java.lang.Object as their ultimate superclass, which is defined to have a depth of 1. So a class that immediately extends java.lang.Object has a metric value of 2; any of its subclasses will have a value of 3, and so on.

A class that is deep within the tree inherits more methods and state variables, thereby increasing its complexity and making it difficult to predict its behavior. It can be harder to understand a system with many inheritance layers.

DIT is defined for classes and interfaces:

  • all interface types have a depth of 1;
  • the class java.lang.Object has a depth of 1;
  • all other classes have a depth of 1 + the depth of their super class.

Number of Attributes - NOA

The number of distinct state variables in a class serves as one measure of its complexity. The more state a class represents the more difficult it is to maintain invariants for it. It also hinders comprehensibility and reuse.

In Java, state can be exposed to subclasses through protected fields, which entails that the subclass also be aware of and maintain any invariants. This interference with the class's data encapsulation can be a source of defects and hidden dependencies between the state variables.

NOA is defined for classes and interfaces. It counts the number of fields declared in the class or interface.

Number of Remote Methods - NRM

NRM is defined for classes. A remote method call is defined as an invocation of a method that is not declared in any of:
  • the class itself;
  • a class or interface that the class extends or implements;
  • a class or method that extends the class.
The value is the count of all the remote method calls in all of the methods and constructors of the class.

Number of Local Methods - NLM

NLM is defined for classes and interfaces. A local method is defined as a method that is declared in the class or interface. NLM can be configured to include the local methods of all of the class's superclasses. Methods with public, protected, package and private visibility can be independently counted by setting configuration parameters.

Weighted Methods per Class - WMC

If the number of methods in a class can be determined during the design and modeling phase of a project, it can be used as a predictor of how much time and effort is needed to develop, debug and maintain it. This metric can be further refined by incorporating a weighting for the complexity of each method. The usual weighting is given by the cyclomatic complexity of the method.

The subclasses of a class inherit all of its public and protected methods, and possibly its package methods as well, so the number of methods a class has directly impacts the complexity of its subclasses. Classes with large numbers of methods are often specific to a particular application, reducing the ability to reuse them.

The definition of WMC is based upon NLM, and it provides the same configuration parameters for counting inherited methods and of varying visibility. The main difference is that NLM always counts each method as 1, whereas WMC will weight each method. There are two weighting schemes:

  • V(G) the cyclomatic complexity of the method is used as its weight. Methods from class files are given a V(G) of 1.
  • the arity, or the number of parameters of the method are used to determine the weight.

Response For Class - RFC

The response set of a class is the set of all methods that can be invoked as a result of a message sent to an object of the class. This includes methods in the class's inheritance hierarchy and methods that can be invoked on other objects. The Response For Class metric is defined to be size of the response set for the class. A class which provides a larger response set is considered to be more complex than one with a smaller response set.

One reason for this is that if a method call on a class can result in a large number of different method calls on the target and other classes, then it can be harder to test the behavior of the class and debug problems. It will typically require a deeper understanding of the potential interactions that objects of the class can have with the rest of the system.

RFC is defined as the sum of NLM and NRM for the class. The local methods include all of the public, protected, package and private methods, but not methods declared only in a superclass.

Data Abstraction Coupling - DAC

DAC is defined for classes and interfaces. It counts the number of reference types that are used in the field declarations of the class or interface. The component types of arrays are also counted. Any field with a type that is either a supertype or a subtype of the class is not counted.

Fan Out - FANOUT

FANOUT is defined for classes and interfaces, constructors and methods. It counts the number of reference types that are used in:
  • field declarations;
  • formal parameters and return types;
  • throws declarations;
  • local variables.
The component types of arrays are also counted. Any type that is either a supertype or a subtype of the class is not counted.

Coupling Between Objects - CBO

When one object or class uses another object or class they are said to be coupled. One major source of coupling is that between a superclass and a subclass. A coupling is also introduced when a method or field in another class is accessed, or when an object of another class is passed into or out of a method invocation. Coupling Between Objects is a measure of the non-inheritance coupling between two objects.

A high value of coupling reduces the modularity of the class and makes reuse more difficult. The more independent a class is the more likely it is that it will be possible to reuse it in another part of the system. When a class is coupled to another class it becomes sensitive to changes in that class, thereby making maintenance for difficult. In addition, a class that is overly dependent on other classes can be difficult to understand and test in isolation.

CBO is defined for classes and interfaces, constructors and methods. It counts the number of reference types that are used in:

  • field declarations
  • formal parameters and return types
  • throws declarations
  • local variables
It also counts:
  • types from which field and method selections are made
The component types of arrays are also counted. Any type that is either a supertype or a subtype of the class is not counted.

Lack of Cohesion Of Methods - LCOM

The cohesion of a class is the degree to which its methods are related to each other. It is determined by examining the pattern of state variable accesses within the set of methods. If all the methods access the same state variables then they have high cohesion; if they access disjoint sets of variables then the cohesion is low. An extreme example of low cohesion would be if none of the methods accessed any of the state variables. If a class exhibits low method cohesion it indicates that the design of the class has probably been partitioned incorrectly, and could benefit by being split into more classes with individually higher cohesion. On the other hand, a high value of cohesion (a low lack of cohesion) implies that the class is well designed. A cohesive class will tend to provide a high degree of encapsulation, whereas a lack of cohesion decreases encapsulation and increases complexity.

Another form of cohesion that is useful for Java programs is cohesion between nested and enclosing classes. A nested class that has very low cohesion with its enclosing class would probably better designed as a peer class rather than a nested class.

LCOM is defined for classes. Operationally, LCOM takes each pair of methods in the class and determines the set of fields they each access. If they have disjoint sets of field accesses increase the count P by one. If they share at least one field access then increase Q by one. After considering each pair of methods, LCOM = (P > Q) ? (P - Q) : 0

Indirect access to fields via local methods can be considered by setting a metric configuration parameter.

Number Of Classes - NOC

The overall size of the system can be estimated by calculating the number of classes it contains. A large system with more classes is more complex than a smaller one because the number of potential interactions between objects is higher. This reduces the comprehensibility of the system which in turn makes it harder to test, debug and maintain.

If the number of classes in the system can be projected during the initial design phase of the project it can serve as a base for estimating the total effort and cost of developing, debugging and maintaining the system.

The NOC metric can also usefully be applied at the package and class level as well as the total system.

NOCL is defined for class and interfaces. It counts the number of classes or interfaces that are declared. This is usually 1, but nested class declarations will increase this number. .bannercell { border: 0px; padding: 0px; } body { margin-left: 10; margin-right: 10; font:normal 80% arial,helvetica,sanserif; background-color:#FFFFFF; color:#000000; } .a td { background: #efefef; } .b td { background: #fff; } th, td { text-align: left; vertical-align: top; } th { font-weight:bold; background: #ccc; color: black; } table, th, td { font-size:100%; border: none } table.log tr td, tr th { } h2 { font-weight:bold; font-size:140%; margin-bottom: 5; } h3 { font-size:100%; font-weight:bold; background: #525D76; color: white; text-decoration: none; padding: 5px; margin-right: 2px; margin-left: 2px; margin-bottom: 0; } .Error { font-weight:bold; color:red; }

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Summary

V(G) LOC DIT NOA NRM NLM WMC RFC DAC FANOUT CBO LCOM NOCL
Note: Metrics evaluate the quality of software by analyzing the program source and quantifying various kind of complexity. Complexity is a common source of problems and defects in software. High complexity makes it more difficult to develop, understand, maintain, extend, test and debug a program.

The primary use of metrics is to focus your attention on those parts of code that potentially are complexity hot spots. Once the complex areas your program have been uncovered, you can take remedial actions. For additional information about metrics and their meaning, please consult Metamata Metrics manual.

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Note: Metrics evaluate the quality of software by analyzing the program source and quantifying various kind of complexity. Complexity is a common source of problems and defects in software. High complexity makes it more difficult to develop, understand, maintain, extend, test and debug a program.

The primary use of metrics is to focus your attention on those parts of code that potentially are complexity hot spots. Once the complex areas your program have been uncovered, you can take remedial actions. For additional information about metrics and their meaning, please consult Metamata Metrics manual.

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