# Index of Java code metrics | PMD Source Code Analyzer
Keywords: extendingmetrics,

# Index of Java code metrics

Index of the code metrics available out of the box to Java rule developers.

# Index of code metrics

## Access to Foreign Data (ATFD)

Operation metric, class metric. Can be computed on classes, enums and concrete operations.

### Description

Number of usages of foreign attributes, both directly and through accessors. High values of ATFD (> 3 for an operation) may suggest that the class or operation breaks encapsulation by relying on the internal representation of the classes it uses instead of the services they provide.

ATFD can be used to detect God Classes and Feature Envy. [Lanza05]

## Class Fan Out Complexity (CLASS_FAN_OUT)

Operation metric, class metric. Can be computed on classes, enums and concrete operations.

### Description

This counts the number of other classes a given class or operation relies on. Classes from the package `java.lang` are ignored by default (can be changed via options). Also primitives are not included into the count.

### Code example

    import java.util.*;
    import java.io.IOException;

    public class Foo { // total 8
        public Set set = new HashSet(); // +2
        public Map map = new HashMap(); // +2
        public String string = ""; // from java.lang -> does not count by default
        public Double number = 0.0; // from java.lang -> does not count by default
        public int[] intArray = new int[3]; // primitive -> does not count

        @Deprecated // from java.lang -> does not count by default
        @Override // from java.lang -> does not count by default
        public void foo(List list) throws Exception { // +1 (Exception is from java.lang)
            throw new IOException(); // +1
        }

        public int getMapSize() {
            return map.size(); // +1 because it uses the Class from the 'map' field
        }
    }

### Options

- Option `includeJavaLang`: Also include classes from the package `java.lang`

## Cognitive Complexity (COGNITIVE_COMPLEXITY)

Operation metric. Can be calculated on any non-abstract operation.

### Description

Cognitive complexity is a measure of how difficult it is for humans to read and understand a method. Code that contains a break in the control flow is more complex, whereas the use of language shorthands doesn’t increase the level of complexity. Nested control flows can make a method more difficult to understand, with each additional nesting of the control flow leading to an increase in cognitive complexity.

Information about Cognitive complexity can be found in the original paper here: CognitiveComplexity

The rule `CognitiveComplexity` by default reports methods with a complexity of 15 or more. These reported methods should be broken down into less complex components.

### Basic Idea

1. Ignore structures that allow multiple statements to be readably shorthanded into one
2. Increment (add one) for each break in the linear flow of the code
3. Increment when flow-breaking structures are nested

### Increments

There is an increment for each of the following:

- `if`, `else if`, `else`, ternary operator
- `switch`
- `for`, `foreach`
- `while`, `do while`
- `catch`
- `goto LABEL`, `break LABEL`, `continue LABEL`
- sequences of binary logical operators
- each method in a recursion cycle

### Nesting level

The following structures increment the nesting level:

- `if`, `else if`, `else`, ternary operator
- `switch`
- `for`, `foreach`
- `while`, `do while`
- `catch`
- nested methods and method-like structures such as lambdas

### Nesting increments

The following structures receive a nesting increment commensurate with their nested depth inside nested structures:

- `if`, ternary operator
- `switch`
- `for`, `foreach`
- `while`, `do while`
- `catch`

### Code example

    class Foo {
      void myMethod () {
        try {
          if (condition1) { // +1
            for (int i = 0; i < 10; i++) { // +2 (nesting=1)
              while (condition2) { } // +3 (nesting=2)
            }
          }
        } catch (ExcepType1 | ExcepType2 e) { // +1
          if (condition2) { } // +2 (nesting=1)
        }
      } // Cognitive Complexity 9
    }

## Cyclomatic Complexity (CYCLO)

Operation metric. Can be calculated on any non-abstract operation.

### Description

Number of independent paths through a block of code [Lanza05]. Formally, given that the control flow graph of the block has `n` vertices, `e` edges and `p` connected components, the cyclomatic complexity of the block is given by `CYCLO = e - n + 2p` [McCabe76]. In practice it can be calculated by counting control flow statements following the standard rules given below.

The standard version of the metric complies with McCabe’s original definition:

- Methods have a base complexity of 1.
- +1 for every control flow statement (`if`, `case`, `catch`, `throw`, `do`, `while`, `for`, `break`, `continue`) and conditional expression (`?:`) [Sonarqube]. Notice switch cases count as one, but not the switch itself: the point is that a switch should have the same complexity value as the equivalent series of `if` statements.
- `else`, `finally` and `default` don’t count;
- +1 for every boolean operator (`&&`, `||`) in the guard condition of a control flow statement. That’s because Java has short-circuit evaluation semantics for boolean operators, which makes every boolean operator kind of a control flow statement in itself.

### Code examples

    class Foo {
      void baseCyclo() {                // Cyclo = 1
        highCyclo();
      }

      void highCyclo() {                // Cyclo = 10
        int x = 0, y = 2;
        boolean a = false, b = true;

        if (a && (y == 1 ? b : true)) { // +3
          if (y == x) {                 // +1
            while (true) {              // +1
              if (x++ < 20) {           // +1
                break;                  // +1
              }
            }
          } else if (y == t && !d) {    // +2
            x = a ? y : x;              // +1
          } else {
            x = 2;
          }
        }
      }
    }

### Options

- Option `CycloVersion#IGNORE_BOOLEAN_PATHS`: Boolean operators are not counted, nor are empty fall-through cases in `switch` statements. You can use this option to get results similar to those of the old `StdCyclomaticComplexityRule`, which is to be replaced.
- Option `CycloVersion#CONSIDER_ASSERTS`: Assert statements are counted as if they were `if (..) throw new AssertionError(..)`. Compatible with `IGNORE_BOOLEAN_PATHS`.

## Lines of Code (LoC)

Operation metric, class metric. Can be calculated on any of those nodes.

### Description

Simply counts the number of lines of code the operation or class takes up in the source. This metric doesn’t discount comments or blank lines. See also NCSS.

## Non-commenting source statements (NCSS)

Operation metric, class metric. Can be calculated on any of those nodes.

### Description

Number of statements in a class or operation. That’s roughly equivalent to counting the number of semicolons and opening braces in the program. Comments and blank lines are ignored, and statements spread on multiple lines count as only one (e.g. `int\n a;` counts a single statement).

The standard version of the metric is based off JavaNCSS’s version
[JavaNcss]:

- +1 for any of the following statements: `if`, `else`, `while`, `do`, `for`, `switch`, `break`, `continue`, `return`, `throw`, `synchronized`, `catch`, `finally`.
- +1 for each assignment, variable declaration (except `for` loop initializers) or statement expression. We count variables declared on the same line (e.g. `int a, b, c;`) as a single statement.
- Contrary to Sonarqube, but as JavaNCSS, we count type declarations (class, interface, enum, annotation), and method and field declarations [Sonarqube].
- Contrary to JavaNCSS, but as Sonarqube, we do not count package declaration and import declarations as statements. This makes it easier to compare nested classes to outer classes. Besides, it makes for class metric results that actually represent the size of the class and not of the file. If you don’t like that behaviour, use the `COUNT_IMPORTS` option.

### Code example

    import java.util.Collections;       // +0
    import java.io.IOException;         // +0

    class Foo {                         // +1, total Ncss = 12

      public void bigMethod()           // +1
          throws IOException {
        int x = 0, y = 2;               // +1
        boolean a = false, b = true;    // +1

        if (a || b) {                   // +1
          try {                         // +1
            do {                        // +1
              x += 2;                   // +1
            } while (x < 12);

            System.exit(0);             // +1
          } catch (IOException ioe) {   // +1
            throw new PatheticFailException(ioe); // +1
          }
        } else {
          assert false;                 // +1
        }
      }
    }

### Options

- Option `NcssVersion#COUNT_IMPORTS`: Import and package statements are counted as well. This version fully complies with JavaNCSS.

## NPath complexity (NPath)

Operation metric. Can be computed on any non-abstract operation.

### Description

Number of acyclic execution paths through a piece of code. This is related to cyclomatic complexity, but the two metrics don’t count the same thing: NPath counts the number of distinct full paths from the beginning to the end of the method, while Cyclo only counts the number of decision points. NPath is not computed as simply as Cyclo. With NPath, two decision points appearing sequentially have their complexity multiplied.

The fact that NPath multiplies the complexity of statements makes it grow exponentially: 10 `if` - `else` statements in a row would give an NPath of 1024, while Cyclo would evaluate to 20. Methods with an NPath complexity over 200 are generally considered too complex.

We compute NPath recursively, with the following set of rules:

- An empty block has a complexity of 1.
- The complexity of a block is the product of the NPath complexity of its statements, calculated as follows:
  - The complexity of `for`, `do` and `while` statements is 1, plus the complexity of the block, plus the complexity of the guard condition.
  - The complexity of a cascading `if` statement (`if .. else if ..`) is the number of `if` statements in the chain, plus the complexity of their guard condition, plus the complexity of the unguarded `else` block (or 1 if there is none).
  - The complexity of a `switch` statement is the number of cases, plus the complexity of each `case` block. It’s equivalent to the complexity of the equivalent cascade of `if` statements.
  - The complexity of a ternary expression (`?:`) is the complexity of the guard condition, plus the complexity of both expressions. It’s equivalent to the complexity of the equivalent `if .. else` construct.
  - The complexity of a `try .. catch` statement is the complexity of the `try` block, plus the complexity of each catch block.
  - The complexity of a `return` statement is the complexity of the expression (or 1 if there is none).
  - All other statements have a complexity of 1 and are discarded from the product.

### Code example

    void fun(boolean a, boolean b, boolean c) { // NPath = 6

      // block #0

      if (a) {
        // block #1
      } else {
        // block #2
      }

      // block #3

      if (b) {
        // block #4
      } else if (c) {
        // block #5
      }

      // block #6
    }

After block 0, the control flow can either execute block 1 or 2 before jumping to block 3. From block three, the control flow will again have the choice between blocks 4 and 5 before jumping to block 6. The first `if` offers 2 choices, the second offers 3, so the cyclomatic complexity of this method is 2 + 3 = 5. NPath, however, sees 2 * 3 = 6 full paths from the beginning to the end.

## Number Of Public Attributes (NOPA)

Class metric. Can be computed on classes.

## Number Of Accessor Methods (NOAM)

Class metric. Can be computed on classes.

## Tight Class Cohesion (TCC)

Class metric. Can be computed on classes and enums.

### Description

The relative number of method pairs of a class that access in common at least one attribute of the measured class. TCC only counts direct attribute accesses, that is, only those attributes that are accessed in the body of the method [BK95].

TCC is taken to be a reliable cohesion metric for a class. High values (>70%) indicate a class with one basic function, which is hard to break into subcomponents. On the other hand, low values (<50%) may indicate that the class tries to do too much and defines several unrelated services, which is undesirable.

TCC can be used to detect God Classes and Brain Classes [Lanza05].

## Weighted Method Count (WMC)

Class metric. Can be computed on classes and enums.

### Description

Sum of the statistical complexity of the operations in the class. We use CYCLO to quantify the complexity of an operation [Lanza05].

### Options

WMC uses the same options as CYCLO, which are provided to CYCLO when computing it.

## Weight Of Class (WOC)

Class metric. Can be computed on classes.

### Description

Number of “functional” public methods divided by the total number of public methods. Our definition of “functional method” excludes constructors, getters, and setters.

This metric tries to quantify whether the measured class’ interface reveals more data than behaviour. Low values (less than 30%) indicate that the class reveals much more data than behaviour, which is a sign of poor encapsulation.

This metric is used to detect Data Classes, in conjunction with WMC, NOPA and NOAM.

# References

BK95: Bieman, Kang; Cohesion and reuse in an object-oriented system. In Proceedings ACM Symposium on Software Reusability, 1995.

Lanza05: Lanza, Marinescu; Object-Oriented Metrics in Practice, 2005.

McCabe76: McCabe, A Complexity Measure, in Proceedings of the 2nd ICSE (1976).

Sonarqube: Sonarqube online documentation.

JavaNcss: JavaNCSS online documentation.

Tags: extending metrics