Details of the Collected Metrics

The following sections provide details for the collected function and file metrics. Although the metrics collected by CScout are considerably more accurate than those collected by programs that either do not parse the source code or parse the preprocessed code, they still employ approximations.

Where appropriate file and function metrics are collected both before and after preprocessing. In the database tables they appear as two records for each entity that are distinguished by the value of the precpp column.

Metrics Common to Files and Functions

Number of characters

See note 1.

Number of comment characters

See note 1.

Number of space characters

See note 1.

Number of line comments

See note 1.

Number of block comments

See note 1.

Number of lines

See note 1.

Maximum number of characters in a line

See note 1.

Maximum number of tokens in a statement

See note 1.

Maximum level of statement nesting

In order to avoid excessively inflating this metric when measuring sequences of the form


if (a) {
	...
} else if (b) {
	...
} else if (c) {
	...
} else
	...
}

this metric does not take into account the nesting of else clauses. Thus the above code will be given a nesting level of 1, rather than 3, which is implied by the following (actual) reading of the code.


if (a) {
	...
} else
	if (b) {
		...
	} else
		if (c) {
			...
		} else
			...
		}

See note 1. See note 4.

Maximum level of brace nesting

See note 1.

Maximum level of bracket nesting

See note 1.

Dangling brace nesting

See note 1.

Dangling bracket nesting

See note 1.

Number of unprocessed lines

See note 1.

Number of C preprocessor directives

See note 1.

Number of processed C preprocessor conditionals (ifdef, if, elif)

See note 1.

Number of defined C preprocessor function-like macros

See note 1.

Number of defined C preprocessor object-like macros

See note 1.

Number of tokens

Although during preprocessing whitespace is considered a valid token, this metric does not take whitespace tokens into account. This makes it easy to compare the number of tokens before preprocessing with the number of tokens after preprocessing. The two metrics are equal if no macro expansion takes place.

Number of statements or declarations

Nested statements are counted recursively. Thus


while (a)
	if (b)
		c();

counts as three statements.

Number of operators

See note 2.

Number of unique operators

See note 2.

Number of numeric constants

See note 1.

Number of character literals

See note 1.

Number of character strings

See note 1.

Number of token concatenation operators (##)

See note 1.

Number of token stringification operators (#)

See note 1.

Number of if statements

See note 3.

Number of else clauses

See note 3.

Number of switch statements

See note 3.

Number of case labels

See note 3.

Number of default labels

See note 3.

Number of break statements

See note 3.

Number of for statements

See note 3.

Number of while statements

This metric does not include the do .. while form. See note 3.

Number of do statements

See note 3.

Number of continue statements

See note 3.

Number of goto statements

See note 3.

Number of return statements

See note 3.

Number of assembly statements

See note 1.

Number of typeof operators

See note 1.

Number of project-scope identifiers

See note 1.

Number of file-scope (static) identifiers

See note 1.

Number of macro identifiers

See note 1.

Total number of object and object-like identifiers

Also includes macros.

Number of unique project-scope identifiers

See note 1.

Number of unique file-scope (static) identifiers

See note 1.

Number of unique macro identifiers

See note 1.

Number of unique object and object-like identifiers

Also includes macros.

Number of goto labels

See note 1.

Tokens added by macro expansion

See note 1.

File-Specific Metrics

Number of copies of the file: See note 1.
Number of defined project-scope functions: See note 1.
Number of defined file-scope (static) functions: See note 1.
Number of defined project-scope variables: See note 1.
Number of defined file-scope (static) variables: See note 1.
Number of complete aggregate (struct/union) declarations: Also includes complete declarations without a tag. See note 1.
Number of declared aggregate (struct/union) members: See note 1.
Number of complete enumeration declarations: See note 1.
Number of declared enumeration elements: See note 1.
Number of directly included files: This counts the number of header files that were directly included while processing the project's source files. If each file is processed exactly once, the metric is roughly similar to the number of #include directives in the project's files. See also note 1.

Function-Specific Metrics

Number of global namespace occupants at function's top: This metric measures the namespace pollution in the object namespace at the point before entering a function. Its value is the count of all macros as well as objects with file and project-scope visibility that are declared at the point it is measured. See note 1. See note 4.
Number of parameters (for macros): See note 1.
Number of parameters (for functions): See note 1.
Number of passed non-expression macro parameters: See note 1.
Fan-in (number of calling functions): This is also listed under a function's details for functions that are not defined (and have not metrics associated with them).
Cyclomatic complexity (control statements): This metric, CC₁ measures the number of branch points in the function. In order to avoid misleadingly high values that occur from even trivial switch statements, this metric measures the complexity of a switch statement as 1.
Extended cyclomatic complexity (includes branching operators): This metric, CC₂, takes into account the nodes introduced by the Boolean-AND, boolean-OR, and conditional evaluation operators.
Maximum cyclomatic complexity (includes branching operators and all switch branches): This metric, CC₃, considers each case label as a separate node.
Structure complexity (Henry and Kafura): This metric is calculcated as follows.
C_p = (fan_in * fan_out)²
Halstead volume: This metric is calculcated as follows.
HC = (number_of_operators + number_of_operands) * log₂( unique_number_of_operators + unique_number_of_operands)
Where operands are object identifiers, macros, numeric and character constants. For the purpose of determining unique operands, each numeric or character constant is considered a separate operand.
Information flow metric (Henry and Selig): This metric is calculcated as follows.
HC_p = CC₁ * C_p

Notes

Note 1

This metric is measured the first time a file is encountered in a project. The metric does not take into account regions that were not processed due to conditional compilation.

Note 2

When this metric is calculated before preprocessing, operators occuring in function-like macros are accounted to the corresponding macro. However, this makes it difficult to differentiate between commas used to separate function arguments and the comma operator. As a result the comma is ignored as an operator.

Note 3

When this metric is calculated before preprocessing, keywords occuring in function-like macros are accounted to the corresponding macro. As a result C keywords used during preprocessing as identifiers, as in


#define x(if, while, else) (if + while + else)

will be miscounted as keywords occuring in the corresponding macro. Furthermore keywords generated during preprocessing, as in


#define WHILE(x) while(x) {
#define WEND	 }

WHILE (x)
	foo();
WEND

will not be counted as occuring in the corresponding C function.

Note 4

This metric is not measured for function-like macros.