For the complete documentation index, see llms.txt. This page is also available as Markdown.

Understanding measures and metrics

This section describes the metrics used in the Sonar solution to evaluate your code.

Metrics are used to measure:

  • Security, maintainability, and reliability attributes on the basis of statistics on the detected security, maintainability, and reliability issues, respectively.

  • Test coverage on the basis of coverage statistics on executable lines and evaluated conditions.

  • Code cyclomatic and cognitive complexities.

  • Security review level on the basis of statistics on reviewed security hotspots.

Metrics also include statistics on:

  • Duplicated lines and blocks.

  • Code size (the number of various code elements).

  • Issues.

For most metrics, SonarQube computes two values or ratings: one for overall code and one for new code.

  • Overall code is all analyzed code in the project or branch, the old code plus new code.

  • New code is the code that falls under your new code definition. It’s the code that has been recently added or modified. See New code definitions for more information.

The computed values might be different for overall code and new code because the scope is different. For example: your overall code might get an A for maintainability rating, while new code introduces more technical debt and gets a B for maintainability rating.

Finally, metrics also include the quality gate status result. Most metrics can be used to define the quality gate conditions.

You can find these metrics on the Measures page of your projects and portfolios.

The Measures page of a project

You can retrieve the metrics via the Web API by using the metric key.

Measuring software qualities

SonarQube Cloud measures your code against three Software qualities: security, reliability, and maintainability. For each one, two kinds of metric are available:

  • A count of the issues impacting that software quality, such as software_quality_reliability_issues.

  • The severity level of the most severe issue impacting that software quality, such as reliability_issue_severity.

Security

A list of security metrics used in SonarQube Cloud. See the Security-related rules page for more details.

Metric
Metric key
Definition

Security issues

software_quality_security_issues

The total number of issues impacting security.

Security issues on new code

new_software_quality_security_issues

The total number of security issues raised for the first time on new code.

Security issue severity

security_issue_severity

The severity level of the most severe security issue.

Security issue severity on new code

new_security_issue_severity

The severity level of the most severe security issue raised for the first time on new code.

Security rating

security_rating

Rating related to security. The rating grid is as follows: A = 0 vulnerability B = at least one minor vulnerability C = at least one major vulnerability D = at least one critical vulnerability E = at least one blocker vulnerability

Security rating on new code

new_security_rating

Rating related to security on new code.

Security remediation effort

security_remediation_effort

The effort to fix all vulnerabilities. The remediation cost of an issue is taken over from the effort (in minutes) assigned to the rule that raised the issue (see Technical debt in the Maintainability section).

An 8-hour day is assumed when values are shown in days.

Security remediation effort on new code

new_security_remediation_effort

The same as Security remediation effort but on new code.

Vulnerabilities (deprecated)

vulnerabilities

The total number of vulnerabilities. Use software_quality_security_issues.

Vulnerabilities on new code (deprecated)

new_vulnerabilities

The total number of vulnerabilities raised for the first time on new code. Use new_software_quality_security_issues.

Vulnerabilities severity on new code (deprecated)

new_vulnerabilities_severity

The severity level of the most severe vulnerability raised for the first time on new code. Use new_security_issue_severity.

Reliability

See the list below and Software qualities for more details about the reliability metrics used in SonarQube Cloud.

Metric
Metric key
Definition

Reliability issues

software_quality_reliability_issues

The total number of issues impacting reliability.

Reliability issues on new code

new_software_quality_reliability_issues

The total number of reliability issues raised for the first time on new code.

Reliability issue severity

reliability_issue_severity

The severity level of the most severe reliability issue.

Reliability issue severity on new code

new_reliability_issue_severity

The severity level of the most severe reliability issue raised for the first time on new code.

Reliability rating

reliability_rating

Rating related to reliability. The rating grid is as follows:

A = 0 bug

B = at least one minor bug

C = at least one major bug

D = at least one critical bug

E = at least one blocker bug

Reliability rating on new code

new_reliability_rating

Rating related to reliability on new code.

Reliability remediation effort

reliability_remediation_effort

The effort to fix all reliability issues. The remediation cost of an issue is taken over from the effort (in minutes) assigned to the rule that raised the issue. An 8-hour day is assumed when values are shown in days.

Reliability remediation effort on new code

new_reliability_remediation_effort

The same as Reliability remediation effort but on new code.

Bugs (deprecated)

bugs

The total number of bugs. Use software_quality_reliability_issues.

Bugs on new code (deprecated)

new_bugs

The total number of bugs raised for the first time on new code. Use new_software_quality_reliability_issues.

Bugs severity on new code (deprecated)

new_bugs_severity

The severity level of the most severe bug raised for the first time on new code. Use new_reliability_issue_severity.

Maintainability

See the list below and Software qualities for more details about the maintainability metrics used in SonarQube Cloud.

Metric
Metric key
Definition

Maintainability issues

software_quality_maintainability_issues

The total number of issues impacting maintainability.

Maintainability issues on new code

new_software_quality_maintainability_issues

The total number of maintainability issues raised for the first time on new code.

Maintainability issue severity

maintainability_issue_severity

The severity level of the most severe maintainability issue.

Maintainability issue severity on new code

new_maintainability_issue_severity

The severity level of the most severe maintainability issue raised for the first time on new code.

Technical debt

sqale_index

A measure of effort to fix all code smells. See below.

Technical debt on new code

new_technical_debt

A measure of effort to fix the code smells raised for the first time on new code.

Technical debt ratio

sqale_debt_ratio

The ratio between the cost to develop the software and the cost to fix it. See below.

Technical debt ratio on new code

new_sqale_debt_ratio

The ratio between the cost to develop the code changed on new code and the cost of the issues linked to it. See below.

Maintainability rating

sqale_rating

The rating related to the value of the technical debt ratio. See below.

Maintainability rating on new code

new_maintainability_rating

The rating related to the value of the technical debt ratio on new code. See below.

Code smells (deprecated)

code_smells

The total number of code smells. Use software_quality_maintainability_issues.

Code smells on new code (deprecated)

new_code_smells

The total number of code smells raised for the first time on new code. Use new_software_quality_maintainability_issues.

Code smells severity on new code (deprecated)

new_code_smells_severity

The severity level of the most severe code smell raised for the first time on new code. Use new_maintainability_issue_severity.

Technical debt

The technical debt is the sum of the maintainability issue remediation costs. An issue remediation cost is the effort (in minutes) evaluated to fix the issue. It is taken over from the effort assigned to the rule that raised the issue.

SonarQube Cloud gives you an estimated measure of the effort required to eliminate technical debt for the issue.

An 8-hour day is assumed when the technical debt is shown in days.

Technical debt ratio

The technical debt ratio is the ratio between the cost to develop the software and the technical debt (the cost to fix it). It is calculated based on the following formula:

sqale_debt_ratio = technical debt /(cost to develop one line of code * number of lines of code)

Where the cost to develop one line of code is predefined in the database (by default, 30 minutes)

Example:

  • Technical debt: 122,563

  • Number of lines of code: 63,987

  • Cost to develop one line of code: 30 minutes

  • Technical debt ratio: 6.4%

Maintainability rating

The maintainability rating reflects the density of technical debt relative to the size of the code. A lower ratio means a better rating.

The default Maintainability rating scale (sqale_rating) is:

  • A ≤ 5%

  • B ≥ 5% to <10%

  • C ≥ 10% to <20%

  • D ≥ 20% to < 50%

  • E ≥ 50%

Security review

A list of security review metrics used in the Sonar solution. See Security hotspot rules for more details.

Metric
Metric key
Definition

Security hotspots

security_hotspots

The number of security hotspots.

Security hotspots on new code

new_security_hotspots

The number of security hotspots on new code.

Security hotspots reviewed

security_hotspots_reviewed

The percentage of reviewed security hotspots compared in relation to the total number of security hotspots.

New security hotspots reviewed

new_security_hotspots_reviewed

The percentage of reviewed security hotspots on new code.

Security review rating

security_review_rating

The security review rating is a letter grade based on the percentage of reviewed security hotspots. Note that security hotspots are considered reviewed if they are marked as Acknowledged, Fixed, or Safe.

The rating grid is as follows: A = >= 80% B = >= 70% and <80% C = >= 50% and <70% D = >= 30% and <50% E = < 30%

Security review rating on new code

new_security_review_rating

The security review rating for new code.

Coverage

A list of coverage metrics used in the Sonar solution. See the Overview page on test coverage, for more details.

Metric
Metric key
Definition

Coverage

coverage

A mix of line coverage and condition coverage. Its goal is to provide an even more accurate answer to the question:

How much of the source code has been covered by unit tests?

coverage = (CT + LC)/(B + EL)

where:

  • CT: conditions that have been evaluated to true at least once

  • LC: covered lines = lines_to_cover - uncovered_lines

  • B: total number of conditions

  • EL: total number of executable lines (lines_to_cover)

Coverage on new code

new_coverage

This definition is identical to coverage but is restricted to new or updated source code.

Lines to cover

lines_to_cover

Coverable lines. The number of lines of code that could be covered by unit tests, for example, blank lines or full comments lines are not considered as lines to cover. Note that this metric is about what is possible, not what is left to do - that’s uncovered lines.

Lines to cover on new code

new_lines_to_cover

This definition is identical to lines to cover but restricted to new or updated source code.

Uncovered lines

uncovered_lines

The number of lines of code that are not covered by unit tests.

Uncovered lines on new code

new_uncovered_lines

This definition is identical to uncovered lines but restricted to new or updated source code.

Line coverage

line_coverage

On a given line of code, line coverage simply answers the question:

Has this line of code been executed during the execution of the unit tests?

It is the density of covered lines by unit tests:

line_coverage = LC / EL

where:

  • LC = covered lines = lines_to_cover - uncovered_lines

  • EL = total number of executable lines (lines_to_cover)

Line coverage on new code

new_line_coverage

This definition is identical to line coverage but restricted to new or updated source code.

Line coverage hits

coverage_line_hist_data

A list of covered lines.

Condition coverage

branch_coverage

The condition coverage answers the following question on each line of code containing boolean expressions:

Has each boolean expression been evaluated both to true and to false?

This is the density of possible conditions in flow control structures that have been followed during unit tests execution.

branch_coverage = (CT + CF) / (2*B)

where:

  • CT = conditions that have been evaluated to true at least once

  • CF = conditions that have been evaluated to false at least once

  • B = total number of conditions

Condition coverage on new code

new_branch_coverage

This definition is identical to condition coverage but is restricted to new or updated source code.

Condition coverage hits

branch_coverage_hits_data

A list of covered conditions.

Conditions by line

conditions_by_line

The number of conditions by line.

Covered conditions by line

covered_conditions_by_line

Number of covered conditions by line.

Uncovered conditions

uncovered_conditions

The number of conditions that are not covered by unit tests.

Uncovered conditions on new code

new_uncovered_conditions

This definition is identical to Uncovered conditions but restricted to new or updated source code.

Unit tests

tests

The number of unit tests.

Unit test errors

test_errors

The number of unit tests that have failed.

Unit test failures

test_failures

The number of unit tests that have failed with an unexpected exception.

Skipped unit tests

skipped_tests

The number of skipped unit tests.

Unit tests duration

test_execution_time

The time required to execute all the unit tests.

Unit test success density (%)

test_success_density

test_success_density = (tests - (test_errors + test_failures)) / (tests) * 100

Duplications

A list of duplication metrics used in SonarQube.

Metric
Metric key
Definition

Duplicated lines density (%)

duplicated_lines_density

Duplicated lines density is calculated by using the following formula:

duplicated_lines_density= duplicated_lines / lines * 100

Duplicated lines density (%) on new code

new_duplicated_lines_density

The same as duplicated lines density but on new code.

Duplicated lines

duplicated_lines

The number of lines involved in duplications.

Duplicated lines on new code

new_duplicated_lines

The number of lines involved in duplications on new code.

Duplicated blocks

duplicated_blocks

The number of duplicated blocks of lines.

For a block of code to be considered as duplicated, for Non-Java projects:

  • There should be at least 100 successive and duplicated tokens.

  • Those tokens should be spread at least on:

    • 30 lines of code for COBOL

    • 20 lines of code for ABAP

    • 10 lines of code for other languages

for Java projects:

  • There should be at least 10 successive and duplicated statements whatever the number of tokens and lines.

Differences in indentation and in string literals are ignored while detecting duplications.

Duplicated block on new code

new_duplicated_blocks

The number of duplicated blocks of lines on new code.

Duplicated files

duplicated_files

The number of files involved in duplications.

Size

A list of size metrics used in SonarQube.

Metric
Metric key
Definition

Lines

lines

The number of physical lines (number of carriage returns).

New lines

new_lines

The number of physical lines on new code (number of carriage returns).

Lines of code

ncloc

The number of physical lines that contain at least one character which is neither a whitespace nor a tabulation nor part of a comment.

New lines of code

new_ncloc

The number of physical lines on new code that contain at least one character which is neither a whitespace nor a tabulation nor part of a comment.

Statements

statements

The number of statements.

Functions

functions

The number of functions. Depending on the language, a function is defined as either a function, a method, or a paragraph. Language-specific details:

  • COBOL: It’s the number of paragraphs.

  • Dart: Any function expression is included, whether it’s the body of a function declaration, of a method, constructor, getter, top-level or nested function, top-level or nested lambda.

  • Java: Methods in anonymous classes are ignored.

  • VB.NET: Accessors are not considered to be methods.

Classes

classes

The number of classes (including nested classes, interfaces, enums, annotations, mixins, extensions, and extension types).

Files

files

The number of files.

Comment lines

comment_lines

The number of lines containing either comment or commented-out code. See Comment lines for calculation details.

Comments (%)

comment_lines_density

The comment lines density. It is calculated based on the following formula: comment_lines_density=[comment_lines / (lines + comment_lines)] * 100

Examples:

  • 50% means that the number of lines of code equals the number of comment lines.

  • 100% means that the file only contains comment lines.

Lines of code per language

ncloc_language_distribution

The non-commented lines of code distributed by language.

Projects

projects

The number of projects in a portfolio.

Comment lines

Non-significant comment lines (empty comment lines, comment lines containing only special characters, etc.) do not increase the number of comment lines.

The following piece of code contains 9 comment lines:

In addition:

  • For COBOL: Generated lines of code and pre-processing instructions (SKIP1, SKIP2, SKIP3, COPY, EJECT, REPLACE) are not counted as lines of code.

  • For Java and Dart: File headers are not counted as comment lines (because they usually define the license).

Complexity

Complexity metrics used in SonarQube.

Metric
Metric key
Definition

Cyclomatic complexity

complexity

A quantitative metric used to calculate the number of paths through the code.

Cognitive complexity

cognitive_complexity

A qualification of how hard it is to understand the code’s control flow. See Cyclomatic complexity: developer's guide for more information or sign up to download Cognitive Complexity white paper for a complete description of the mathematical model applied to compute this measure.

Cyclomatic complexity

Cyclomatic complexity is a quantitative metric used to calculate the number of paths through the code. The analyzer calculates the score of this metric for a given function (depending on the language, it may be a function, a method, a subroutine, etc.) by incrementing the function’s cyclomatic complexity counter by one each time the control flow of the function splits resulting in a new conditional branch. Each function has a minimum complexity of 1. The calculation formula is as follows:

Cyclomatic complexity = 1 + number of conditional branches

The calculation of the overall code’s cyclomatic complexity is basically the sum of all complexity scores calculated at the function level. In some languages, the complexity of external functions is additionally taken into account.

Split detection by language.

ABAP

The ABAP analyzer calculates the cyclomatic complexity at the function level. It increments the cyclomatic complexity by one each time it detects one of the following keywords:

  • AND

  • CATCH

  • DO

  • ELSEIF

  • IF

  • LOOP

  • LOOPAT

  • OR

  • PROVIDE

  • SELECT…ENDSELECT

  • TRY

  • WHEN

  • WHILE

C/C++/Objective-C

The C/C++/Objective-C analyzer calculates the cyclomatic complexity at function and coroutine levels. It increments the cyclomatic complexity by one each time it detects:

  • A control statement such as: if, while, do while, for

  • A switch statement keyword such as: case, default

  • The && and || operators

  • The ? ternary operator

  • A lambda expression definition

Each time the analyzer scans a header file as part of a compilation unit, it computes the measures for this header: statements, functions, classes, cyclomatic complexity, and cognitive complexity. That means that each measure may be computed more than once for a given header. In that case, it stores the largest value for each measure.

C#

The C# analyzer calculates the cyclomatic complexity at method and property levels. It increments the cyclomatic complexity by one each time it detects:

  • one of these function declarations: method, constructor, destructor, property, accessor, operator, or local function declaration.

  • A conditional expression

  • A conditional access

  • A switch case or switch expression arm

  • An and/or pattern

  • One of these statements: do, for, foreach, if, while

  • One of these expressions: ??, ??=, ||, or &&

COBOL

The COBOL analyzer calculates the cyclomatic complexity at paragraph, section, and program levels. It increments the cyclomatic complexity by one each time it detects one of these commands (except when they are used in a copybook):

  • ALSO

  • ALTER

  • AND

  • DEPENDING

  • END_OF_PAGE

  • ENTRY

  • EOP

  • EXCEPTION

  • EXEC CICS HANDLE

  • EXEC CICS LINK

  • EXEC CICS XCTL

  • EXEC CICS RETURN

  • EXIT

  • GOBACK

  • IF

  • INVALID

  • OR

  • OVERFLOW

  • SIZE

  • STOP

  • TIMES

  • UNTIL

  • USE

  • VARYING

  • WHEN

Dart

The Dart analyzer calculates the cyclomatic complexity for:

  • top-level functions

  • top-level function expressions (lambdas)

  • methods

  • accessors (getters and setters)

  • constructors

It increments the complexity by one for each of the structures listed above. It doesn’t increment the complexity for nested function declarations or expressions.

In addition, the count is incremented by one for each:

  • short-circuit binary expression or logical patterns (&&, ||, ??)

  • if-null assignments (??=)

  • conditional expressions (?:)

  • null-aware operators (?[, ?., ?.., ...?)

  • propagating cascades (a?..b..c)

  • if statement or collection

  • loop (for, while, do, and for collection)

case or pattern in a switch statement or expression

Java

The Java analyzer calculates the cyclomatic complexity at the method level. It increments the Cyclomatic complexity by one each time it detects one of these keywords:

  • if

  • for

  • while

  • case

  • &&

  • ||

  • ?

  • ->

JS/TS, PHP

The JS/TS analyzer calculates the cyclomatic complexity at the function level. The PHP analyzer calculates the cyclomatic complexity at the function and class levels. Both analyzers increment the cyclomatic complexity by one each time they detect:

  • A function (i.e non-abstract and non-anonymous constructors, functions, procedures or methods)

  • An if or (for PHP) elsif keyword

  • A short-circuit (AKA lazy) logical conjunction (&&)

  • A short-circuit (AKA lazy) logical disjunction (||)

  • A ternary conditional expression

  • A loop

  • A case clause of a switch statement

  • A throw or a catch statement

  • A goto statement (only for PHP)

PL/I

The PL/I analyzer increments the cyclomatic complexity by one each time it detects one of the following keywords:

  • PROC

  • PROCEDURE

  • GOTO

  • GO TO

  • DO

  • IF

  • WHEN

  • |

  • !

  • |=

  • !=

  • &

  • &=

  • A DO statement with conditions (Type 1 DO statements are ignored)

For procedures having more than one return statement: each additional return statement except for the last one, will increment the complexity metric.

PL/SQL

The PL/SQL analyzer calculates the cyclomatic complexity at the function and procedure level. It increments the cyclomatic complexity by one each time it detects:

  • The main PL/SQL anonymous block (not inner ones)

  • One of the following statements:

    • CREATE PROCEDURE

    • CREATE TRIGGER

    • basic LOOP

    • WHEN clause (the WHEN of simple CASE statement and searched CASE statement)

    • cursor FOR LOOP

    • CONTINUE / EXIT WHEN clause (The WHEN part of the CONTINUE and EXIT statements)

    • exception handler (every individual WHEN)

    • EXIT

    • FORLOOP

    • FORALL

    • IF

    • ELSIF

    • RAISE

    • WHILELOOP

  • One of the following expressions:

    • AND expression (AND reserved word used within PL/SQL expressions)

    • OR expression (OR reserved word used within PL/SQL expressions),

    • WHEN clause expression (the WHEN of simple CASE expression and searched CASE expression)

VB.NET

The VB.NET analyzer calculates the cyclomatic complexity at function, procedure, and property levels. It increments the cyclomatic complexity by one each time it detects:

  • a method or constructor declaration (Sub, Function),

  • AndAlso

  • Case

  • Do

  • End

  • Error

  • Exit

  • For

  • ForEach

  • GoTo

  • If

  • Loop

  • On Error

  • OrElse

  • Resume

  • Stop

  • Throw

  • Try

  • While

Issues

A list of issues metrics used in the Sonar solution. See the Issue identification and assignment by SonarQube page for information about how SonarQube Cloud identifies issues and manages its life cycle. To measure severity per software quality, see the Security, Reliability, and Maintainability sections.

Metric

Metric key

Definition

Issues

violations

The number of issues in all states.

Issues on new code

new_violations

The number of issues raised for the first time on new code.

Open issues

open_issues

The number of issues in the Open status.

Closed issues

resolved_issues

The number of issues closed. An issue is considered closed when it no longer appears in a later analysis.

Issue density

issue_density

The number of issues per 1000 lines of code.

Accepted issues

accepted_issues

The number of issues marked as Accepted.

Accepted issues on new code

new_accepted_issues

The number of Accepted issues on new code.

False positive issues

false_positive_issues

The number of issues marked as False positive.

Blocker issues (deprecated)

blocker_violations

Issues with Blocker type severity level. Use one or more of security_issue_severity, reliability_issue_severity, or maintainability_issue_severity instead.

Critical issues (deprecated)

critical_violations

Issues with Critical type severity level. Use one or more of security_issue_severity, reliability_issue_severity, or maintainability_issue_severity instead.

Major issues (deprecated)

major_violations

Issues with Major type severity level. Use one or more of security_issue_severity, reliability_issue_severity, or maintainability_issue_severity instead.

Minor issues (deprecated)

minor_violations

Issues with Minor type severity level. Use one or more of security_issue_severity, reliability_issue_severity, or maintainability_issue_severity instead.

Info issues (deprecated)

info_violations

Issues with Info type severity level. Use one or more of security_issue_severity, reliability_issue_severity, or maintainability_issue_severity instead.

Quality Gates

Quality gates metrics used in the Sonar solution.

Metric
Metric key
Definition

Quality gate status

alert_status

The state of the quality gate associated with your project. Possible values are ERROR and OK.

Quality gate details

quality_gate_details

Status (passed or failed) of each condition in the quality gate.

Advanced security (SCA)

Advanced security (SCA) metrics used in the Sonar solution.

The Advanced Security product is available starting with the Team plan. See the Subscribing to the Advanced Security product article for signup instructions.

Metric
Metric key
Definition

SCA issue count

sca_count_any_issue

The total number of dependency risks.

SCA issue count on new code

new_sca_count_any_issue

The total number of dependency risks raised for the first time on new code.

SCA severity threshold

sca_severity_any_issue

Indicates whether there is any dependency risk at or above the specified severity.

SCA severity threshold on new code

new_sca_severity_any_issue

Indicates whether there is any dependency risk at or above the specified severity raised for the first time on new code.

SCA vulnerability threshold

sca_severity_vulnerability

Indicates whether there is any vulnerability dependency risk at or above the specified severity.

SCA vulnerability threshold on new code

new_sca_severity_vulnerability

Indicates whether there is any vulnerability dependency risk at or above the specified severity raised for the first time on new code.

SCA licensing risk threshold

sca_severity_licensing

Indicates whether there is any license dependency risk at or above the specified severity.

Note: License risks are currently always HIGH severity. If this parameter is set to BLOCKER, no license risk will fail the quality gate.

SCA licensing risk threshold on new code

new_sca_severity_licensing

Indicates whether there is any license dependency risk at or above the specified severity raised for the first time on new code.

Note: License risks are currently always HIGH severity. If this parameter is set to BLOCKER, no license risk will fail the quality gate.

SCA rating

sca_rating_any_issue

Rating related to dependency risks. The rating grid is as follows:

  • A = 0 or more info risks

  • B = at least one low risks

  • C = at least one medium risk

  • D = at least one high risk

  • E = at least one blocker risk

SCA rating on new code

new_sca_rating_any_issue

Rating related to dependency risks in new code.

SCA vulnerability rating

sca_rating_vulnerability

Rating related to vulnerability risks.

SCA vulnerability rating on new code

new_sca_rating_vulnerability

Rating related to vulnerability risks in new code.

SCA license rating

sca_rating_licensing

Rating related to dependency licenses. License risks always have a rating of D, so using E will not fail the quality gate.

SCA license rating on new code

new_sca_rating_licensing

Rating related to dependency licenses in new code.

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