Gcov For Mac

• Gcov For Macbook Air
• Gcov For Macbook
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Gcovr provides a utility for managing the use of the GNU gcov utilityand generating summarized code coverage results. This command isinspired by the Python coverage.py package, which provides a similarutility for Python.

The gcovr command can produce different kinds of coverage reports:

• default: compact human-readable summaries
• --xml: machine readable XML reports in Cobertura format
• --html: HTML summaries
• --html-details: HTML report with annotated source files

For example, if the header file x.h contains code, and was included in the file a.c, then running gcov on the file a.c will produce an output file called a.c##x.h.gcov instead of x.h.gcov. This can be useful if x.h is included in multiple source files and you want to see the individual contributions. Gcov is a source code coverage analysis and statement-by-statement profiling tool. Gcov generates exact counts of the number of times each statement in a program is executed and annotates source code to add instrumentation. Gcov comes as a standard utility with the GNU Compiler Collection (GCC) suite. This post explains how to flush gcov1 trace data dynamically from all linked shared libraries. Technique Typically tracing data is written when the application terminates. Tracing date from all shared libraries with activated gcov are written to the specified location. However, when tracing date is needed during runtime, a signal handler is required to call.

Thus, gcovr can be viewedas a command-line alternative to the lcov utility, which runs gcovand generates an HTML-formatted report.The development of gcovr was motivated by the need fortext summaries and XML reports.

In OS X, GCC is part of Xcode's command tools, so first, open the Mac App Store and install Xcode for free. Then, open Xcode, go to Xcode menu (on the menu bar) Preferences Downloads, and install Command Line Tools. You will get commands like gcc, make, purge.

The Gcovr Home Page ishttp://gcovr.com.Automated test results are available throughTravis CI andAppveyor.Gcovr is available under theBSD license.

This documentation describes Gcovr 4.1.

This User Guide provides the following sections:

• Getting Started
• The gcovr Command
• Using Filters

Related documents:

• Contributing (includes instructions for bug reports)

The gcovr command provides a summary of the lines that have beenexecuted in a program. Code coverage statistics help you discoveruntested parts of a program, which is particularly important whenassessing code quality. Well-tested code is a characteristic ofhigh quality code, and software developers often assess code coveragestatistics when deciding if software is ready for a release.

The gcovr command can be used to analyze programs compiled withGCC. The following sections illustrate the application of gcovrto test coverage of the following program:

This code executes several subroutines in this program,but some lines in the program are not executed.

We compile example1.cpp with the GCC compiler as follows:

Note that we compile this program without optimization, becauseoptimization may combine lines of code and otherwise change theflow of execution in the program. Additionally, we compile withthe -fprofile-arcs-ftest-coverage-fPIC compiler options, whichadd logic to generate output files that can be processed by thegcov command.

The compiler generates the program executable. When we execute this command:

the files example1.gcno and example1.gcda are generated. Thesefiles are processed with by gcov to generate code coveragestatistics. The gcovr command calls gcov and summarizes thesecode coverage statistics in various formats. For example:

generates a text summary of the lines executed:

Each line of this output includes a summary for a given source file,including the number of lines instrumented, the number of linesexecuted, the percentage of lines executed, and a summary of theline numbers that were not executed. To improve clarity, gcovruses an aggressive approach to grouping uncovered lines and willcombine uncovered lines separated by “non-code” lines (blank,freestanding braces, and single-line comments) into a single region.As a result, the number of lines listed in the “Missing” list maybe greater than the difference of the “Lines” and “Exec” columns.

The -r option specifies the root directory for the files that arebeing analyzed. This allows gcovr to generate a simpler report(without absolute path names), and it allows system header filesto be excluded from the analysis.

Note that gcov accumulates statistics by line. Consequently, itworks best with a programming style that places only one statementon each line.

The gcovr command can also summarize branch coverage using the --branches option:

This generates a tabular output that summarizes the number of branches, the number ofbranches taken and the branches that were not completely covered:

The default output format for gcovr is to generate a tabularsummary in plain text. The gcovr command can also generate anXML output using the --xml and --xml-pretty options:

This generates an XML summary of the lines executed:

This XML format is in theCobertura XMLformat suitable for import and display within theJenkins and Hudsoncontinuous integration servers using theCobertura Plugin.

The --xml option generates a denser XML output, and the --xml-prettyoption generates an indented XML output that is easier to read.Note that the XML output contains more information than the tabularsummary. The tabular summary shows the percentage of covered lines,while the XML output includes branch statistics and the number oftimes that each line was covered. Consequently, XML output can beused to support performance optimization in the same manner thatgcov does.

The gcovr command can also generate a simpleHTML output using the --html option:

This generates a HTML summary of the lines executed. In thisexample, the file example1.html is generated, which has thefollowing output:

The default behavior of the --html option is to generate HTML fora single webpage that summarizes the coverage for all files. TheHTML is printed to standard output, but the -o (--output) optionis used to specify a file that stores the HTML output.

The --html-details option is used to create a separate web pagefor each file. Each of these web pages includes the contents offile with annotations that summarize code coverage. Consider the followingcommand:

This generates the following HTML page for the file example1.cpp:

Note that the --html-details option can only be used with the-o (--output) option. For example, if the --output optionspecifies the output file coverage.html, then the web pagesgenerated for each file will have names of the formcoverage.<filename>.html.

The gcovr command recursively searches a directory tree to findgcov coverage files, and generates a text summary of the codecoverage. The --help option generates the following summary ofthe gcovr command line options:

A utility to run gcov and summarize the coverage in simple reports.

See <http://gcovr.com/> for the full manual.

Options¶

Search these directories for coverage files. Defaults to –root and –object-directory.

Show this help message, then exit.

Print the version number, then exit.

Print progress messages. Please include this output in bug reports.

The root directory of your source files. Defaults to ‘.’, the current directory. File names are reported relative to this root. The –root is the default –filter.

Exit with a status of 2 if the total line coverage is less than MIN. Can be ORed with exit status of ‘–fail-under-branch’ option.

Exit with a status of 4 if the total branch coverage is less than MIN. Can be ORed with exit status of ‘–fail-under-line’ option.

Select the source file encoding. Defaults to the system default encoding (UTF-8).

If the coverage is below MEDIUM, the value is marked as low coverage in the HTML report. MEDIUM has to be lower than or equal to value of –html-high-threshold. If MEDIUM is equal to value of –html-high-threshold the report has only high and low coverage. Default is 75.0.

If the coverage is below HIGH, the value is marked as medium coverage in the HTML report. HIGH has to be greater than or equal to value of –html-medium-threshold. If HIGH is equal to value of –html-medium-threshold the report has only high and low coverage. Default is 90.0.

Output Options¶

Gcovr prints a text report by default, but can switch to XML or HTML.

Print output to this filename. Defaults to stdout. Required for –html-details.

Report the branch coverage instead of the line coverage. For text report only.

Sort entries by increasing number of uncovered lines. For text and HTML report.

Sort entries by increasing percentage of uncovered lines. For text and HTML report.

Generate a Cobertura XML report.

Pretty-print the XML report. Implies –xml. Default: False.

Generate a HTML report.

Add annotated source code reports to the HTML report. Requires –output as a basename for the reports. Implies –html.

Use TITLE as title for the HTML report. Default is Head.

Use absolute paths to link the –html-details reports. Defaults to relative links.

Override the declared HTML report encoding. Defaults to UTF-8. See also –source-encoding.

Print a small report to stdout with line & branch percentage coverage. This is in addition to other reports. Default: False.

Filter Options¶

Filters decide which files are included in the report. Any filter must match, and no exclude filter must match. A filter is a regular expression that matches a path. Filter paths use forward slashes, even on Windows.

Keep only source files that match this filter. Can be specified multiple times. If no filters are provided, defaults to –root.

Exclude source files that match this filter. Can be specified multiple times.

Keep only gcov data files that match this filter. Can be specified multiple times.

Exclude gcov data files that match this filter. Can be specified multiple times.

Exclude directories that match this regex while searching raw coverage files. Can be specified multiple times.

GCOV Options¶

The ‘gcov’ tool turns raw coverage files (.gcda and .gcno) into .gcov files that are then processed by gcovr. The gcno files are generated by the compiler. The gcda files are generated when the instrumented program is executed.

Use a particular gcov executable. Must match the compiler you are using, e.g. ‘llvm-cov gcov’ for Clang. Can include additional arguments. Defaults to the GCOV environment variable, or ‘gcov’: ‘gcov’.

Exclude branch coverage with LCOV/GCOV exclude markers. Additionally, exclude branch coverage from lines without useful source code (often, compiler-generated “dead” code). Default: False.

Use existing gcov files for analysis. Default: False.

Skip lines with parse errors in GCOV files instead of exiting with an error. A report will be shown on stderr. Default: False.

Override normal working directory detection. Gcovr needs to identify the path between gcda files and the directory where the compiler was originally run. Normally, gcovr can guess correctly. This option specifies either the path from gcc to the gcda file (i.e. gcc’s ‘-o’ option), or the path from the gcda file to gcc’s working directory.

Keep gcov files after processing. This applies both to files that were generated by gcovr, or were supplied via the –use-gcov-files option. Default: False.

Delete gcda files after processing. Default: False.

Set the number of threads to use in parallel.

The above Getting Started guideillustrates the use of some command line options.Using Filters is discussed below.

Gcovr tries to only report coverage for files within your project,not for your libraries. This is influenced by the following options:

• -r, --root
• -f, --filter
• -e, --exclude
• (the current working directory where gcovr is invoked)

These options take filters.A filter is a regular expression that matches a file path.Because filters are regexes,you will have to escape “special” characters with a backslash .

Always use forward slashes / as path separators, even on Windows:

• wrong: --filterC:projectsrc
• correct: --filterC:/project/src/

If the filter looks like an absolute path,it is matched against an absolute path.Otherwise, the filter is matched against a relative path,where that path is relative to the current directory.Examples of relative filters:

• --filtersubdir/ matches only that subdirectory
• --filter'./src/' matches a sibling directory ./src.But because a dot . matches any character in a regex,we have to escape it.You have to use additional shell escaping.This example uses single quotes for Bash or POSIX shell.
• --filter'(.+/)?foo.c$' matches only files called foo.c.The regex must match from the start of the relative path,so we ignore any leading directory parts with (.+/)?.The $ at the end ensures that the path ends here.

If no --filter is provided,the --root is turned into a default filter.Therefore, files outside of the --root directory are excluded.

To be included in a report, the source file must match any --filter,and must not match any --exclude filter.

The --gcov-filter and --gcov-exclude filters apply to the .gcov files created by gcov.This is useful mostly when running gcov yourself,and then invoking gcovr with -g/--use-gcov-files.But these filters also apply when gcov is launched by gcovr.

The --exclude-directories filter is usedwhile searching for raw coverage data(or for existing .gcov files when --use-gcov-files is active).This filter is matched against directory paths, not file paths.If a directory matches,all its contents (files and subdirectories) will be excluded from the search.For example, consider this build directory:

If we run gcovr--exclude-directories'build/a$',this will exclude anything in the build/a directorybut will use the coverage data for better_code.o and main.o.

This can speed up gcovr when you have a complicated build directory structure.Consider also using the search_pathsor --object-directory argumentsto specify where gcovr starts searching.If you are unsure which directories are being searched,run gcovr in --verbose mode.

For each found coverage data file gcovr will invoke the gcov tool.This is typically the slowest part,and other filters can only be applied after this step.In some cases, parallel execution with the -j optionmight be helpful to speed up processing.

Gcovr matches filters against real pathsthat have all their symlinks resolved.E.g. consider this project layout:

Here, the relevant-libraryhas the real path /home/you/external-library.

To write a filter that includes both src/ and relevant-library/src/,we cannot use --filterrelevant-library/src/because that contains a symlink.Instead, we have to use an absolute path to the real name:

or a relative path to the real path:

Note

This section discusses symlinks on Unix systems.The behavior under Windows is unclear.If you have more insight,please update this section by submitting a pull request(see our contributing guide).

Gcovr is maintained by:

The following developers contributed to gcovr (ordered alphabetically):

The development of Gcovr has been partially supportedby Sandia National Laboratories. Sandia National Laboratories isa multi-program laboratory managed and operated by Sandia Corporation,a wholly owned subsidiary of Lockheed Martin Corporation, for theU.S. Department of Energy’s National Nuclear Security Administrationunder contract DE-AC04-94AL85000.

This article has been migrated from my original post at embeddedinn.wordpress.com.

Any large code base needs to be incrementally tested for each release for regressions and bugs. When the code base grows, manual testing fails to meet the requirements and we have to move into automated systems for testing. Once a test is written, we have excellent continuous integration systems like Jenkins or Cruise Control to validate the tests against any changes made on the code. However, the CI system is only as effective as the test. If the test does not cover all use cases, then there is no point in running the tests in CI.

This article intends to illustrate the use of ‘gcov’ to estimate the dynamic coverage of a test. The article speaks solely from the viewpoint of a C programmer working on a Linux PC (or similar systems)

What is coverage?

All large scale, usable C code is written in the form of blocks of code enclosed in functions. A block can be a set of simple execution statements or a logical branch.

The ideal test code should logically call all the functions and execute all statements in the blocks. The percentage of lines of actual code that gets executed when a test code runs is called the coverage of the test code. More the number of lines of code that is tested, less is the probability to get a last minute surprise bug.

There are two types of coverage analysis that is possible.

Static code coverage analysis is done by analyzing the test code and the actual code to primarily estimate the function call coverage. Static code coverage analysis is much faster and simpler since the generated object file need not be executed. This is particularly handy in the case of small scale embedded systems.

Dynamic code coverage analysis is much more elaborate and requires the test code to be executed on the target. It also requires the object file to be generated with special compilation options. However, it gives much more detailed analysis of how effective the test is.

For obvious reasons, it is not practical to manually compute the coverage of a test code. Thus we have some tools that can compute the coverage of our test code for us. We will now look into the details of how ‘gcov’ can be used for dynamic code coverage analysis.

GCOV

As per Wikipedia, Gcov is a source code coverage analysis and statement-by-statement profiling tool. Gcov generates exact counts of the number of times each statement in a program is executed and annotates source code to add instrumentation. Gcov comes as a standard utility with GNU CC Suite (GCC)

Gcov provides the following details:

• How often each line of code executes
• What lines of code are actually executed
• How much computing time each section of code uses

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Getting Started With GCOV

When using gcov, you must first compile your program with –coverage GCC option.

This tells the compiler to generate additional information needed by gcov (basically a flow graph of the program) and also includes additional code in the object files for generating the extra profiling information needed by gcov. These additional files (.gcno) are placed in the directory where the object file is located.

Once the object file is generated, execute it once to get the profile file (.gcda)

Once we have the gcna and gcda files , we can now run gcov.

To illustrate the usage of gcov, we will consider a very minimal library (lib.c) and it test suite (test.c) .

lib.c

test.c

Compilation command for the test code :

gcc --coverage lib.c test.c –o test

This will generate the following files:

• lib.gcno – library flow graph
• test.gcno – test code flow graph
• test – test code executable

Now, execute the test code object file. This will generate the following files

• lib.gcda – library profile output
• test.gcda – test code profile output

Now we have all the inputs required for gcov to generate the coverage report. To generate the coverage report, run the following command

gcov -abcfu lib.c

Coverage summary will be displayed as below when gcov finishes execution:

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Detailed coverage report will be available in the lib.c.gcov file generated by gcov

Each block is marked by a line with the same line number as the last line of the block and the number of branch and calls in the block.

Each function is preceded with a line showing the number of times the function is called, number of times it returns and the percentage of function blocks that were executed.

Each line of executable code contains the number of times the line was executed and the actual source code line number. Any line that was not executed will have ##### in place of the execution count. Blocks that are not executed will have $$$$$ in place of the execution count.

The command line option summary for gcov is given below:

Visualizing results with LCOV

The Linux testing project (LTP) has come up with a tool called lcov that provides a more user-friendly graphical visualization of the gcov output. It generates html files and integrates well with web based CI systems.

To make lcov generate html reports for you, give the following commands once the gcno and gcda files are generated.

lcov --directory . –zerocounters
lcov --directory . --capture --output-file app.info
genhtml app.info

The lcov reports seen from a browser is shown in the screenshots below.

Cross Profiling

This section is adapted from the GCOV manual :

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As we have seen so far, running the program to be profiled will cause profile output to be generated. For each source file compiled with the –coverage option, a .gcda file will be generated in the object file directory. This places a restriction that the target system should have the same directory structure. (The program will try to create the needed directory structure, if it is not already present).

As per the gnu GCOV documentation, redirection can be done with the help of two execution environment variables.

• GCOV_PREFIX : Contains the prefix to add to the absolute paths in the object file. Prefix can be absolute, or relative. The default is no prefix.
• GCOV_PREFIX_STRIP : Indicates the how many initial directory names to strip off the hardwired absolute paths. Default value is 0.

Note: If GCOV_PREFIX_STRIP is set without GCOV_PREFIX is undefined, then a relative path is made out of the hardwired absolute paths.

For example, if the object file /user/build/foo.o was built with -fprofile-arcs, the final executable will try to create the data file /user/build/foo.gcda when running on the target system. This will fail if the corresponding directory does not exist and it is unable to create it. This can be overcome by, for example, setting the environment as GCOV_PREFIX=/target/run and GCOV_PREFIX_STRIP=1. Such a setting will name the data file /target/run/build/foo.gcda.

You must move the data files to the expected directory tree in order to use them for profile directed optimizations (–use-profile), or to use the gcov tool.