.\"	$OpenBSD: gcov.1,v 1.3 2004/08/25 21:59:59 jmc Exp $
.\"
.\"    Published by the Free Software Foundation 59 Temple Place - Suite 330
.\" Boston, MA 02111-1307 USA
.\"
.\"    Copyright (C) 1988, 1989, 1992, 1993, 1994, 1995, 1996, 1997, 1998,
.\" 1999, 2000 Free Software Foundation, Inc.
.\"
.\"    Permission is granted to make and distribute verbatim copies of this
.\" manual provided the copyright notice and this permission notice are
.\" preserved on all copies.
.\"
.\"    Permission is granted to copy and distribute modified versions of
.\" this manual under the conditions for verbatim copying, provided also
.\" that the sections entitled "GNU General Public License" and "Funding
.\" for Free Software" are included exactly as in the original, and
.\" provided that the entire resulting derived work is distributed under
.\" the terms of a permission notice identical to this one.
.\"
.\"    Permission is granted to copy and distribute translations of this
.\" manual into another language, under the above conditions for modified
.\" versions, except that the sections entitled "GNU General Public
.\" License" and "Funding for Free Software", and this permission notice,
.\" may be included in translations approved by the Free Software Foundation
.\" instead of in the original English.
.\"
.Dd February 15, 2003
.Dt GCOV 1
.Os
.Sh NAME
.Nm gcov
.Nd test coverage program
.Sh SYNOPSIS
.Nm
.Op Fl b
.Op Fl v
.Op Fl n
.Op Fl l
.Op Fl f
.Op Fl o Ar directory
.Ar sourcefile
.Sh DESCRIPTION
The
.Nm
utility is a test coverage program.
Use it in concert with
.Xr gcc 1
to analyze programs to help create more efficient, faster running code.
.Nm
can be used as a profiling tool to help discover where optimization efforts
will best affect the code.
.Nm
can also be used along with the other profiling tool
.Xr gprof 1 ,
to assess which parts of the code use the greatest amount of computing time.
.Pp
Profiling tools help analyze the code's performance.
Using a profiler such as
.Nm gcov
or
.Xr gprof 1 ,
basic performance statistics can be obtained, such as:
.Pp
.Bl -bullet -offset indent -compact
.It
how often each line of code executes
.It
what lines of code are actually executed
.It
how much computing time each section of code uses
.El
.Pp
Once you know these things about how your code works when compiled,
you can look at each module to see which modules should be optimized.
.Nm
helps determine where to work on optimization.
.Pp
Software developers also use coverage testing in concert with
testsuites, to make sure software is actually good enough for a release.
Testsuites can verify that a program works as expected;
a coverage program tests to see how much of the program is exercised by the
testsuite.
Developers can then determine what kinds of test cases need
to be added to the testsuites to create both better testing and a better
final product.
.Pp
Code should be compiled without optimization when using
.Nm
because the optimization, by combining some lines of code into
one function,
may not give as much information as necessary to look
for
.Sq hot spots
where the code is using a great deal of computer time.
Likewise, because
.Nm
accumulates statistics by line
.Pq at the lowest resolution ,
it works best with a programming style that places only
one statement on each line.
If complicated macros that expand to loops or to other control structures
are used, the statistics are less helpful \- they only report on the line
where the macro call appears.
If complex macros behave like functions, they can be replaced  with
inline functions to solve this problem.
.Pp
.Nm
creates a logfile called
.Sq Ar sourcefile Ns Li .gcov
which indicates how many times each line of a source file
.Sq Ar sourcefile Ns Li \&.c
has executed.
These logfiles can then be used along with
.Xr gprof 1
to aid in fine-tuning the performance of the programs.
.Xr gprof 1
gives timing information which can be used along with the information you
obtained from
.Nm gcov .
.Pp
.Nm
works only on code compiled with GNU CC.
It is not compatible with any other profiling or test coverage mechanism.
.Pp
.Nm
accepts the following options:
.Bl -tag -width Ds
.It Fl b
Write branch frequencies to the output file, and write branch
summary info to the standard output.
This option indicates how often each branch in the program was taken.
.It Fl v
Display the
.Nm
version number
.Pq on the standard error stream .
.It Fl n
Do not create the
.Nm
output file.
.It Fl l
Create long file names for included source files.
For example, if the header file
.Pa x.h
contains code, and was included in the file
.Pa a.c ,
then running
.Nm
on the file
.Pa a.c
will produce an output file called
.Pa a.c.x.h.gcov
instead of
.Pa x.h.gcov .
This can be useful if
.Pa x.h
is included in multiple source files.
.It Fl f
Output summaries for each function in addition to the file level summary.
.It Fl o Ar directory
The directory where the object files live.
.Nm
will search for
.Pa .bb , .bbg ,
and
.Pa .da
files in this directory.
.El
.Pp
When using
.Nm gcov ,
programs must first be compiled with two special GNU CC options:
.Fl fprofile-arcs ftest-coverage .
This tells the compiler to generate additional information needed by
.Nm
.Pq basically a flow graph of the program
and also includes additional code in the object files for generating the
extra profiling information needed by
.Nm gcov .
These additional files are placed in the directory where the source code
is located.
.Pp
Running the program will cause profile output to be generated.
For each source file compiled with
.Fl fprofile-arcs ,
an accompanying
.Pa .da
file will be placed in the source directory.
.Pp
Running
.Nm
with the program's source file names as arguments
will now produce a listing of the code along with frequency of execution
for each line.
For example, if the program is called
.Pa tmp.c ,
this is what is displayed when using the basic
.Nm
facility:
.Bd -literal -offset indent
$ gcc -fprofile-arcs -ftest-coverage tmp.c
$ a.out
$ gcov tmp.c
 87.50% of 8 source lines executed in file tmp.c
Creating tmp.c.gcov.
.Ed
.Pp
The file
.Pa tmp.c.gcov
contains output from
.Nm gcov .
Here is a sample:
.Bd -unfilled -offset indent
     	main()
     	{
     1	    int i, total;

     1      total = 0;

    11      for (i = 0; i < 10; i++)
    10          total += i;

     1      if (total != 45)
######          printf ("Failure\\n");
            else
     1          printf ("Success\\n");
     1    }
.Ed
.Pp
When the
.Fl b
option is used, output looks like this:
.Pp
.Dl $ gcov -b tmp.c
.Bd -unfilled -offset indent -compact
 87.50% of 8 source lines executed in file tmp.c
 80.00% of 5 branches executed in file tmp.c
 80.00% of 5 branches taken at least once in file tmp.c
 50.00% of 2 calls executed in file tmp.c
Creating tmp.c.gcov.
.Ed
.Pp
Here is a sample of a resulting
.Pa tmp.c.gcov
file:
.Bd -unfilled -offset indent
                main()
                {
           1        int i, total;

           1        total = 0;

          11        for (i = 0; i < 10; i++)
branch 0 taken = 91%
branch 1 taken = 100%
branch 2 taken = 100%
          10        total += i;

           1        if (total != 45)
branch 0 taken = 100%
      ######            printf ("Failure\\n");
call 0 never executed
branch 1 never executed
                    else
           1            printf ("Success\\n");
call 0 returns = 100%
           1    }
.Ed
.Pp
For each basic block, a line is printed after the last line of the
basic block describing the branch or call that ends the basic block.
There can be multiple branches and calls listed for a single source
line if there are multiple basic blocks that end on that line.
In this case, the branches and calls are each given a number.
There is no simple way to map these branches and calls back to source
constructs.
In general, though, the lowest numbered branch or call will correspond
to the leftmost construct on the source line.
.Pp
For a branch, if it was executed at least once, then a percentage
indicating the number of times the branch was taken divided by the
number of times the branch was executed will be printed.
Otherwise, the message
.Qq never executed
is printed.
.Pp
For a call, if it was executed at least once, then a percentage
indicating the number of times the call returned divided by the number
of times the call was executed will be printed.
This will usually be 100%,
but may be less for functions which call
.Sq exit
or
.Sq longjmp ,
and thus may not return every time they are called.
.Pp
The execution counts are cumulative.
If the example program were executed again without removing the
.Pa .da
file,
the count for the number of times each line in the source was executed
would be added to the results of the previous run(s).
This is potentially useful in several ways.
For example, it could be used to accumulate data over a
number of program runs as part of a test verification suite,
or to provide more accurate long-term information over a large number of
program runs.
.Pp
The data in the
.Pa .da
files is saved immediately before the program exits.
For each source file compiled with
.Fl fprofile-arcs ,
the profiling code first attempts to read in an existing
.Pa .da
file;
if the file doesn't match the executable
.Pq differing number of basic block counts
it will ignore the contents of the file.
It then adds in the new execution counts and finally writes the data
to the file.
.Sh USING GCOV WITH GCC OPTIMIZATION
If
.Nm
is to be used to help optimize code,
programs must be compiled with two special GNU CC options:
.Fl fprofile-arcs ftest-coverage .
Aside from that, any other GNU CC options can be used;
but if you want to prove that every single line in your
program was executed, you should not compile with optimization at the
same time.
On some machines the optimizer can eliminate some simple
code lines by combining them with other lines.
For example, code like this:
.Bd -unfilled -offset indent
if (a != b)
  c = 1;
else
  c = 0;
.Ed
.Pp
can be compiled into one instruction on some machines.
In this case, there is no way for
.Nm
to calculate separate execution counts for each line because there
isn't separate code for each line.
Hence the
.Nm
output looks like this if the program is compiled with optimization:
.Bd -unfilled -offset indent
100  if (a != b)
100      c = 1;
100  else
100      c = 0;
.Ed
.Pp
The output shows that this block of code, combined by optimization,
executed 100 times.
In one sense this result is correct,
because there was only one instruction representing all four of these lines.
However, the output does not indicate how many times the result was 0 and how
many times the result was 1.
.Sh BRIEF DESCRIPTION OF GCOV DATA FILES
.Nm
uses three files for doing profiling.
The names of these files are derived from the original _source_ file
by substituting the file suffix with either
.Pa .bb , .bbg ,
or
.Pa .da .
All of these files are placed in the same directory as the source file,
and contain data stored in a platform-independent method.
.Pp
The
.Pa .bb
and
.Pa .bbg
files are generated when the source file is compiled with the GNU CC
.Fl ftest-coverage
option.
The
.Pa .bb
file contains a list of source files
.Pq including headers ,
functions within those files,
and line numbers corresponding to each basic block in the source file.
.Pp
The
.Pa .bb
file format consists of several lists of 4-byte integers
which correspond to the line numbers of each basic block in the file.
Each list is terminated by a line number of 0.
A line number of \-1 is used to designate that the source file name
(padded to a 4-byte boundary and followed by another \-1) follows.
In addition, a line number of \-2 is used to designate that the name of a
function (also padded to a 4-byte boundary and followed by a \-2) follows.
.Pp
The
.Pa .bbg
file is used to reconstruct the program flow graph for the source file.
It contains a list of the program flow arcs
(possible branches taken from one basic block to another)
for each function which,
in combination with the
.Pa .bb
file,
enables
.Nm
to reconstruct the program flow.
.Pp
In the
.Pa .bbg
file, the format is:
.Bd -unfilled -offset indent
number of basic blocks for function #0 (4-byte number)
total number of arcs for function #0 (4-byte number)
count of arcs in basic block #0 (4-byte number)
destination basic block of arc #0 (4-byte number)
flag bits (4-byte number)
destination basic block of arc #1 (4-byte number)
flag bits (4-byte number)
\&...
destination basic block of arc #N (4-byte number)
flag bits (4-byte number)
count of arcs in basic block #1 (4-byte number)
destination basic block of arc #0 (4-byte number)
flag bits (4-byte number)
\&...
.Ed
.Pp
A \-1
.Pq stored as a 4-byte number
is used to separate each function's list of basic blocks,
and to verify that the file has been read correctly.
.Pp
The
.Pa .da
file is generated when a program containing object files
built with the GNU CC
.Fl fprofile-arcs
option is executed.
A separate
.Pa .da
file is created for each source file compiled with this option,
and the name of the
.Pa .da
file is stored as an absolute pathname in the resulting object file.
This path name is derived from the source file name by substituting a
.Pa .da
suffix.
.Pp
The format of the
.Pa .da
file is fairly simple.
The first 8-byte number is the number of counts in the file,
followed by the counts
.Pq stored as 8-byte numbers .
Each count corresponds to the number of
times each arc in the program is executed.
The counts are cumulative;
each time the program is executed, it attempts to combine the existing
.Pa .da
files with the new counts for this invocation of the program.
It ignores the contents of any
.Pa .da
files whose number of arcs doesn't
correspond to the current program,
and merely overwrites them instead.
.Pp
All three of these files use the functions in
.Pa gcov-io.h
to store integers;
the functions in this header provide a machine-independent
mechanism for storing and retrieving data from a stream.
.Sh SEE ALSO
.Xr gcc 1 ,
.Xr gcc-local 1 ,
.Xr gprof 1
.Sh HISTORY
This man page describes version 1.5 of
.Nm gcov .