* class.c (check_bitfield_decl): New function, split out from

[official-gcc.git] / gcc / gcov.texi

@c Copyright (C) 1996, 1997 Free Software Foundation, Inc.
@c This is part of the GCC manual.
@c For copying conditions, see the file gcc.texi.

@node Gcov
@chapter @code{gcov}: a Test Coverage Program

@code{gcov} is a tool you can use in conjunction with @sc{gnu} CC to
test code coverage in your programs.

This chapter describes version 1.5 of @code{gcov}.

@menu
* Gcov Intro::                  Introduction to gcov.
* Invoking Gcov::               How to use gcov.
* Gcov and Optimization::       Using gcov with GCC optimization.
* Gcov Data Files::             The files used by gcov.
@end menu

@node Gcov Intro
@section Introduction to @code{gcov}

@code{gcov} is a test coverage program.  Use it in concert with @sc{gnu}
CC to analyze your programs to help create more efficient, faster
running code.  You can use @code{gcov} as a profiling tool to help
discover where your optimization efforts will best affect your code.  You
can also use @code{gcov} along with the other profiling tool,
@code{gprof}, to assess which parts of your code use the greatest amount
of computing time.

Profiling tools help you analyze your code's performance.  Using a
profiler such as @code{gcov} or @code{gprof}, you can find out some
basic performance statistics, such as:

@itemize @bullet
@item
how often each line of code executes

@item
what lines of code are actually executed

@item
how much computing time each section of code uses
@end itemize

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.
@code{gcov} helps you determine where to work on optimization.

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.

You should compile your code without optimization if you plan to use
@code{gcov} because the optimization, by combining some lines of code
into one function, may not give you as much information as you need to
look for `hot spots' where the code is using a great deal of computer
time.  Likewise, because @code{gcov} accumulates statistics by line (at
the lowest resolution), it works best with a programming style that
places only one statement on each line.  If you use complicated macros
that expand to loops or to other control structures, the statistics are
less helpful---they only report on the line where the macro call
appears.  If your complex macros behave like functions, you can replace
them with inline functions to solve this problem.

@code{gcov} creates a logfile called @file{@var{sourcefile}.gcov} which
indicates how many times each line of a source file @file{@var{sourcefile}.c}
has executed.  You can use these logfiles along with @code{gprof} to aid
in fine-tuning the performance of your programs.  @code{gprof} gives
timing information you can use along with the information you get from
@code{gcov}.

@code{gcov} works only on code compiled with @sc{gnu} CC.  It is not
compatible with any other profiling or test coverage mechanism.

@node Invoking Gcov
@section Invoking gcov

@smallexample
gcov [-b] [-v] [-n] [-l] [-f] [-o directory] @var{sourcefile}
@end smallexample

@table @code
@item -b 
Write branch frequencies to the output file, and write branch summary
info to the standard output.  This option allows you to see how often
each branch in your program was taken.

@item -v
Display the @code{gcov} version number (on the standard error stream).

@item -n
Do not create the @code{gcov} output file.

@item -l
Create long file names for included source files.  For example, if the
header file @samp{x.h} contains code, and was included in the file
@samp{a.c}, then running @code{gcov} on the file @samp{a.c} will produce
an output file called @samp{a.c.x.h.gcov} instead of @samp{x.h.gcov}.
This can be useful if @samp{x.h} is included in multiple source files.

@item -f
Output summaries for each function in addition to the file level summary.

@item -o
The directory where the object files live.  Gcov will search for @code{.bb},
@code{.bbg}, and @code{.da} files in this directory.
@end table

@need 3000
When using @code{gcov}, you must first compile your program with two
special @sc{gnu} CC options: @samp{-fprofile-arcs -ftest-coverage}.
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 are placed in the
directory where the source code is located.

Running the program will cause profile output to be generated.  For each
source file compiled with -fprofile-arcs, an accompanying @code{.da}
file will be placed in the source directory.

Running @code{gcov} with your 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 your program is called @samp{tmp.c}, this
is what you see when you use the basic @code{gcov} facility:

@smallexample
$ 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.
@end smallexample

The file @file{tmp.c.gcov} contains output from @code{gcov}. 
Here is a sample:

@smallexample
                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    @}
@end smallexample

@need 450
When you use the @samp{-b} option, your output looks like this:

@smallexample
$ gcov -b tmp.c
 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.
@end smallexample

Here is a sample of a resulting @file{tmp.c.gcov} file:

@smallexample
                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    @}
@end smallexample

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.

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 ``never executed'' is printed.

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 call @code{exit} or @code{longjmp},
and thus may not return everytime they are called.

The execution counts are cumulative.  If the example program were
executed again without removing the @code{.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.

The data in the @code{.da} files is saved immediately before the program
exits.  For each source file compiled with -fprofile-arcs, the profiling
code first attempts to read in an existing @code{.da} file; if the file
doesn't match the executable (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.

@node Gcov and Optimization
@section Using @code{gcov} with GCC Optimization

If you plan to use @code{gcov} to help optimize your code, you must
first compile your program with two special @sc{gnu} CC options:
@samp{-fprofile-arcs -ftest-coverage}.  Aside from that, you can use any
other @sc{gnu} CC options; 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:

@smallexample
if (a != b)
  c = 1;
else
  c = 0;
@end smallexample

@noindent
can be compiled into one instruction on some machines.  In this case,
there is no way for @code{gcov} to calculate separate execution counts
for each line because there isn't separate code for each line.  Hence
the @code{gcov} output looks like this if you compiled the program with
optimization:

@smallexample
      100  if (a != b)
      100    c = 1;
      100  else
      100    c = 0;
@end smallexample

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.

@node Gcov Data Files
@section Brief description of @code{gcov} data files

@code{gcov} uses three files for doing profiling.  The names of these
files are derived from the original @emph{source} file by substituting
the file suffix with either @code{.bb}, @code{.bbg}, or @code{.da}.  All
of these files are placed in the same directory as the source file, and
contain data stored in a platform-independent method.

The @code{.bb} and @code{.bbg} files are generated when the source file
is compiled with the @sc{gnu} CC @samp{-ftest-coverage} option.  The
@code{.bb} file contains a list of source files (including headers),
functions within those files, and line numbers corresponding to each
basic block in the source file.

The @code{.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.

The @code{.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 @code{.bb} file, enables gcov to reconstruct the
program flow.

In the @code{.bbg} file, the format is:
@smallexample
        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)
        ...
@end smallexample

A -1 (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.

The @code{.da} file is generated when a program containing object files
built with the @sc{gnu} CC @samp{-fprofile-arcs} option is executed.  A
separate @code{.da} file is created for each source file compiled with
this option, and the name of the @code{.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 @code{.da} suffix.

The format of the @code{.da} file is fairly simple.  The first 8-byte
number is the number of counts in the file, followed by the counts
(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 attemps to combine the existing
@code{.da} files with the new counts for this invocation of the
program.  It ignores the contents of any @code{.da} files whose number of
arcs doesn't correspond to the current program, and merely overwrites
them instead.

All three of these files use the functions in @code{gcov-io.h} to store
integers; the functions in this header provide a machine-independent
mechanism for storing and retrieving data from a stream.