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This is, produced by makeinfo version 4.0 from gprof.texi.
* gprof: (gprof). Profiling your program's execution
This file documents the gprof profiler of the GNU system.
Copyright (C) 1988, 92, 97, 98, 99, 2000 Free Software Foundation,
Permission is granted to copy, distribute and/or modify this document
under the terms of the GNU Free Documentation License, Version 1.1
or any later version published by the Free Software Foundation;
with no Invariant Sections, with no Front-Cover Texts, and with no
Back-Cover Texts. A copy of the license is included in the
section entitled "GNU Free Documentation License".

File:, Node: Line-by-line, Next: Annotated Source, Prev: Call Graph, Up: Output
Line-by-line Profiling
`gprof''s `-l' option causes the program to perform "line-by-line"
profiling. In this mode, histogram samples are assigned not to
functions, but to individual lines of source code. The program usually
must be compiled with a `-g' option, in addition to `-pg', in order to
generate debugging symbols for tracking source code lines.
The flat profile is the most useful output table in line-by-line
mode. The call graph isn't as useful as normal, since the current
version of `gprof' does not propagate call graph arcs from source code
lines to the enclosing function. The call graph does, however, show
each line of code that called each function, along with a count.
Here is a section of `gprof''s output, without line-by-line
profiling. Note that `ct_init' accounted for four histogram hits, and
13327 calls to `init_block'.
Flat profile:
Each sample counts as 0.01 seconds.
% cumulative self self total
time seconds seconds calls us/call us/call name
30.77 0.13 0.04 6335 6.31 6.31 ct_init
Call graph (explanation follows)
granularity: each sample hit covers 4 byte(s) for 7.69% of 0.13 seconds
index % time self children called name
0.00 0.00 1/13496 name_too_long
0.00 0.00 40/13496 deflate
0.00 0.00 128/13496 deflate_fast
0.00 0.00 13327/13496 ct_init
[7] 0.0 0.00 0.00 13496 init_block
Now let's look at some of `gprof''s output from the same program run,
this time with line-by-line profiling enabled. Note that `ct_init''s
four histogram hits are broken down into four lines of source code -
one hit occurred on each of lines 349, 351, 382 and 385. In the call
graph, note how `ct_init''s 13327 calls to `init_block' are broken down
into one call from line 396, 3071 calls from line 384, 3730 calls from
line 385, and 6525 calls from 387.
Flat profile:
Each sample counts as 0.01 seconds.
% cumulative self
time seconds seconds calls name
7.69 0.10 0.01 ct_init (trees.c:349)
7.69 0.11 0.01 ct_init (trees.c:351)
7.69 0.12 0.01 ct_init (trees.c:382)
7.69 0.13 0.01 ct_init (trees.c:385)
Call graph (explanation follows)
granularity: each sample hit covers 4 byte(s) for 7.69% of 0.13 seconds
% time self children called name
0.00 0.00 1/13496 name_too_long (gzip.c:1440)
0.00 0.00 1/13496 deflate (deflate.c:763)
0.00 0.00 1/13496 ct_init (trees.c:396)
0.00 0.00 2/13496 deflate (deflate.c:727)
0.00 0.00 4/13496 deflate (deflate.c:686)
0.00 0.00 5/13496 deflate (deflate.c:675)
0.00 0.00 12/13496 deflate (deflate.c:679)
0.00 0.00 16/13496 deflate (deflate.c:730)
0.00 0.00 128/13496 deflate_fast (deflate.c:654)
0.00 0.00 3071/13496 ct_init (trees.c:384)
0.00 0.00 3730/13496 ct_init (trees.c:385)
0.00 0.00 6525/13496 ct_init (trees.c:387)
[6] 0.0 0.00 0.00 13496 init_block (trees.c:408)

File:, Node: Annotated Source, Prev: Line-by-line, Up: Output
The Annotated Source Listing
`gprof''s `-A' option triggers an annotated source listing, which
lists the program's source code, each function labeled with the number
of times it was called. You may also need to specify the `-I' option,
if `gprof' can't find the source code files.
Compiling with `gcc ... -g -pg -a' augments your program with
basic-block counting code, in addition to function counting code. This
enables `gprof' to determine how many times each line of code was
executed. For example, consider the following function, taken from
gzip, with line numbers added:
1 ulg updcrc(s, n)
2 uch *s;
3 unsigned n;
4 {
5 register ulg c;
7 static ulg crc = (ulg)0xffffffffL;
9 if (s == NULL) {
10 c = 0xffffffffL;
11 } else {
12 c = crc;
13 if (n) do {
14 c = crc_32_tab[...];
15 } while (--n);
16 }
17 crc = c;
18 return c ^ 0xffffffffL;
19 }
`updcrc' has at least five basic-blocks. One is the function
itself. The `if' statement on line 9 generates two more basic-blocks,
one for each branch of the `if'. A fourth basic-block results from the
`if' on line 13, and the contents of the `do' loop form the fifth
basic-block. The compiler may also generate additional basic-blocks to
handle various special cases.
A program augmented for basic-block counting can be analyzed with
`gprof -l -A'. I also suggest use of the `-x' option, which ensures
that each line of code is labeled at least once. Here is `updcrc''s
annotated source listing for a sample `gzip' run:
ulg updcrc(s, n)
uch *s;
unsigned n;
2 ->{
register ulg c;
static ulg crc = (ulg)0xffffffffL;
2 -> if (s == NULL) {
1 -> c = 0xffffffffL;
1 -> } else {
1 -> c = crc;
1 -> if (n) do {
26312 -> c = crc_32_tab[...];
26312,1,26311 -> } while (--n);
2 -> crc = c;
2 -> return c ^ 0xffffffffL;
2 ->}
In this example, the function was called twice, passing once through
each branch of the `if' statement. The body of the `do' loop was
executed a total of 26312 times. Note how the `while' statement is
annotated. It began execution 26312 times, once for each iteration
through the loop. One of those times (the last time) it exited, while
it branched back to the beginning of the loop 26311 times.

File:, Node: Inaccuracy, Next: How do I?, Prev: Output, Up: Top
Inaccuracy of `gprof' Output
* Menu:
* Sampling Error:: Statistical margins of error
* Assumptions:: Estimating children times

File:, Node: Sampling Error, Next: Assumptions, Up: Inaccuracy
Statistical Sampling Error
The run-time figures that `gprof' gives you are based on a sampling
process, so they are subject to statistical inaccuracy. If a function
runs only a small amount of time, so that on the average the sampling
process ought to catch that function in the act only once, there is a
pretty good chance it will actually find that function zero times, or
By contrast, the number-of-calls and basic-block figures are derived
by counting, not sampling. They are completely accurate and will not
vary from run to run if your program is deterministic.
The "sampling period" that is printed at the beginning of the flat
profile says how often samples are taken. The rule of thumb is that a
run-time figure is accurate if it is considerably bigger than the
sampling period.
The actual amount of error can be predicted. For N samples, the
_expected_ error is the square-root of N. For example, if the sampling
period is 0.01 seconds and `foo''s run-time is 1 second, N is 100
samples (1 second/0.01 seconds), sqrt(N) is 10 samples, so the expected
error in `foo''s run-time is 0.1 seconds (10*0.01 seconds), or ten
percent of the observed value. Again, if the sampling period is 0.01
seconds and `bar''s run-time is 100 seconds, N is 10000 samples,
sqrt(N) is 100 samples, so the expected error in `bar''s run-time is 1
second, or one percent of the observed value. It is likely to vary
this much _on the average_ from one profiling run to the next.
(_Sometimes_ it will vary more.)
This does not mean that a small run-time figure is devoid of
information. If the program's _total_ run-time is large, a small
run-time for one function does tell you that that function used an
insignificant fraction of the whole program's time. Usually this means
it is not worth optimizing.
One way to get more accuracy is to give your program more (but
similar) input data so it will take longer. Another way is to combine
the data from several runs, using the `-s' option of `gprof'. Here is
1. Run your program once.
2. Issue the command `mv gmon.out gmon.sum'.
3. Run your program again, the same as before.
4. Merge the new data in `gmon.out' into `gmon.sum' with this command:
gprof -s EXECUTABLE-FILE gmon.out gmon.sum
5. Repeat the last two steps as often as you wish.
6. Analyze the cumulative data using this command:

File:, Node: Assumptions, Prev: Sampling Error, Up: Inaccuracy
Estimating `children' Times
Some of the figures in the call graph are estimates--for example, the
`children' time values and all the the time figures in caller and
subroutine lines.
There is no direct information about these measurements in the
profile data itself. Instead, `gprof' estimates them by making an
assumption about your program that might or might not be true.
The assumption made is that the average time spent in each call to
any function `foo' is not correlated with who called `foo'. If `foo'
used 5 seconds in all, and 2/5 of the calls to `foo' came from `a',
then `foo' contributes 2 seconds to `a''s `children' time, by
This assumption is usually true enough, but for some programs it is
far from true. Suppose that `foo' returns very quickly when its
argument is zero; suppose that `a' always passes zero as an argument,
while other callers of `foo' pass other arguments. In this program,
all the time spent in `foo' is in the calls from callers other than `a'.
But `gprof' has no way of knowing this; it will blindly and incorrectly
charge 2 seconds of time in `foo' to the children of `a'.
We hope some day to put more complete data into `gmon.out', so that
this assumption is no longer needed, if we can figure out how. For the
nonce, the estimated figures are usually more useful than misleading.

File:, Node: How do I?, Next: Incompatibilities, Prev: Inaccuracy, Up: Top
Answers to Common Questions
How do I find which lines in my program were executed the most times?
Compile your program with basic-block counting enabled, run it,
then use the following pipeline:
gprof -l -C OBJFILE | sort -k 3 -n -r
This listing will show you the lines in your code executed most
often, but not necessarily those that consumed the most time.
How do I find which lines in my program called a particular function?
Use `gprof -l' and lookup the function in the call graph. The
callers will be broken down by function and line number.
How do I analyze a program that runs for less than a second?
Try using a shell script like this one:
for i in `seq 1 100`; do
mv gmon.out gmon.out.$i
gprof -s fastprog gmon.out.*
gprof fastprog gmon.sum
If your program is completely deterministic, all the call counts
will be simple multiples of 100 (i.e. a function called once in
each run will appear with a call count of 100).

File:, Node: Incompatibilities, Next: Details, Prev: How do I?, Up: Top
Incompatibilities with Unix `gprof'
GNU `gprof' and Berkeley Unix `gprof' use the same data file
`gmon.out', and provide essentially the same information. But there
are a few differences.
* GNU `gprof' uses a new, generalized file format with support for
basic-block execution counts and non-realtime histograms. A magic
cookie and version number allows `gprof' to easily identify new
style files. Old BSD-style files can still be read. *Note File
* For a recursive function, Unix `gprof' lists the function as a
parent and as a child, with a `calls' field that lists the number
of recursive calls. GNU `gprof' omits these lines and puts the
number of recursive calls in the primary line.
* When a function is suppressed from the call graph with `-e', GNU
`gprof' still lists it as a subroutine of functions that call it.
* GNU `gprof' accepts the `-k' with its argument in the form
`from/to', instead of `from to'.
* In the annotated source listing, if there are multiple basic
blocks on the same line, GNU `gprof' prints all of their counts,
separated by commas.
* The blurbs, field widths, and output formats are different. GNU
`gprof' prints blurbs after the tables, so that you can see the
tables without skipping the blurbs.

File:, Node: Details, Next: GNU Free Documentation License, Prev: Incompatibilities, Up: Top
Details of Profiling
* Menu:
* Implementation:: How a program collects profiling information
* File Format:: Format of `gmon.out' files
* Internals:: `gprof''s internal operation
* Debugging:: Using `gprof''s `-d' option

File:, Node: Implementation, Next: File Format, Up: Details
Implementation of Profiling
Profiling works by changing how every function in your program is
compiled so that when it is called, it will stash away some information
about where it was called from. From this, the profiler can figure out
what function called it, and can count how many times it was called.
This change is made by the compiler when your program is compiled with
the `-pg' option, which causes every function to call `mcount' (or
`_mcount', or `__mcount', depending on the OS and compiler) as one of
its first operations.
The `mcount' routine, included in the profiling library, is
responsible for recording in an in-memory call graph table both its
parent routine (the child) and its parent's parent. This is typically
done by examining the stack frame to find both the address of the
child, and the return address in the original parent. Since this is a
very machine-dependent operation, `mcount' itself is typically a short
assembly-language stub routine that extracts the required information,
and then calls `__mcount_internal' (a normal C function) with two
arguments - `frompc' and `selfpc'. `__mcount_internal' is responsible
for maintaining the in-memory call graph, which records `frompc',
`selfpc', and the number of times each of these call arcs was traversed.
GCC Version 2 provides a magical function
(`__builtin_return_address'), which allows a generic `mcount' function
to extract the required information from the stack frame. However, on
some architectures, most notably the SPARC, using this builtin can be
very computationally expensive, and an assembly language version of
`mcount' is used for performance reasons.
Number-of-calls information for library routines is collected by
using a special version of the C library. The programs in it are the
same as in the usual C library, but they were compiled with `-pg'. If
you link your program with `gcc ... -pg', it automatically uses the
profiling version of the library.
Profiling also involves watching your program as it runs, and
keeping a histogram of where the program counter happens to be every
now and then. Typically the program counter is looked at around 100
times per second of run time, but the exact frequency may vary from
system to system.
This is done is one of two ways. Most UNIX-like operating systems
provide a `profil()' system call, which registers a memory array with
the kernel, along with a scale factor that determines how the program's
address space maps into the array. Typical scaling values cause every
2 to 8 bytes of address space to map into a single array slot. On
every tick of the system clock (assuming the profiled program is
running), the value of the program counter is examined and the
corresponding slot in the memory array is incremented. Since this is
done in the kernel, which had to interrupt the process anyway to handle
the clock interrupt, very little additional system overhead is required.
However, some operating systems, most notably Linux 2.0 (and
earlier), do not provide a `profil()' system call. On such a system,
arrangements are made for the kernel to periodically deliver a signal
to the process (typically via `setitimer()'), which then performs the
same operation of examining the program counter and incrementing a slot
in the memory array. Since this method requires a signal to be
delivered to user space every time a sample is taken, it uses
considerably more overhead than kernel-based profiling. Also, due to
the added delay required to deliver the signal, this method is less
accurate as well.
A special startup routine allocates memory for the histogram and
either calls `profil()' or sets up a clock signal handler. This
routine (`monstartup') can be invoked in several ways. On Linux
systems, a special profiling startup file `gcrt0.o', which invokes
`monstartup' before `main', is used instead of the default `crt0.o'.
Use of this special startup file is one of the effects of using `gcc
... -pg' to link. On SPARC systems, no special startup files are used.
Rather, the `mcount' routine, when it is invoked for the first time
(typically when `main' is called), calls `monstartup'.
If the compiler's `-a' option was used, basic-block counting is also
enabled. Each object file is then compiled with a static array of
counts, initially zero. In the executable code, every time a new
basic-block begins (i.e. when an `if' statement appears), an extra
instruction is inserted to increment the corresponding count in the
array. At compile time, a paired array was constructed that recorded
the starting address of each basic-block. Taken together, the two
arrays record the starting address of every basic-block, along with the
number of times it was executed.
The profiling library also includes a function (`mcleanup') which is
typically registered using `atexit()' to be called as the program
exits, and is responsible for writing the file `gmon.out'. Profiling
is turned off, various headers are output, and the histogram is
written, followed by the call-graph arcs and the basic-block counts.
The output from `gprof' gives no indication of parts of your program
that are limited by I/O or swapping bandwidth. This is because samples
of the program counter are taken at fixed intervals of the program's
run time. Therefore, the time measurements in `gprof' output say
nothing about time that your program was not running. For example, a
part of the program that creates so much data that it cannot all fit in
physical memory at once may run very slowly due to thrashing, but
`gprof' will say it uses little time. On the other hand, sampling by
run time has the advantage that the amount of load due to other users
won't directly affect the output you get.

File:, Node: File Format, Next: Internals, Prev: Implementation, Up: Details
Profiling Data File Format
The old BSD-derived file format used for profile data does not
contain a magic cookie that allows to check whether a data file really
is a `gprof' file. Furthermore, it does not provide a version number,
thus rendering changes to the file format almost impossible. GNU
`gprof' uses a new file format that provides these features. For
backward compatibility, GNU `gprof' continues to support the old
BSD-derived format, but not all features are supported with it. For
example, basic-block execution counts cannot be accommodated by the old
file format.
The new file format is defined in header file `gmon_out.h'. It
consists of a header containing the magic cookie and a version number,
as well as some spare bytes available for future extensions. All data
in a profile data file is in the native format of the host on which the
profile was collected. GNU `gprof' adapts automatically to the
byte-order in use.
In the new file format, the header is followed by a sequence of
records. Currently, there are three different record types: histogram
records, call-graph arc records, and basic-block execution count
records. Each file can contain any number of each record type. When
reading a file, GNU `gprof' will ensure records of the same type are
compatible with each other and compute the union of all records. For
example, for basic-block execution counts, the union is simply the sum
of all execution counts for each basic-block.
Histogram Records
Histogram records consist of a header that is followed by an array of
bins. The header contains the text-segment range that the histogram
spans, the size of the histogram in bytes (unlike in the old BSD
format, this does not include the size of the header), the rate of the
profiling clock, and the physical dimension that the bin counts
represent after being scaled by the profiling clock rate. The physical
dimension is specified in two parts: a long name of up to 15 characters
and a single character abbreviation. For example, a histogram
representing real-time would specify the long name as "seconds" and the
abbreviation as "s". This feature is useful for architectures that
support performance monitor hardware (which, fortunately, is becoming
increasingly common). For example, under DEC OSF/1, the "uprofile"
command can be used to produce a histogram of, say, instruction cache
misses. In this case, the dimension in the histogram header could be
set to "i-cache misses" and the abbreviation could be set to "1"
(because it is simply a count, not a physical dimension). Also, the
profiling rate would have to be set to 1 in this case.
Histogram bins are 16-bit numbers and each bin represent an equal
amount of text-space. For example, if the text-segment is one thousand
bytes long and if there are ten bins in the histogram, each bin
represents one hundred bytes.
Call-Graph Records
Call-graph records have a format that is identical to the one used in
the BSD-derived file format. It consists of an arc in the call graph
and a count indicating the number of times the arc was traversed during
program execution. Arcs are specified by a pair of addresses: the
first must be within caller's function and the second must be within
the callee's function. When performing profiling at the function
level, these addresses can point anywhere within the respective
function. However, when profiling at the line-level, it is better if
the addresses are as close to the call-site/entry-point as possible.
This will ensure that the line-level call-graph is able to identify
exactly which line of source code performed calls to a function.
Basic-Block Execution Count Records
Basic-block execution count records consist of a header followed by a
sequence of address/count pairs. The header simply specifies the
length of the sequence. In an address/count pair, the address
identifies a basic-block and the count specifies the number of times
that basic-block was executed. Any address within the basic-address can
be used.

File:, Node: Internals, Next: Debugging, Prev: File Format, Up: Details
`gprof''s Internal Operation
Like most programs, `gprof' begins by processing its options.
During this stage, it may building its symspec list
(`sym_ids.c:sym_id_add'), if options are specified which use symspecs.
`gprof' maintains a single linked list of symspecs, which will
eventually get turned into 12 symbol tables, organized into six
include/exclude pairs - one pair each for the flat profile
(INCL_FLAT/EXCL_FLAT), the call graph arcs (INCL_ARCS/EXCL_ARCS),
printing in the call graph (INCL_GRAPH/EXCL_GRAPH), timing propagation
in the call graph (INCL_TIME/EXCL_TIME), the annotated source listing
(INCL_ANNO/EXCL_ANNO), and the execution count listing
After option processing, `gprof' finishes building the symspec list
by adding all the symspecs in `default_excluded_list' to the exclude
lists EXCL_TIME and EXCL_GRAPH, and if line-by-line profiling is
specified, EXCL_FLAT as well. These default excludes are not added to
Next, the BFD library is called to open the object file, verify that
it is an object file, and read its symbol table (`core.c:core_init'),
using `bfd_canonicalize_symtab' after mallocing an appropriately sized
array of symbols. At this point, function mappings are read (if the
`--file-ordering' option has been specified), and the core text space
is read into memory (if the `-c' option was given).
`gprof''s own symbol table, an array of Sym structures, is now built.
This is done in one of two ways, by one of two routines, depending on
whether line-by-line profiling (`-l' option) has been enabled. For
normal profiling, the BFD canonical symbol table is scanned. For
line-by-line profiling, every text space address is examined, and a new
symbol table entry gets created every time the line number changes. In
either case, two passes are made through the symbol table - one to
count the size of the symbol table required, and the other to actually
read the symbols. In between the two passes, a single array of type
`Sym' is created of the appropriate length. Finally,
`symtab.c:symtab_finalize' is called to sort the symbol table and
remove duplicate entries (entries with the same memory address).
The symbol table must be a contiguous array for two reasons. First,
the `qsort' library function (which sorts an array) will be used to
sort the symbol table. Also, the symbol lookup routine
(`symtab.c:sym_lookup'), which finds symbols based on memory address,
uses a binary search algorithm which requires the symbol table to be a
sorted array. Function symbols are indicated with an `is_func' flag.
Line number symbols have no special flags set. Additionally, a symbol
can have an `is_static' flag to indicate that it is a local symbol.
With the symbol table read, the symspecs can now be translated into
Syms (`sym_ids.c:sym_id_parse'). Remember that a single symspec can
match multiple symbols. An array of symbol tables (`syms') is created,
each entry of which is a symbol table of Syms to be included or
excluded from a particular listing. The master symbol table and the
symspecs are examined by nested loops, and every symbol that matches a
symspec is inserted into the appropriate syms table. This is done
twice, once to count the size of each required symbol table, and again
to build the tables, which have been malloced between passes. From now
on, to determine whether a symbol is on an include or exclude symspec
list, `gprof' simply uses its standard symbol lookup routine on the
appropriate table in the `syms' array.
Now the profile data file(s) themselves are read
(`gmon_io.c:gmon_out_read'), first by checking for a new-style
`gmon.out' header, then assuming this is an old-style BSD `gmon.out' if
the magic number test failed.
New-style histogram records are read by `hist.c:hist_read_rec'. For
the first histogram record, allocate a memory array to hold all the
bins, and read them in. When multiple profile data files (or files
with multiple histogram records) are read, the starting address, ending
address, number of bins and sampling rate must match between the
various histograms, or a fatal error will result. If everything
matches, just sum the additional histograms into the existing in-memory
As each call graph record is read (`call_graph.c:cg_read_rec'), the
parent and child addresses are matched to symbol table entries, and a
call graph arc is created by `cg_arcs.c:arc_add', unless the arc fails
a symspec check against INCL_ARCS/EXCL_ARCS. As each arc is added, a
linked list is maintained of the parent's child arcs, and of the child's
parent arcs. Both the child's call count and the arc's call count are
incremented by the record's call count.
Basic-block records are read (`basic_blocks.c:bb_read_rec'), but
only if line-by-line profiling has been selected. Each basic-block
address is matched to a corresponding line symbol in the symbol table,
and an entry made in the symbol's bb_addr and bb_calls arrays. Again,
if multiple basic-block records are present for the same address, the
call counts are cumulative.
A gmon.sum file is dumped, if requested (`gmon_io.c:gmon_out_write').
If histograms were present in the data files, assign them to symbols
(`hist.c:hist_assign_samples') by iterating over all the sample bins
and assigning them to symbols. Since the symbol table is sorted in
order of ascending memory addresses, we can simple follow along in the
symbol table as we make our pass over the sample bins. This step
includes a symspec check against INCL_FLAT/EXCL_FLAT. Depending on the
histogram scale factor, a sample bin may span multiple symbols, in
which case a fraction of the sample count is allocated to each symbol,
proportional to the degree of overlap. This effect is rare for normal
profiling, but overlaps are more common during line-by-line profiling,
and can cause each of two adjacent lines to be credited with half a
hit, for example.
If call graph data is present, `cg_arcs.c:cg_assemble' is called.
First, if `-c' was specified, a machine-dependent routine (`find_call')
scans through each symbol's machine code, looking for subroutine call
instructions, and adding them to the call graph with a zero call count.
A topological sort is performed by depth-first numbering all the
symbols (`cg_dfn.c:cg_dfn'), so that children are always numbered less
than their parents, then making a array of pointers into the symbol
table and sorting it into numerical order, which is reverse topological
order (children appear before parents). Cycles are also detected at
this point, all members of which are assigned the same topological
number. Two passes are now made through this sorted array of symbol
pointers. The first pass, from end to beginning (parents to children),
computes the fraction of child time to propagate to each parent and a
print flag. The print flag reflects symspec handling of
INCL_GRAPH/EXCL_GRAPH, with a parent's include or exclude (print or no
print) property being propagated to its children, unless they
themselves explicitly appear in INCL_GRAPH or EXCL_GRAPH. A second
pass, from beginning to end (children to parents) actually propagates
the timings along the call graph, subject to a check against
INCL_TIME/EXCL_TIME. With the print flag, fractions, and timings now
stored in the symbol structures, the topological sort array is now
discarded, and a new array of pointers is assembled, this time sorted
by propagated time.
Finally, print the various outputs the user requested, which is now
fairly straightforward. The call graph (`cg_print.c:cg_print') and
flat profile (`hist.c:hist_print') are regurgitations of values already
computed. The annotated source listing
(`basic_blocks.c:print_annotated_source') uses basic-block information,
if present, to label each line of code with call counts, otherwise only
the function call counts are presented.
The function ordering code is marginally well documented in the
source code itself (`cg_print.c'). Basically, the functions with the
most use and the most parents are placed first, followed by other
functions with the most use, followed by lower use functions, followed
by unused functions at the end.

File:, Node: Debugging, Prev: Internals, Up: Details
Debugging `gprof'
If `gprof' was compiled with debugging enabled, the `-d' option
triggers debugging output (to stdout) which can be helpful in
understanding its operation. The debugging number specified is
interpreted as a sum of the following options:
2 - Topological sort
Monitor depth-first numbering of symbols during call graph analysis
4 - Cycles
Shows symbols as they are identified as cycle heads
16 - Tallying
As the call graph arcs are read, show each arc and how the total
calls to each function are tallied
32 - Call graph arc sorting
Details sorting individual parents/children within each call graph
64 - Reading histogram and call graph records
Shows address ranges of histograms as they are read, and each call
graph arc
128 - Symbol table
Reading, classifying, and sorting the symbol table from the object
file. For line-by-line profiling (`-l' option), also shows line
numbers being assigned to memory addresses.
256 - Static call graph
Trace operation of `-c' option
512 - Symbol table and arc table lookups
Detail operation of lookup routines
1024 - Call graph propagation
Shows how function times are propagated along the call graph
2048 - Basic-blocks
Shows basic-block records as they are read from profile data (only
meaningful with `-l' option)
4096 - Symspecs
Shows symspec-to-symbol pattern matching operation
8192 - Annotate source
Tracks operation of `-A' option