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Next: <a href="Incompatibilities.html#Incompatibilities" accesskey="n" rel="next">Incompatibilities</a>, Previous: <a href="Inaccuracy.html#Inaccuracy" accesskey="p" rel="prev">Inaccuracy</a>, Up: <a href="index.html#Top" accesskey="u" rel="up">Top</a> &nbsp; [<a href="index.html#SEC_Contents" title="Table of contents" rel="contents">Contents</a>]</p>
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<a name="Answers-to-Common-Questions"></a>
<h2 class="chapter">7 Answers to Common Questions</h2>
<dl compact="compact">
<dt>How can I get more exact information about hot spots in my program?</dt>
<dd>
<p>Looking at the per-line call counts only tells part of the story.
Because <code>gprof</code> can only report call times and counts by function,
the best way to get finer-grained information on where the program
is spending its time is to re-factor large functions into sequences
of calls to smaller ones. Beware however that this can introduce
artificial hot spots since compiling with &lsquo;<samp>-pg</samp>&rsquo; adds a significant
overhead to function calls. An alternative solution is to use a
non-intrusive profiler, e.g. oprofile.
</p>
</dd>
<dt>How do I find which lines in my program were executed the most times?</dt>
<dd>
<p>Use the <code>gcov</code> program.
</p>
</dd>
<dt>How do I find which lines in my program called a particular function?</dt>
<dd>
<p>Use &lsquo;<samp>gprof -l</samp>&rsquo; and lookup the function in the call graph.
The callers will be broken down by function and line number.
</p>
</dd>
<dt>How do I analyze a program that runs for less than a second?</dt>
<dd>
<p>Try using a shell script like this one:
</p>
<div class="example">
<pre class="example">for i in `seq 1 100`; do
fastprog
mv gmon.out gmon.out.$i
done
gprof -s fastprog gmon.out.*
gprof fastprog gmon.sum
</pre></div>
<p>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).
</p>
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