I'm writing a program in C++/Qt which contains a graph file parser. I use g++ to compile the project.
While developing, I am constantly comparing the performance of my low level parser layer between different compiler flags regarding optimization and debug information, plus Qt's debug flag (turning on/off qDebug() and Q_ASSERT()).
Now I'm facing a problem where the only correctly functioning build is the one without any optimization. All other versions, even with -O1, seem to work in another way. They crash due to unsatisfied assertions, which are satisfied when compiled without a -O... flag. The code doesn't produce any compiler warning, even with -Wall.
I am very sure that there is a bug in my program, which seems to be only harmful with optimization being enabled. The problem is: I can't find it even when debugging the program. The parser seems to read wrong data from the file. When I run some simple test cases, they run perfectly. When I run a bigger test case (a route calculation on a graph read directly from a file), there is an incorrect read in the file which I can't explain.
Where should I start tracking down the problem of this undefined behavior? Which optimization methods are possibly involved within this different behavior? (I could enable all flags one after the other, but I don't know that much compiler flags but -O... and I know that there are a lot of them, so this would need a very long time.) As soon as I know which type the bug is of, I am sure I find it sooner or later.
You can help me a lot if you can tell me which compiler optimization methods are possible candidates for such problems.
There are a few classes of bugs that commonly arise in optimized builds, that often don't arise in debug builds.
Un-initialized variables. The compiler can catch some but not all. Look at all your constructors, look at global variables. etc. Particularly look for uninitialized pointers. In a debug build memory is reset to zero, but in a release build it isn't.
Use of temporaries that have gone out of scope. For example when you return a reference to a local temporary in a function. These often work in debug builds because the stack is padded out more. The temporaries tend to survive on the stack a little longer.
array overruns writing of temporaries. For example if you create an array as a temporary in a function and then write one element beyond the end. Again, the stack will have extra space in debug ( for debugging information ) and your overrun won't hit program data.
There are optimizations you can disable from the optimized build to help make debugging the optimized version easier.
-g -O1 -fno-inline -fno-loop-optimize -fno-if-conversion -fno-if-conversion2 \
-fno-delayed-branch
This should make stepping through your code in the debugger a little easier to follow.
Another suggestion is that if the assertions you have do not give you enough information about what is causing the problem, you should consider adding more assertions. If you are afraid of performance issues, or assertion clutter, you can wrap them in a macro. This allows you to distinguish the debugging assertions from the ones you originally added, so they can be disabled or removed from your code later.
1) Use valgrind on the broken version. (For that matter, try valgrind on the working version, maybe you'll get lucky.)
2) Build the system with "-O1 -g" and step through your program with gdb. At the crash, what variable has an incorrect value? Re-run your program and note when that variable is written to (or when it isn't and should have been.)
Related
I am working on a plugin for an application. Due to a quirk of the SDK, I can only build my plugin as a Release build.
While working on a particular portion of my code, I have found odd behaviour. When stepping through it in the debugger, I get what appears to be heap corruption, and access violations within the SDKs functions, but there does not appear to be anything wrong with the code. The code runs fine outside the debugger.
Most importantly, if I turn off optimisation, I can step through it fine.
I know that I should not debug optimised code, but always thought it was because the compiler did things like inline functions, unroll or remove redundant loops and optimise away local variables. The debugger would have reduced visibility of what was going on yes, but it wouldn't break anything.
This makes me concerned that turning off optimisations is just hiding a bug. So my question is, should I be expecting to step through an optimised build like a debug build, or should I expect the debugger to break it?
Well, there are two questions:
Does turning off optimization hide bugs?
Does using a debugger break things?
The answer to both is sometimes.
Any change to build-options potentially both hides and exposes a different set of bugs, as well as altering how they are expressed.
Dito for changing the environment in which your program runs, and "under the debugger" is a completely different environment, than without.
That especially impacts race-conditions, which are hard to diagnose using a debugger.
See heisenbug.
I understand that valgrind can call memcheck to perform memory leak check, and in this case the compiled C++ executable program must contain debug information. Then, if I want to use valgrind/callgrind to perform profiling, must the executable contain debug information? I have run a small test, and it seems that valgrind/callgrind can work on release executable programs without debug information. Can anyone confirm it?
From Official Valgrind documentation link, following information can be found:
2.2. Getting started
First off, consider whether it might be beneficial to recompile your application and supporting libraries with debugging info enabled (the -g option).
Without debugging info, the best Valgrind tools will be able to do is guess which function a particular piece of code belongs to, which makes both error messages and profiling output nearly useless. With -g, you'll get messages which point directly to the relevant source code lines.
Another option you might like to consider, if you are working with C++, is -fno-inline. That makes it easier to see the function-call chain, which can help reduce confusion when navigating around large C++ apps. For example, debugging OpenOffice.org with Memcheck is a bit easier when using this option. You don't have to do this, but doing so helps Valgrind produce more accurate and less confusing error reports. Chances are you're set up like this already, if you intended to debug your program with GNU GDB, or some other debug.
Hence the recommended step is to recompile your program with -g option to get maximum information from the Valgrind.
According to the valgrind manual:
http://valgrind.org/docs/manual/manual-core.html
If you are planning to use Memcheck: On rare occasions, compiler optimisations (at -O2 and above, and sometimes -O1) have been observed to generate code which fools Memcheck into wrongly reporting uninitialised value errors, or missing uninitialised value errors. We have looked in detail into fixing this, and unfortunately the result is that doing so would give a further significant slowdown in what is already a slow tool. So the best solution is to turn off optimisation altogether. Since this often makes things unmanageably slow, a reasonable compromise is to use -O. This gets you the majority of the benefits of higher optimisation levels whilst keeping relatively small the chances of false positives or false negatives from Memcheck. Also, you should compile your code with -Wall because it can identify some or all of the problems that Valgrind can miss at the higher optimisation levels. (Using -Wall is also a good idea in general.) All other tools (as far as we know) are unaffected by optimisation level, and for profiling tools like Cachegrind it is better to compile your program at its normal optimisation level.
When compiler optimizes code, what is the scope of the optimizations? Can an optimization
a) span more than a set of nested braces?
b) span more than a function?
c) span more than a file?
We are chasing an obscure bug that seems to derive from optimization. Code crashes in release mode but not debug mode. And of course we are aware this could be heap corruption or other memory problem bur have been chasing this for a while now. One avenue we are considering is to selectively compile our files in debug mode until the problem goes away. In other words:
a) Start with all file compiled in release mode
b) Compile 1/2 the files in debug mode
if crash still seen, take half the release compiled files and compile in debug mode
if crash not seen, talk half the files compiled in debug mode and compile in release mode
repeat until we narrow in on suspect files
this is a binary search to narrow in on problem files
We are aware that if this is a memory issue, simple doing this mixed compilation may make the bug go away, but we are curous if we can narrow in on the problem files.
The outstanding question though is what is the scope of optimizations - can they span more than one file?
An optimization can do literally anything as long as it doesn't change the semantics of the behaviour defined by the language. That means the answers to your first questions (a), (b), and (c) are all yes. In practice, most compilers aren't that ambitious, but there are certainly some examples. Clang and LLVM have flags for link time optimization that allow optimizations to span pretty much the entire program. MSVC has a similar /GL flag that allows whole-program optimization.
Often the causes of these sorts of failures are uninitialized variables. Static analysis tools can be very helpful in finding problems like the one you're describing. I'm not sure your binary searching via optimizations is going to help you track down too much, though it is possible. Your bug could be the result of pretty complicated interactions between modules.
Good luck!
You can approximately identify problem files from call traces of crash in release mode. Then try to rebuild them without optimizations - this is much simpler than binary search.
To know about compiler optimization, one easy resourse could be wikipedia. It nicely explains in brief some important and wide-implemented optimizations by almost all modern compilers.
Maybe, you would like to read the wiki entry first, especially these sections:
Types of optimizations
Specific techniques
I think you are asking the wrong question.
It is unlikely (unless you are doing something special) that the optimizer is your problem.
The problem is most likely an uninitialized variable in your code.
When you compile in debug mode most compilers will initialize all memory to a specific pattern, so that during debugging you can see what has happened to the memory (was it allocated/ was it de-allcoated/ was it from the stack/ Was the stack popped back from etc).
Thus in debug mode any uninitialized memory has the a specific pattern that can be recognized by the debugger. The exact pattern will depend on the compiler. But this can make sloppy code work as the uninitialized pointers are NULL, integer counters start at 0 etc.
When you compile for release mode all the extra initialization is turned off. If you did not explicitly initialize the memory it is in a random state. This is what debug/release versions of an application behave differently.
The easy way to check for this is to check your compiler warnings.
Make sure that all variables are initialized before use (it will be in the warnings).
I've seen posts talk about what might cause differences between Debug and Release builds, but I don't think anybody has addressed from a development standpoint what is the most efficient way to solve the problem.
The first thing I do when a bug appears in the Release build but not in Debug is I run my program through valgrind in hopes of a better analysis. If that reveals nothing, -- and this has happened to me before -- then I try various inputs in hopes of getting the bug to surface also in the Debug build. If that fails, then I would try to track changes to find the most recent version for which the two builds diverge in behavior. And finally I guess I would resort to print statements.
Are there any best software engineering practices for efficiently debugging when the Debug and Release builds differ? Also, what tools are there that operate at a more fundamental level than valgrind to help debug these cases?
EDIT: I notice a lot of responses suggesting some general good practices such as unit testing and regression testing, which I agree are great for finding any bug. However, is there something specifically tailored to this Release vs. Debug problem? For example, is there such a thing as a static analysis tool that says "Hey, this macro or this code or this programming practice is dangerous because it has the potential to cause differences between your Debug/Release builds?"
One other "Best Practice", or rather a combination of two: Have Automated Unit Tests, and Divide and Conquer.
If you have a modular application, and each module has good unit tests, then you may be able to quickly isolate the errant piece.
The very existence of two configurations is a problem from debugging point of view. Proper engineering would be such that the system on the ground and in the air behave the same way, and achieve this by reducing the number of ways by which the system can tell the difference.
Debug and Release builds differ in 3 aspects:
_DEBUG define
optimizations
different version of the standard library
The best way around, the way I often work, is this:
Disable optimizations where performance is not critical. Debugging is more important. Most important is disable function auto-inlining, keep standard stack frame and variable reuse optimizations. These annoy debug the most.
Monitor code for dependence on DEBUG define. Never use debug-only asserts, or any other tools sensitive to DEBUG define.
By default, compile and work /release.
When I come across a bug that only happens in release, the first thing I always look for is use of an uninitialized stack variable in the code that I am working on. On Windows, the debug C runtime will automatically initialise stack variables to a know bit pattern, 0xcdcdcdcd or something. In release, stack variables will contain the value that was last stored at that memory location, which is going to be an unexpected value.
Secondly, I will try to identify what is different between debug and release builds. I look at the compiler optimization settings that the compiler is passed in Debug and Release configurations. You can see this is the last property page of the compiler settings in Visual Studio. I will start with the release config, and change the command line arguments passed to the compiler one item at a time until they match the command line that is used for compiling in debug. After each change I run the program and reproducing the bug. This will often lead me to the particular setting that causes the bug to happen.
A third technique can be to take a function that is misbehaving and disable optimizations around it using the pre-processor. This will allow you run the program in release with the particular function compiled in debug. The behaviour of the program which has been built in this way will help you learn more about the bug.
#pragma optimize( "", off )
void foo() {
return 1;
}
#pragma optimize( "", on )
From experience, the problems are usually stack initialization, memory scrubbing in the memory allocator, or strange #define directives causing the code to be compiled incorrectly.
The most obvious cause is simply the use of #ifdef and #ifndef directives associated DEBUG or similar symbol that change between the two builds.
Before going down the debugging road (which is not my personal idea of fun), I would inspect both command lines and check which flags are passed in one mode and not the other, then grep my code for this flags and check their uses.
One particular issue that comes to mind are macros:
#ifdef _DEBUG_
#define CHECK(CheckSymbol) { if (!(CheckSymbol)) throw CheckException(); }
#else
#define CHECK(CheckSymbol)
#endif
also known as a soft-assert.
Well, if you call it with a function that has side effect, or rely on it to guard a function (contract enforcement) and somehow catches the exception it throws in debug and ignore it... you will see differences in release :)
When debug and release differ it means:
you code depends on the _DEBUG or similar macros (defined when compiling a debug version - no optimizations)
your compiler has an optimization bug (I seen this few times)
You can easily deal with (1) (code modification) but with (2) you will have to isolate the compiler bug. After isolating the bug you do a little "code rewriting" to get the compiler generate correct binary code (I did this a few times - the most difficult part is to isolate the bug).
I can say that when enabling debug information for release version the debugging process works ... (though because of optimizations you might see some "strange" jumps when running).
You will need to have some "black-box" tests for your application - valgrind is a solution in this case. These solutions help you find differences between release and debug (which is very important).
The best solution is to set up something like automated unit testing to thoroughly test all aspects of the application (not just individual components, but real world tests which use the application the same way a regular user would with all of the dependencies). This allows you to know immediately when a release-only bug has been introduced which should give you a good idea of where the problem is.
Good practice to actively monitor and seek out problems beats any tool to help you fix them long after they happen.
However, when you have one of those cases where it's too late: too many builds have gone by, can't reproduce consistently, etc. then I don't know of any one tool for the job. Sometimes fiddling with your release settings can give a bit of insight as to why the bug is occurring: if you can eliminate optimizations which suddenly make the bug go away, that could give you some useful information about it.
Release-only bugs can fall into various categories, but the most common ones (aside from something like a misuse of assertions) is:
1) Uninitialized memory. I use this term over uninitialized variables as a variable may be initialized but still be pointing to memory which hasn't been initialized properly. For this, memory diagnostic tools like Valgrind can help.
2) Timing (ex: race conditions). These can be a nightmare to debug, but there are some multithreading profilers and diagnostic tools which can help. I can't suggest any off the bat, but there's Coverity Integrity Manager as one example.
Many times I work with optimized code (sometimes even involving vectorized loops), which contain bugs and such. How would one debug such code? I'm looking for any kind of tools or techniques. I use the following (possibly outdated) tools, so I'm looking to upgrade.
I use the following:
Since with ddd, you cannot see the code, I use gdb+ dissambler command and see the produced code; I can't really step through the program using this.
ndisasm
Thanks
It is always harder to debug optimised programs, but there are always ways. Some additional tips:
Make a debug build, and see if you get the same bug in a debug build. No point debugging an optimised version if you don't have to.
Use valgrind if on a platform that supports it. The errors you see may be harder to understand, but catching the problem early often simplifies debugging.
printf debugging is primitive, but sometimes it is the simplest way if you have a complex issue that only shows up in optimised builds.
If you suspect a timing issue (especially in a multithreaded program), roll your own version of assert which aborts or prints if the condition is violated, and use it in a few select places, to rule out possible problems.
See if you can reproduce the problem without using -fomit-frame-pointers, since that makes code very hard to debug, and with -O2 or -O3 enabled. That might give you enough information to find the cause of your problem.
Isolate parts of your code, build a test-suite, and see if you can identify any testcases which fail. It is much easier to debug one function than the whole program.
Try turning off optimisations one by one with the -fno-X options. This might help you find common problems like strict aliasing problems.
Turn on more compiler warnings. Some things, like strict aliasing problems, can generate compiler warnings if they create a difference in behaviour between different optimisation levels.
When debugging release builds you can put in __asm nops; as a placeholder for breakpoints (int 3). This is nice as you can guarantee breakpoint locations without messing up compiler optimizations or writing printf/cout statements.
It's always easier to debug a non-optimized version, of course. Failing that, disassembly of the code can be helpful. Other techinques I've used include partially de-optimizing the code by forcing intermediate results to be printed or logged, or changing a critical variable to "volatile" so I can at least look at that value in the debugger.
Chances are what you call optimized code is scrambled to shave cycles (which makes debugging hard) but is not really very optimized. Here is an example of what I mean.
I would turn off the compiler optimization, debug and tune it yourself, and then turn compiler optimization back on if the code has hotspots that are actually in code the compiler sees (not in outside libraries). (I define a hotspot as a part of code where the PC is often found. That automatically exempts loops containing function calls because they steal away the PC.)