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I am looking for a way to find out which lines are executed most often in my code. I am mainly using Xcode and Instruments.
Using Instruments, I already know how to get the heaviest stack traces using the Time Profiler, which samples my program.
I would like to study the code's performance under a different angle. I am not interested in finding the heaviest functions with regards to execution time, I want to find the heaviest functions with regards to number of invocations.
The closest I could get so far is by using llvm's code coverage tools through Xcode. After activating code coverage, I can see execution counts on the various lines of code of my program inside Xcode. Unfortunately, it is a large project and going through every file one by one isn't a good way to work. That's why I'm looking for an efficient way to enumerate the top results.
I have tried using llvm-cov on the command line, but I couldn't find any way to achieve my goal. The --line-coverage-gt parameter doesn't seem to achieve what it is supposed to do. Any value greater than 0 filters out the lines of code that weren't executed at all, but any number greater than 99 filters out everything. Some of the lines are executed tens of millions of times, but I can't get rid of the ones that got executed thousands of times.
Answers to this question can leverage Xcode, Instruments and llvm-cov without any issues. I'm also interested in other alternatives even though they might be harder to apply on my codebase.
Thank you!
This is intended to be a general-purpose question to assist new programmers who have a problem with a program, but who do not know how to use a debugger to diagnose the cause of the problem.
This question covers three classes of more specific question:
When I run my program, it does not produce the output I expect for the input I gave it.
When I run my program, it crashes and gives me a stack trace. I have examined the stack trace, but I still do not know the cause of the problem because the stack trace does not provide me with enough information.
When I run my program, it crashes because of a segmentation fault (SEGV).
A debugger is a program that can examine the state of your program while your program is running. The technical means it uses for doing this are not necessary for understanding the basics of using a debugger. You can use a debugger to halt the execution of your program when it reaches a particular place in your code, and then examine the values of the variables in the program. You can use a debugger to run your program very slowly, one line of code at a time (called single stepping), while you examine the values of its variables.
Using a debugger is an expected basic skill
A debugger is a very powerful tool for helping diagnose problems with programs. And debuggers are available for all practical programming languages. Therefore, being able to use a debugger is considered a basic skill of any professional or enthusiast programmer. And using a debugger yourself is considered basic work you should do yourself before asking others for help. As this site is for professional and enthusiast programmers, and not a help desk or mentoring site, if you have a question about a problem with a specific program, but have not used a debugger, your question is very likely to be closed and downvoted. If you persist with questions like that, you will eventually be blocked from posting more.
How a debugger can help you
By using a debugger you can discover whether a variable has the wrong value, and where in your program its value changed to the wrong value.
Using single stepping you can also discover whether the control flow is as you expect. For example, whether an if branch executed when you expect it ought to be.
General notes on using a debugger
The specifics of using a debugger depend on the debugger and, to a lesser degree, the programming language you are using.
You can attach a debugger to a process already running your program. You might do it if your program is stuck.
In practice it is often easier to run your program under the control of a debugger from the very start.
You indicate where your program should stop executing by indicating the source code file and line number of the line at which execution should stop, or by indicating the name of the method/function at which the program should stop (if you want to stop as soon as execution enters the method). The technical means that the debugger uses to cause your program to stop is called a breakpoint and this process is called setting a breakpoint.
Most modern debuggers are part of an IDE and provide you with a convenient GUI for examining the source code and variables of your program, with a point-and-click interface for setting breakpoints, running your program, and single stepping it.
Using a debugger can be very difficult unless your program executable or bytecode files include debugging symbol information and cross-references to your source code. You might have to compile (or recompile) your program slightly differently to ensure that information is present. If the compiler performs extensive optimizations, those cross-references can become confusing. You might therefore have to recompile your program with optimizations turned off.
I want to add that a debugger isn't always the perfect solution, and shouldn't always be the go-to solution to debugging. Here are a few cases where a debugger might not work for you:
The part of your program which fails is really large (poor modularization, perhaps?) and you're not exactly sure where to start stepping through the code. Stepping through all of it might be too time-consuming.
Your program uses a lot of callbacks and other non-linear flow control methods, which makes the debugger confused when you step through it.
Your program is multi-threaded. Or even worse, your problem is caused by a race condition.
The code that has the bug in it runs many times before it bugs out. This can be particularly problematic in main loops, or worse yet, in physics engines, where the problem could be numerical. Even setting a breakpoint, in this case, would simply have you hitting it many times, with the bug not appearing.
Your program must run in real-time. This is a big issue for programs that connect to the network. If you set up a breakpoint in your network code, the other end isn't going to wait for you to step through, it's simply going to time out. Programs that rely on the system clock, e.g. games with frameskip, aren't much better off either.
Your program performs some form of destructive actions, like writing to files or sending e-mails, and you'd like to limit the number of times you need to run through it.
You can tell that your bug is caused by incorrect values arriving at function X, but you don't know where these values come from. Having to run through the program, again and again, setting breakpoints farther and farther back, can be a huge hassle. Especially if function X is called from many places throughout the program.
In all of these cases, either having your program stop abruptly could cause the end results to differ, or stepping through manually in search of the one line where the bug is caused is too much of a hassle. This can equally happen whether your bug is incorrect behavior, or a crash. For instance, if memory corruption causes a crash, by the time the crash happens, it's too far from where the memory corruption first occurred, and no useful information is left.
So, what are the alternatives?
Simplest is simply logging and assertions. Add logs to your program at various points, and compare what you get with what you're expecting. For instance, see if the function where you think there's a bug is even called in the first place. See if the variables at the start of a method are what you think they are. Unlike breakpoints, it's okay for there to be many log lines in which nothing special happens. You can simply search through the log afterward. Once you hit a log line that's different from what you're expecting, add more in the same area. Narrow it down farther and farther, until it's small enough to be able to log every line in the bugged area.
Assertions can be used to trap incorrect values as they occur, rather than once they have an effect visible to the end-user. The quicker you catch an incorrect value, the closer you are to the line that produced it.
Refactor and unit test. If your program is too big, it might be worthwhile to test it one class or one function at a time. Give it inputs, and look at the outputs, and see which are not as you're expecting. Being able to narrow down a bug from an entire program to a single function can make a huge difference in debugging time.
In case of memory leaks or memory stomping, use appropriate tools that are able to analyze and detect these at runtime. Being able to detect where the actual corruption occurs is the first step. After this, you can use logs to work your way back to where incorrect values were introduced.
Remember that debugging is a process going backward. You have the end result - a bug - and find the cause, which preceded it. It's about working your way backward and, unfortunately, debuggers only step forwards. This is where good logging and postmortem analysis can give you much better results.
How big can a SQL Server 2005 SSIS package definition become before design-time or run-time performance is impacted? I'm not talking about the size of the datasets being passed, or even the number of columns being returned. I'm just talking about the number of sequences, tasks, data flow tasks, and variables being used in the package. I have a package that I'm less than halfway through with implementing, and I've got a total of 20 sequences (some nested), 16 data flow tasks, and 28 non-data flow tasks (mostly Execute SQL and Script tasks). The .dtsx file itself is 4MB so far.
By the time I'm done, I could see the packge easily double or even triple its current size. I haven't seen any performance issues yet, but I want to know if I'm going to encounter any. Has anyone else run into design-time or run-time performance issues with large package definitions? Is there a best practice out there for package size limitations?
It does sound like it's time for you to break that package down into separate packages, and use the Execute Package Task to execute them. That's much too large.
Two issues arise from large packages. The first as #Andrew mentioned is in the maintenance of a large package regardless of performance issues. Especially if you are working in a team environment, if you have the one large package checked out, you will have to be careful of merging changes etc. The second problem, which I have seen in SQL 2005 has to do with the fact that the runtime for SSIS in BIDS is a 32bit process. With packages as large as you have mentioned, It is very likely that you will soon run into out of memory issues while trying to execute that package in your dev environment. Most people recommend breaking the packages up in to much smaller units to simplify team development and unit testing.
Here is a specific recommendation from a knowledge base article
http://support.microsoft.com/kb/952110/en-us
that mentions 7mb as a .dtsx size that can start to cause problems.
As mentioned above, the root cause is that the runtime for SSIS/BIDS (DevEnv.exe) is a 32 Bit process and many subsystems in that exe create their own private heaps that don't release memory (xml, oledb, etc.) See this response to a similar question:
http://social.msdn.microsoft.com/forums/en-US/sqlintegrationservices/thread/7ead0bee-6f04-4778-83b7-0fd666833113/
I'm not sure what is too big, but to me the inherit problem with these type of tools is you end up with a mess of graphical pictures with embedded dialogs and properties making a nightmare in a hurry. Nothing beats raw code if you ask me. What you see is what you get. However do what one would do with raw code, make small digestible pieces and piece them together in the most logical way possible so that you can wrap your mind around them. Much easier to do this with code than SSIS, but you can still try for that type of design.
So in summary if the package has gotten so large and complex you can't wrap your mind around it, it's too big.
I'm working on a board game algorithm where a large tree is traversed using recursion, however, it's not behaving as expected. How do I handle this and what are you experiences with these situations?
To make things worse, it's using alpha-beta pruning which means entire parts of the tree are never visited, as well that it simply stops recursion when certain conditions are met. I can't change the search-depth to a lower number either, because while it's deterministic, the outcome does vary by how deep is searched and it may behave as expected at a lower search-depth (and it does).
Now, I'm not gonna ask you "where is the problem in my code?" but I am looking for general tips, tools, visualizations, anything to debug code like this. Personally, I'm developing in C#, but any and all tools are welcome. Although I think that this may be most applicable to imperative languages.
Logging. Log in your code extensively. In my experience, logging is THE solution for these types of problems. when it's hard to figure out what your code is doing, logging it extensively is a very good solution, as it lets you output from within your code what the internal state is; it's really not a perfect solution, but as far as I've seen, it works better than using any other method.
One thing I have done in the past is to format your logs to reflect the recursion depth. So you may do a new indention for every recurse, or another of some other delimiter. Then make a debug dll that logs everything you need to know about a each iteration. Between the two, you should be able to read the execution path and hopefully tell whats wrong.
I would normally unit-test such algorithms with one or more predefined datasets that have well-defined outcomes. I would typically make several such tests in increasing order of complexity.
If you insist on debugging, it is sometimes useful to doctor the code with statements that check for a given value, so you can attach a breakpoint at that time and place in the code:
if ( depth = X && item.id = 32) {
// Breakpoint here
}
Maybe you could convert the recursion into an iteration with an explicit stack for the parameters. Testing is easier in this way because you can directly log values, access the stack and don't have to pass data/variables in each self-evaluation or prevent them from falling out of scope.
I once had a similar problem when I was developing an AI algorithm to play a Tetris game. After trying many things a loosing a LOT of hours in reading my own logs and debugging and stepping in and out of functions what worked out for me was to code a fast visualizer and test my code with FIXED input.
So, if time is not a problem and you really want to understand what is going on, get a fixed board state and SEE what your program is doing with the data using a mix of debug logs/output and some sort of your own tools that shows information on each step.
Once you find a board state that gives you this problem, try to pin-point the function(s) where it starts and then you will be in a position to fix it.
I know what a pain this can be. At my job, we are currently working with a 3rd party application that basically behaves as a black box, so we have to devise some interesting debugging techniques to help us work around issues.
When I was taking a compiler theory course in college, we used a software library to visualize our trees; this might help you as well, as it could help you see what the tree looks like. In fact, you could build yourself a WinForms/WPF application to dump the contents of your tree into a TreeView control--it's messy, but it'll get the job done.
You might want to consider some kind of debug output, too. I know you mentioned that your tree is large, but perhaps debug statements or breaks at key point during execution that you're having trouble visualizing would lend you a hand.
Bear in mind, too, that intelligent debugging using Visual Studio can work wonders. It's tough to see how state is changing across multiple breaks, but Visual Studio 2010 should actually help with this.
Unfortunately, it's not particularly easy to help you debug without further information. Have you identified the first depth at which it starts to break? Does it continue to break with higher search depths? You might want to evaluate your working cases and try to determine how it's different.
Since you say that the traversal is not working as expected, I assume you have some idea of where things may go wrong. Then inspect the code to verify that you have not overlooked something basic.
After that I suggest you set up some simple unit tests. If they pass, then keep adding tests until they fail. If they fail, then reduce the tests until they either pass or are as simple as they can be. That should help you pinpoint the problems.
If you want to debug as well, I suggest you employ conditional breakpoints. Visual Studio lets you modify breakpoints, so you can set conditions on when the breakpoint should be triggered. That can reduce the number of iterations you need to look at.
I would start by instrumenting the function(s). At each recursive call log the data structures and any other info that will be useful in helping you identify the problem.
Print out the dump along with the source code then get away from the computer and have a nice paper-based debugging session over a cup of coffee.
Start from the base case where you've mentioned if else statements and then try to channelize your thinking by writing it down on pen and paper + printing the values on console when the first few instances of recursive functions are generated with values.
The motto is to find the correct trend between the values you print and match them with those values you wrote on paper in the initial few steps of your recursive algorithm.
What's your standard way of debugging a problem? This might seem like a pretty broad question with some of you replying 'It depends on the problem' but I think a lot of us debug by instinct and haven't actually tried wording our process. That's why we say 'it depends'.
I was sort of forced to word my process recently because a few developers and I were working an the same problem and we were debugging it in totally different ways. I wanted them to understand what I was trying to do and vice versa.
After some reflection I realized that my way of debugging is actually quite monotonous. I'll first try to be able to reliably replicate the problem (especially on my local machine). Then through a series of elimination (and this is where I think it's problem dependent) try to identify the problem.
The other guys were trying to do it in a totally different way.
So, just wondering what has been working for you guys out there? And what would you say your process is for debugging if you had to formalize it in words?
BTW, we still haven't found out our problem =)
My approach varies based on my familiarity with the system at hand. Typically I do something like:
Replicate the failure, if at all possible.
Examine the fail state to determine the immediate cause of the failure.
If I'm familiar with the system, I may have a good guess about to root cause. If not, I start to mechanically trace the data back through the software while challenging basic assumptions made by the software.
If the problem seems to have a consistent trigger, I may manually walk forward through the code with a debugger while challenging implicit assumptions that the code makes.
Tracing the root cause is, of course, where things can get hairy. This is where having a dump (or better, a live, broken process) can be truly invaluable.
I think that the key point in my debugging process is challenging pre-conceptions and assumptions. The number of times I've found a bug in that component that I or a colleague would swear is working fine is massive.
I've been told by my more intuitive friends and colleagues that I'm quite pedantic when they watch me debug or ask me to help them figure something out. :)
Consider getting hold of the book "Debugging" by David J Agans. The subtitle is "The 9 Indispensable Rules for Finding Even the Most Elusive Software and Hardware Problems". His list of debugging rules — available in a poster form at the web site (and there's a link for the book, too) is:
Understand the system
Make it fail
Quit thinking and look
Divide and conquer
Change one thing at a time
Keep an audit trail
Check the plug
Get a fresh view
If you didn't fix it, it ain't fixed
The last point is particularly relevant in the software industry.
I picked those on the web or some book which I can't recall (it may have been CodingHorror ...)
Debugging 101:
Reproduce
Progressively Narrow Scope
Avoid Debuggers
Change Only One Thing At a Time
Psychological Methods:
Rubber-duck debugging
Don't Speculate
Don't be too Quick to Blame the Tools
Understand Both Problem and Solution
Take a Break
Consider Multiple Causes
Bug Prevention Methods:
Monitor Your Own Fault Injection Habits
Introduce Debugging Aids Early
Loose Coupling and Information Hiding
Write a Regression Test to Prevent Re occurrence
Technical Methods:
Inert Trace Statements
Consult the Log Files of Third Party Products
Search the web for the Stack Trace
Introduce Design By Contract
Wipe the Slate Clean
Intermittent Bugs
Explot Localility
Introduce Dummy Implementations and Subclasses
Recompile / Relink
Probe Boundary Conditions and Special Cases
Check Version Dependencies (third party)
Check Code that Has Changed Recently
Don't Trust the Error Message
Graphics Bugs
When I'm up against a bug that I can't get seem to figure out, I like to make a model of the problem. Make a copy of the section of problem code, and start removing features from it, one at a time. Run a unit test against the code after every removal. Through this process your will either remove the feature with the bug (and hence, locate the bug), or you will have isolated the bug down to a core piece of code that contains the essence of the problem. And once you figure out the essence of the problem, its a lot easier to fix.
I normally start off by forming an hypothesis based on the information I have at hand. Once this is done, I work to prove it to be correct. If it proves to be wrong, I start off with a different hypothesis.
Most of the Multithreaded synchronization issues get solved very easily with this approach.
Also you need to have a good understanding of the debugger you are using and its features. I work on Windows applications and have found windbg to be extremely helpful in finding bugs.
Reducing the bug to its simplest form often leads to greater understanding of the issue as well adding the benefit of being able to involve others if necessary.
Setting up a quick reproduction scenario to allow for efficient use of your time to test any hypothosis you chose.
Creating tools to dump the environment quickly for comparisons.
Creating and reproducing the bug with logging turned onto the maximum level.
Examining the system logs for anything alarming.
Looking at file dates and timestamps to get a feeling if the problem could be a recent introduction.
Looking through the source repository for recent activity in the relevant modules.
Apply deductive reasoning and apply the Ockham's Razor principles.
Be willing to step back and take a break from the problem.
I'm also a big fan of using process of elimination. Ruling out variables tremendously simplifies the debugging task. It's often the very first thing that should to be done.
Another really effective technique is to roll back to your last working version if possible and try again. This can be extremely powerful because it gives you solid footing to proceed more carefully. A variation on this is to get the code to a point where it is working, with less functionality, than not working with more functionality.
Of course, it's very important to not just try things. This increases your despair because it never works. I'd rather make 50 runs to gather information about the bug rather take a wild swing and hope it works.
I find the best time to "debug" is while you're writing the code. In other words, be defensive. Check return values, liberally use assert, use some kind of reliable logging mechanism and log everything.
To more directly answer the question, the most efficient way for me to debug problems is to read code. Having a log helps you find the relevant code to read quickly. No logging? Spend the time putting it in. It may not seem like you're finding the bug, and you may not be. The logging might help you find another bug though, and eventually once you've gone through enough code, you'll find it....faster than setting up debuggers and trying to reproduce the problem, single stepping, etc.
While debugging I try to think of what the possible problems could be. I've come up with a fairly arbitrary classification system, but it works for me: all bugs fall into one of four categories. Keep in mind here that I'm talking about runtime problems, not compiler or linker errors. The four categories are:
dynamic memory allocation
stack overflow
uninitialized variable
logic bug
These categories have been most useful to me with C and C++, but I expect they apply pretty well elsewhere. The logic bug category is a big one (e.g. putting a < b when the correct thing was a <= b), and can include things like failing to synchronize access among threads.
Knowing what I'm looking for (one of these four things) helps a lot in finding it. Finding bugs always seems to be much harder than fixing them.
The actual mechanics for debugging are most often:
do I have an automated test that demonstrates the problem?
if not, add a test that fails
change the code so the test passes
make sure all the other tests still pass
check in the change
No automated testing in your environment? No time like the present to set it up. Too hard to organize things so you can test individual pieces of your program? Take the time to make it so. May make it take "too long" to fix this particular bug, but the sooner you start, the faster everything else'll go. Again, you might not fix the particular bug you're looking for but I bet you find and fix others along the way.
My method of debugging is different, probably because I am still beginner.
When I encounter logical bug I seem to end up adding more variables to see which values go where and then I go and debug line by line in the piece of code that causing a problem.
Replicating the problem and generating a repeatable test data set is definitely the first and most important step to debugging.
If I can identify a repeatable bug, I'll typically try and isolate the components involved until I locate the problem. Frequently I'll spend a little time ruling out cases so I can state definitively: The problem is not in component X (or process Y, etc.).
First I try to replicate the error, without being able to replicate the error it is basically impossible in a non-trivial program to guess the problem.
Then if possible, break out the code in a separate standalone project. There are several reasons for this: If the original project is big it quite difficult to debug second it eliminates or highlights any assumptions about the code.
I normally always have another copy of VS open which I use for the debugging parts in mini projects and to test routines which I later add to the main project.
Once having reproduced the error in the separate module the battle is almost won.
Sometimes it is not easy to break out a piece of code so in those cases I use different methods depending on how complex the issue is. In most cases assumptions about data seem to come and bite me so I try to add lots of asserts in the code in order make sure my assumptions are correct. I also disabling code by using #ifdef until the error disappears. Eliminating dependencies to other modules etc... sort of slowly circling in the bug like a vulture ..
I think I don't have really a conscious way of doing it, it varies quite a lot but the general principle is to eliminate the noise around the issue until it is quite obvious what it is. Hope I didn't sound too confusing :)