Effect of logging on Apache's performence - performance

I am developing an Apache module. During development I found it convenient to use logging functions at various points in my code.
For example after opening a file, I would log an error if the operation was not successful so that I may know exactly where the problem occurred in my code.
Now, I am about to deliver my module to my boss (I am on an internship). I wanted to what are the best practices regarding logging. Is it good for maintenance purposes or is it bad because it may hamper the response time of the server.

It really depends on how you wrote those logging instructions. If you wrote:
logger.debug(computeSomeCostlyDebugOutput());
You might affect performance badly if the logger is not set on a DEBUG level (computeSomeCostlyDebugOutput will always take time to execute and its result will then be ignored by the logger if not matching the DEBUG level).
If you write it like this instead:
if (logger.isDebugEnabled()) {
logger.debug(computeSomeCostlyDebugOutput());
}
then the costly operations and logging will occur only if the correct logger level is set (i.e. the logger won't ignore it). It basically acts like another switch for the logger, the first switch being the configured logger level.
As Andrzej Doyle very well pointed out, the logger will check its level internally, but this happens in the debug method, after time was already wasted in the computeSomeCostlyDebugOutput. If you waste time in computeSomeCostlyDebugOutput, you better do it when you know that its result won't be in vain.
A lot of software ships with logging instructions which you can activate if you need more details into the inner workings of the thing, execution path and stuff. Just make sure they can be deactivated and only take computing time if the appropriate level is set.

One of the design goals of Log4J (for good reason) was performance; Ceki Gulku wanted the library to be usable in production, enterprise software and the overhead of Log4J itself is actually pretty minimal (measured on my own webapp project with a profiler).
Two things that are liable to take some time though, are:
Forming the arguments to pass into the logging method, for some calls. As dpb says, this should be avoided by wrapping any computation of complex output in a logging check so you're not deriving complex debug output when the logger's going to throw it away as it's set to only record errors.
The sheer I/O required to record the log data. If you've got your application logging 200Mb of debug logs per second (it might sound infeasible, but it's happened to me before) then that's likely to put a strain on how fast it runs, as IIRC the file writing happens synchronously. In various webapp-type projects I've developed, I can usually actually notice a slight difference in responsiveness when I set the logs to debug level (and IMO this is a good thing, as you should be generating a lot of output when you ask for debug logs).

Related

The effect of println statements in production?

I was reviewing the Grails application code and i found println statements in a lot of places. These were used for debugging. I am wondering whether leaving these statements affect the production app performance?
Yes, it affects in production environment, because println statements are synchronous. Without processing your println statements execution will not move forward, if you are printing huge size objects like Map, List, file content etc, this will take more execution time and increase the log file size as well, so this will definitely affect your production performance.
The better way is if you want to maintain the logs use Log4J like asynchronous library for auditing your important logs in the application.
Log4j reference

How do you reproduce bugs that occur sporadically?

We have a bug in our application that does not occur every time and therefore we don't know its "logic". I don't even get it reproduced in 100 times today.
Disclaimer: This bug exists and I've seen it. It's not a pebkac or something similar.
What are common hints to reproduce this kind of bug?
Analyze the problem in a pair and pair-read the code. Make notes of the problems you KNOW to be true and try to assert which logical preconditions must hold true for this happen. Follow the evidence like a CSI.
Most people instinctively say "add more logging", and this may be a solution. But for a lot of problems this just makes things worse, since logging can change timing-dependencies sufficiently to make the problem more or less frequent. Changing the frequency from 1 in 1000 to 1 in 1,000,000 will not bring you closer to the true source of the problem.
So if your logical reasoning does not solve the problem, it'll probably give you a few specifics you could investigate with logging or assertions in your code.
There is no general good answer to the question, but here is what I have found:
It takes a talent for this kind of thing. Not all developers are best suited for it, even if they are superstars in other areas. So know your team, who has a talent for it, and hope you can give them enough candy to get them excited about helping you out, even if it isn't their area.
Work backwards, and treat it like a scientific investigation. Start with the bug, what you see is wrong. Develop hypotheses about what could cause it (this is the creative/imaginative part, the art that not everyone has the talent for) - and it helps a lot to know how the code works. For each of those hypotheses (preferably sorted by what you think is most likely - again pure gut feel here), develop a test that tries to eliminate it as the cause, and test the hypothesis. Any given failure to meet a prediction doesn't mean the hypothesis is wrong. Test the hypothesis until it is confirmed to be wrong (although as it gets less likely you may want to move on to another hypothesis first, just don't discount this one until you have a definitive failure).
Gather as much data as you can during this process. Extensive logging and whatever else is applicable. Do not discount a hypothesis because you lack the data, rather remedy the lack of data. Quite often the inspiration for the right hypothesis comes from examining the data. Noticing something off in a stack trace, weird issue in a log, something missing that should be there in a database, etc.
Double check every assumption. So many times I have seen an issue not get fixed quickly because some general method call was not further investigated, so the problem was just assumed to be not applicable. "Oh that, that should be simple." (See point 1).
If you run out of hypotheses, that is generally caused by insufficient knowledge of the system (this is true even if you wrote every line of code yourself), and you need to run through and review code and gain additional insight into the system to come up with a new idea.
Of course, none of the above guarantees anything, but that is the approach that I have found gets results consistently.
Add some sort of logging or tracing. For example log the last X actions the user committed before causing the bug (only if you can set a condition to match bug).
It's quite common for programmers not to be able to reiterate a user-experienced crash simply because you have developed a certain workflow and habits in using the application that obviously goes around the bug.
At this frequency of 1/100, I'd say that the first thing to do is to handle exceptions and log anything anywhere or you could be spending another week hunting this bug.
Also make a priority list of potentially sensitive articulations and features in your project. For example :
1 - Multithreading
2 - Wild pointers/ loose arrays
3 - Reliance on input devices
etc.
This will help you segment areas that you can brute-force-until-break-again as suggested by other posters.
Since this is language-agnostic, I'll mention a few axioms of debugging.
Nothing a computer ever does is random. A 'random occurrence' indicates a as-yet-undiscovered pattern. Debugging begins with isolating the pattern. Vary individual elements and assess what makes a change in the behaviour of the bug.
Different user, same computer?
Same user, different computer?
Is the occurrence strongly periodic? Does rebooting change the periodicity?
FYI- I once saw a bug that was experienced by a single person. I literally mean person, not a user account. User A would never see the problem on their system, User B would sit down at that workstation, signed on as User A and could immediately reproduce the bug. There should be no conceivable way for the app to know the difference between the physical body in the chair. However-
The users used the app in different ways. User A habitually used a hotkey to to invoke a action and User B used an on-screen control. The difference in the user behaviour would cascade into a visible error a few actions later.
ANY difference that effects the behaviour of the bug should be investigated, even if it makes no sense.
There's a good chance your application is MTWIDNTBMT (Multi Threaded When It Doesn't Need To Be Multi Threaded), or maybe just multi-threaded (to be polite). A good way to reproduce sporadic errors in multi-threaded applications is to sprinkle code like this around (C#):
Random rnd = new Random();
System.Threading.Thread.Sleep(rnd.Next(2000));
and/or this:
for (int i = 0; i < 4000000000; i++)
{
// tight loop
}
to simulate threads completing their tasks at different times than usual or tying up the processor for long stretches.
I've inherited many buggy, multi-threaded apps over the years, and code like the above examples usually makes the sporadic errors occur much more frequently.
Add verbose logging. It will take multiple -- sometimes dozen(s) -- iterations to add enough logging to understand the scenario.
Now the problem is that if the problem is a race condition, which is likely if it doesn't reproduce reliably, so logging can change timing and the problem will stop happening. In this case do not log to a file, but keep a rotating buffer of the log in memory and only dump it on disk when you detect that the problem has occurred.
Edit: a little more thoughts: if this is a gui application run tests with a qa automation tool which allows you to replay macros. If this is a service-type app, try to come up with at least a guess as to what is happening and then programmatically create 'freak' usage patterns which would exercise the code that you suspect. Create higher than usual loads etc.
What development environment?
For C++, your best bet may be VMWare Workstation record/replay, see:
http://stackframe.blogspot.com/2007/04/workstation-60-and-death-of.html
Other suggestions include inspecting the stack trace, and careful code overview... there is really no silver bullet :)
Try to add code in your app to trace the bug automatically once it happens (or even alert you via mail / SMS)
log whatever you can so when it happens you can catch the right system state.
Another thing- try applying automated testing that can cover more territory than human based testing in a formed manner.. it's a long shot, but a good practice in general.
all the above, plus throw some brute force soft-robot at it that is semi random, and scater a lot of assert/verify (c/c++, probably similar in other langs) through the code
Tons of logging and careful code review are your only options.
These can be especially painful if the app is deployed and you can't adjust the logging. At that point, your only choice is going through the code with a fine-tooth comb and trying to reason about how the program could enter into the bad state (scientific method to the rescue!)
Often these kind of bugs are related to corrupted memory and for that reason they might not appear very often. You should try to run your software with some kind of memory profiler e.g., valgrind, to see if something goes wrong.
Let’s say I’m starting with a production application.
I typically add debug logging around the areas where I think the bug is occurring. I setup the logging statements to give me insight into the state of the application. Then I have the debug log level turned on and ask the user/operator(s) notify me of the time of the next bug occurrence. I then analyze the log to see what hints it gives about the state of the application and if that leads to a better understanding of what could be going wrong.
I repeat step 1 until I have a good idea of where I can start debugging the code in the debugger
Sometimes the number of iterations of the code running is key but other times it maybe the interaction of a component with an outside system (database, specific user machine, operating system, etc.). Take some time to setup a debug environment that matches the production environment as closely as possible. VM technology is a good tool for solving this problem.
Next I proceed via the debugger. This could include creating a test harness of some sort that puts the code/components in the state I’ve observed from the logs. Knowing how to setup conditional break points can save a lot of time, so get familiar with that and other features within your debugger.
Debug, debug , debug. If you’re going nowhere after a few hours, take a break and work on something unrelated for awhile. Come back with a fresh mind and perspective.
If you have gotten nowhere by now, go back to step 1 and make another iteration.
For really difficult problems you may have to resort to installing a debugger on the system where the bug is occurring. That combined with your test harness from step 4 can usually crack the really baffling issues.
Unit Tests. Testing a bug in the app is often horrendous because there is so much noise, so many variable factors. In general the bigger the (hay)stack, the harder it is to pinpoint the issue. Creatively extending your unit test framework to embrace edge cases can save hours or even days of sifting
Having said that there is no silver bullet. I feel your pain.
Add pre and post condition check in methods related to this bug.
You may have a look at Design by contract
Along with a lot of patience, a quiet prayer & cursing you would need:
a good mechanism for logging the user actions
a good mechanism for gathering the data state when the user performs some actions (state in application, database etc.)
Check the server environment (e.g. an anti-virus software running at a particular time etc.) & record the times of the error & see if you can find any trends
some more prayers & cursing...
HTH.
Assuming you're on Windows, and your "bug" is a crash or some sort of corruption in unmanaged code (C/C++), then take a look at Application Verifier from Microsoft. The tool has a number of stops that can be enabled to verify things during runtime. If you have an idea of the scenario where your bug occurs, then try to run through the scenario (or a stress version of the scenario) with AppVerifer running. Make sure to either turn on pageheap in AppVerifier, or consider compiling your code with the /RTCcsu switch (see http://msdn.microsoft.com/en-us/library/8wtf2dfz.aspx for more information).
"Heisenbugs" require great skills to diagnose, and if you want help from people here you have to describe this in much more detail, and patiently listen to various tests and checks, report result here, and iterate this till you solve it (or decide it is too expensive in terms of resources).
You will probably have to tell us your actual situation, language, DB, operative system, workload estimate, time of the day it happened in the past, and a myriad of other things, list tests you did already, how they went, and be ready to do more and share the results.
And this will not guarantee that we collectively can find it, either...
I'd suggest to write down all things that user has been doing. If you have lets say 10 such bug reports You can try to find something that connects them.
Read the stack trace carefully and try to guess what could be happened;
then try to trace\log every line of code that potentially can cause trouble.
Keep your focus on disposing resources; many sneaky sporadical bugs i found were related to close\dispose things :).
For .NET projects You can use Elmah (Error Logging Modules and Handlers) to monitor you application for un-caught exceptions, it's very simple to install and provides a very nice interface to browse unknown errors
http://code.google.com/p/elmah/
This saved me just today in catching a very random error that was occuring during a registration process
Other than that I can only recommend trying to get as much information from your users as possible and having a thorough understanding of the project workflow
They mostly come out at night....
mostly
The team that I work with has enlisted the users in recording their time they spend in our app with CamStudio when we've got a pesky bug to track down. It's easy to install and for them to use, and makes reproducing those nagging bugs much easier, since you can watch what the users are doing. It also has no relationship to the language you're working in, since it's just recording the windows desktop.
However, this route seems to be viable only if you're developing corporate apps and have good relationships with your users.
This varies (as you say), but some of the things that are handy with this can be
immediately going into the debugger when the problem occurs and dumping all the threads (or the equivalent, such as dumping the core immediately or whatever.)
running with logging turned on but otherwise entirely in release/production mode. (This is possible in some random environments like c and rails but not many others.)
do stuff to make the edge conditions on the machine worse... force low memory / high load / more threads / serving more requests
Making sure that you're actually listening to what the users encountering the problem are actually saying. Making sure that they're actually explaining the relevant details. This seems to be the one that breaks people in the field a lot. Trying to reproduce the wrong problem is boring.
Get used to reading assembly that was produced by optimizing compilers. This seems to stop people sometimes, and it isn't applicable to all languages/platforms, but it can help
Be prepared to accept that it is your (the developer's) fault. Don't get into the trap of insisting the code is perfect.
sometimes you need to actually track the problem down on the machine it is happening on.
#p.marino - not enough rep to comment =/
tl;dr - build failures due to time of day
You mentioned time of day and that caught my eye. Had a bug once were someone stayed later at work on night, tried to build and commit before they left and kept getting a failure. They eventually gave up and went home. When they caught in the next morning it built fine, they committed (probably should have been more suspiscious =] ) and the build worked for everyone. A week or two later someone stayed late and had an unexpected build failure. Turns out there was a bug in the code that made any build after 7PM break >.>
We also found a bug in one seldom used corner of the project this january that caused problems marshalling between different schemas because we were not accounting for the different calendars being 0 AND 1 month based. So if no one had messed with that part of the project we wouldn't have possibly found the bug until jan. 2011
These were easier to fix than threading issues, but still interesting I think.
hire some testers!
This has worked for really weird heisenbugs.
(I'd also recommend getting a copy of "Debugging" by Dave Argans, these ideas are partly derived form using his ideas!)
(0) Check the ram of the system using something like Memtest86!
The whole system exhibits the problem, so make a test jig that exercises the whole thing.
Say it's a server side thing with a GUI, you run the whole thing with a GUI test framework doing the necessary input to provoke the problem.
It doesn't fail 100% of the time, so you have to make it fail more often.
Start by cutting the system in half ( binary chop)
worse case, you have to remove sub-systems one at a time.
stub them out if they can't be commented out.
See if it still fails. Does it fail more often ?
Keep proper test records, and only change one variable at a time!
Worst case you use the jig and you test for weeks to get meaningful statistics. This is HARD; but remember, the jig is doing the work.
I've got No threads and only one process, and I don't talk to hardware
If the system has no threads, no communicating processes and contacts no hardware; it's tricky; heisenbugs are generally synchronization, but in the no-thread no processes case it's more likely to be uninitialized data, or data used after being released, either on the heap or the stack. Try to use a checker like valgrind.
For threaded/multi-process problems:
Try running it on a different number of CPU's. If it's running on 1, try on 4! Try forcing a 4-computer system onto 1.
It'll mostly ensure things happen one at a time.
If there are threads or communicating processes this can shake out bugs.
If this is not helping but you suspect it's synchronization or threading, try changing the OS time-slice size.
Make it as fine as your OS vendor allows!
Sometimes this has made race conditions happen almost every time!
Obversely, try going slower on the timeslices.
Then you set the test jig running with debugger(s) attached all over the place and wait for the test jig to stop on a fault.
If all else fails, put the hardware in the freezer and run it there. The timing of everything will be shifted.
Debugging is hard and time consuming especially if you are unable to deterministically reproduce the problem. My advice to you is to find out the steps to reproduce it deterministically (not just sometimes).
There has been a lot of research in the field of failure reproduction in the past years and is still very active. Record&Replay techniques have been (so far) the research direction of most researchers. This is what you need to do:
1) Analyze the source code and determine what are the sources of non-determinism in the application, that is, what are the aspects that may take your application through different execution paths (e.g. user input, OS signals)
2) Log them in the next time you execute the application
3) When your application fails again, you have the steps-to-reproduce the failure in your log.
If your log still does not reproduce the failure, then you are dealing with a concurrency bug. In that case, you should take a look at how your application accesses shared variables. Do not attempt to record the accesses to shared variables, because you would be logging too much data, thereby causing severe slowdowns and large logs. Unfortunately, there is not much I can say that would help you to reproduce concurrency bugs, because research still has a long way to go in this subject. The best I can do is to provide a reference to the most recent advance (so far) in the topic of deterministic replay of concurrency bugs:
http://www.gsd.inesc-id.pt/~nmachado/software/Symbiosis_Tutorial.html
Best regards
Use an enhanced crash reporter. In the Delphi environment, we have EurekaLog and MadExcept. Other tools exist in other environments. Or you can diagnose the core dump. You're looking for the stack trace, which will show you where it's blowing up, how it got there, what's in memory, etc.. It's also useful to have a screenshot of the app, if it's a user-interaction thing. And info about the machine that it crashed on (OS version and patch, what else is running at the time, etc..) Both of the tools that I mentioned can do this.
If it's something that happens with a few users but you can't reproduce it, and they can, go sit with them and watch. If it's not apparent, switch seats - you "drive", and they tell you what to do. You'll uncover the subtle usability issues that way. double-clicks on a single-click button, for example, initiating re-entrancy in the OnClick event. That sort of thing. If the users are remote, use WebEx, Wink, etc., to record them crashing it, so you can analyze the playback.

How to debug a program without a debugger? [closed]

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Interview question-
Often its pretty easier to debug a program once you have trouble with your code.You can put watches,breakpoints and etc.Life is much easier because of debugger.
But how to debug a program without a debugger?
One possible approach which I know is simply putting print statements in your code wherever you want to check for the problems.
Are there any other approaches other than this?
As its a general question, its not restricted to any specific language.So please share your thoughts on how you would have done it?
EDIT- While submitting your answer, please mention a useful resource (if you have any) about any concept. e.g. Logging
This will be lot helpful for those who don't know about it at all.(This includes me, in some cases :)
UPDATE: Michal Sznajderhas put a real "best" answer and also made it a community wiki.Really deserves lots of up votes.
Actually you have quite a lot of possibilities. Either with recompilation of source code or without.
With recompilation.
Additional logging. Either into program's logs or using system logging (eg. OutputDebugString or Events Log on Windows). Also use following steps:
Always include timestamp at least up to seconds resolution.
Consider adding thread-id in case of multithreaded apps.
Add some nice output of your structures
Do not print out enums with just %d. Use some ToString() or create some EnumToString() function (whatever suits your language)
... and beware: logging changes timings so in case of heavily multithreading you problems might disappear.
More details on this here.
Introduce more asserts
Unit tests
"Audio-visual" monitoring: if something happens do one of
use buzzer
play system sound
flash some LED by enabling hardware GPIO line (only in embedded scenarios)
Without recompilation
If your application uses network of any kind: Packet Sniffer or I will just choose for you: Wireshark
If you use database: monitor queries send to database and database itself.
Use virtual machines to test exactly the same OS/hardware setup as your system is running on.
Use some kind of system calls monitor. This includes
On Unix box strace or dtrace
On Windows tools from former Sysinternals tools like http://technet.microsoft.com/en-us/sysinternals/bb896645.aspx, ProcessExplorer and alike
In case of Windows GUI stuff: check out Spy++ or for WPF Snoop (although second I didn't use)
Consider using some profiling tools for your platform. It will give you overview on thing happening in your app.
[Real hardcore] Hardware monitoring: use oscilloscope (aka O-Scope) to monitor signals on hardware lines
Source code debugging: you sit down with your source code and just pretend with piece of paper and pencil that you are computer. Its so called code analysis or "on-my-eyes" debugging
Source control debugging. Compare diffs of your code from time when "it" works and now. Bug might be somewhere there.
And some general tips in the end:
Do not forget about Text to Columns and Pivot Table in Excel. Together with some text tools (awk, grep or perl) give you incredible analysis pack. If you have more than 32K records consider using Access as data source.
Basics of Data Warehousing might help. With simple cube you may analyse tons of temporal data in just few minutes.
Dumping your application is worth mentioning. Either as a result of crash or just on regular basis
Always generate you debug symbols (even for release builds).
Almost last but not least: most mayor platforms has some sort of command line debugger always built in (even Windows!). With some tricks like conditional debugging and break-print-continue you can get pretty good result with obscure bugs
And really last but not least: use your brain and question everything.
In general debugging is like science: you do not create it you discover it. Quite often its like looking for a murderer in a criminal case. So buy yourself a hat and never give up.
First of all, what does debugging actually do? Advanced debuggers give you machine hooks to suspend execution, examine variables and potentially modify state of a running program. Most programs don't need all that to debug them. There are many approaches:
Tracing: implement some kind of logging mechanism, or use an existing one such as dtrace(). It usually worth it to implement some kind of printf-like function that can output generally formatted output into a system log. Then just throw state from key points in your program to this log. Believe it or not, in complex programs, this can be more useful than raw debugging with a real debugger. Logs help you know how you got into trouble, while a debugger that traps on a crash assumes you can reverse engineer how you got there from whatever state you are already in. For applications that you use other complex libraries that you don't own that crash in the middle of them, logs are often far more useful. But it requires a certain amount of discipline in writing your log messages.
Program/Library self-awareness: To solve very specific crash events, I often have implemented wrappers on system libraries such as malloc/free/realloc which extensions that can do things like walk memory, detect double frees, attempts to free non-allocated pointers, check for obvious buffer over-runs etc. Often you can do this sort of thing for your important internal data types as well -- typically you can make self-integrity checks for things like linked lists (they can't loop, and they can't point into la-la land.) Even for things like OS synchronization objects, often you only need to know which thread, or what file and line number (capturable by __FILE__, __LINE__) the last user of the synch object was to help you work out a race condition.
If you are insane like me, you could, in fact, implement your own mini-debugger inside of your own program. This is really only an option in a self-reflective programming language, or in languages like C with certain OS-hooks. When compiling C/C++ in Windows/DOS you can implement a "crash-hook" callback which is executed when any program fault is triggered. When you compile your program you can build a .map file to figure out what the relative addresses of all your public functions (so you can work out the loader initial offset by subtracting the address of main() from the address given in your .map file). So when a crash happens (even pressing ^C during a run, for example, so you can find your infinite loops) you can take the stack pointer and scan it for offsets within return addresses. You can usually look at your registers, and implement a simple console to let you examine all this. And voila, you have half of a real debugger implemented. Keep this going and you can reproduce the VxWorks' console debugging mechanism.
Another approach, is logical deduction. This is related to #1. Basically any crash or anomalous behavior in a program occurs when it stops behaving as expected. You need to have some feed back method of knowing when the program is behaving normally then abnormally. Your goal then is to find the exact conditions upon which your program goes from behaving correctly to incorrectly. With printf()/logs, or other feedback (such as enabling a device in an embedded system -- the PC has a speaker, but some motherboards also have a digital display for BIOS stage reporting; embedded systems will often have a COM port that you can use) you can deduce at least binary states of good and bad behavior with respect to the run state of your program through the instrumentation of your program.
A related method is logical deduction with respect to code versions. Often a program was working perfectly at one state, but some later version is not longer working. If you use good source control, and you enforce a "top of tree must always be working" philosophy amongst your programming team, then you can use a binary search to find the exact version of the code at which the failure occurs. You can use diffs then to deduce what code change exposes the error. If the diff is too large, then you have the task of trying to redo that code change in smaller steps where you can apply binary searching more effectively.
Just a couple suggestions:
1) Asserts. This should help you work out general expectations at different states of the program. As well familiarize yourself with the code
2) Unit tests. I have used these at times to dig into new code and test out APIs
One word: Logging.
Your program should write descriptive debug lines which include a timestamp to a log file based on a configurable debug level. Reading the resultant log files gives you information on what happened during the execution of the program. There are logging packages in every common programming language that make this a snap:
Java: log4j
.Net: NLog or log4net
Python: Python Logging
PHP: Pear Logging Framework
Ruby: Ruby Logger
C: log4c
I guess you just have to write fine-grain unit tests.
I also like to write a pretty-printer for my data structures.
I think the rest of the interview might go something like this...
Candidate: So you don't buy debuggers for your developers?
Interviewer: No, they have debuggers.
Candidate: So you are looking for programmers who, out of masochism or chest thumping hamartia, make things complicated on themselves even if they would be less productive?
Interviewer: No, I'm just trying to see if you know what you would do in a situation that will never happen.
Candidate: I suppose I'd add logging or print statements. Can I ask you a similar question?
Interviewer: Sure.
Candidate: How would you recruit a team of developers if you didn't have any appreciable interviewing skill to distinguish good prospects based on relevant information?
Peer review. You have been looking at the code for 8 hours and your brain is just showing you what you want to see in the code. A fresh pair of eyes can make all the difference.
Version control. Especially for large teams. If somebody changed something you rely on but did not tell you it is easy to find a specific change set that caused your trouble by rolling the changes back one by one.
On *nix systems, strace and/or dtrace can tell you an awful lot about the execution of your program and the libraries it uses.
Binary search in time is also a method: If you have your source code stored in a version-control repository, and you know that version 100 worked, but version 200 doesn't, try to see if version 150 works. If it does, the error must be between version 150 and 200, so find version 175 and see if it works... etc.
use println/log in code
use DB explorer to look at data in DB/files
write tests and put asserts in suspicious places
More generally, you can monitor side effects and output of the program, and trigger certain events in the program externally.
A Print statement isn't always appropriate. You might use other forms of output such as writing to the Event Log or a log file, writing to a TCP socket (I have a nice utility that can listen for that type of trace from my program), etc.
For programs that don't have a UI, you can trigger behavior you want to debug by using an external flag such as the existence of a file. You might have the program wait for the file to be created, then run through a behavior you're interested in while logging relevant events.
Another file's existence might trigger the program's internal state to be written to your logging mechanism.
like everyone else said:
Logging
Asserts
Extra Output
&
your favorite task manager or process
explorer
links here and here
Another thing I have not seen mentioned here that I have had to use quite a bit on embedded systems is serial terminals.
You can cannot a serial terminal to just about any type of device on the planet (I have even done it to embedded CPUs for hydraulics, generators, etc). Then you can write out to the serial port and see everything on the terminal.
You can get real fancy and even setup a thread that listens to the serial terminal and responds to commands. I have done this as well and implemented simple commands to dump a list, see internal variables, etc all from a simple 9600 baud RS-232 serial port!
Spy++ (and more recently Snoop for WPF) are tremendous for getting an insight into Windows UI bugs.
A nice read would be Delta Debugging from Andreas Zeller. It's like binary search for debugging

Problems with running an application under controlled environment (Win32)

I'm not exactly sure how to tag this question or how to write the title, so if anyone has a better idea, please edit it
Here's the deal:
Some time ago I had written a little but cruicial part of a computing olympiad management system. The system's job is to get submissions from participants (code files), compile them, run them against predefined test cases, and return results. Plus all the rest of the stuff you can imagine it should do.
The part I had written was called Limiter. It was a little program whose job was to take another program and run it in a controlled environment. Controlled in this case means limitations on available memory, computing time and access to system resources. Plus if the program crashes I should be able to determine the type of the exception and report that to the user. Also, when the process terminated, it should be noted how long it executed (with a resolution of at least 0.01 seconds, better more).
Of course, the ideal solution to this would be virtualization, but I'm not that experienced to write that.
My solution to this was split into three parts.
The simplest part was the access to system resources. The program would simply be executed with limited access tokens. I combined some of the basic (Everyone, Anonymous, etc.) access tokens that are available to all processes in order to provide practically a read-only access to the system, with the exception of the folder it was executing in.
The limitation of memory was done through job objects - they allow to specify maximum memory limit.
And lastly, to limit execution time and catch all the exceptions, my Limiter attaches to the process as a debugger. Thus I can monitor the time it has spent and terminate it if it takes too long. Note, that I cannot use Job objects for this, because they only report Kernel Time and User Time for the job. A process might do something like Sleep(99999999) which would count in none of them, but still would disable the testing machine. Thus, although I don't count a processes idle time in its final execution time, it still has to have a limit.
Now, I'm no expert in low-level stuff like this. I spent a few days reading MSDN and playing around, and came up with a solution as best I could. Unfortunately it seems it's not running as well as it could be expected. For most part it seems to work fine, but weird cases keep creeping up. Just now I have a little C++ program which runs in a split second on its own, but my Limiter reports 8 seconds of User mode time (taken from job counters). Here's the code. It prints the output in about half a second and then spends more than 7 seconds just waiting:
#include <iostream>
#include <vector>
using namespace std;
int main()
{
vector< vector<int> > dp(50000, vector<int>(4, -1));
cout << dp.size();
}
The code of the limiter is pretty lengthy, so I'm not including it here. I also feel that there might be something wrong with my approach - perhaps I shouldn't do the debugger stuff. Perhaps there are some common pitfalls that I don't know of.
I would like some advice on how other people would tackle this problem. Perhaps there is already something that does this, and my Limiter is obsolete?
Added: The problem seems to be in the little program that I posted above. I've opened a new question for it, since it is somewhat unrelated. I'd still like comments on this approach for limiting a program.
Running with a debugger attached can change the characteristics of the application. Performance can be impacted, and code paths can even change (if the target process does things based on the presence of a debugger, i.e. IsDebuggerPresent).
A different approach that we've used is to configure our own application to run as the JIT debugger. By setting the AeDebug registry key, you can control what debugger is invoked when an application crashes. This way you only jump in when the target process crashes, and it doesn't impact the process during normal run-time.
This site has some details about setting the postmortem debugger: Configuring Automatic Debugging.
Your approaches for limiting the memory, getting timing etc. all sound perfectly fine.

What logging implementation do you prefer?

I'm about to implement a logging class in C++ and am trying to decide how to do it. I'm curious to know what kind of different logging implementations there are out there.
For example, I've used logging with "levels" in Python. Where you filter out log events that are lower than a certain threshold. It also includes logging "names" where you can filter out events via a hierarchy, for example "app.apples.*" will not be displayed but "app.bananas.*" will be.
I've had thoughts about using "tags", but unsure of the implementation. I've seen games use "bits" for compactness.
So my questions:
What implementations have you created or used before?
What do you think the advantages and disadvantages of them are?
I'd read this post by Jeff Atwood
It's about the overflow of Logging and how to avoid it.
There are lots of links on the Log4J wikipedia page.
One of our applications uses Registry entries to dynamically control logging/tracing during production execution.
For example:
if (Logger.TraceOptionIsEnabled(TraceOption.PLCF_ShowConfig)) {...whatever
Whe executed at run-time, if registry value PLCF_ShowConfig is true, the call returns true, and whatever is executed.
Quite handy.
Jeff Atwood had a pretty interesting blog entry about logging. The ultimate message of it was that logging is generally unnecessary (to some extents).
Logging generally doesn't scale well (too much data on high traffic systems).
I think the best point of it is that you generally don't need it. It's easier to trace through your code by hand to understand what values are being assigned to things than it is to sift through lots of log files.
It's just information overload.
Now the same can't be said for single user applications. For things like media encoding or general OS usage, it can be nice to have a log for small apps because debug info is useful (to me) in this situation. If you're burning a DVD and something goes wrong, looking at log info can be very helpful to troubleshoot with if you understand the log output.
I think having a few levels would help for the user, such as:
No logs
Basic logging for general user feedback
Highly technical data for a developer or tech-support person to interpret
Depending on the situation, it may be useful to store ALL log data and only display to the user the basic info, or perhaps giving the option to see all detailed data.
It all depends on the domain.

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