I've downloaded Apple's TextEdit example app (here) and I'm a bit puzzled by one thing I see there: the TextEdit.scatterload file. It contains a list of functions and methods. My guess is that it provides information to the linker as to which functions/methods will be needed, and in what order, when the app launches, and that this is used to order the binary generated by the linker for maximum efficiency. Oddly, I seem to be unable to find any information whatsoever about this file through Google. So. First of all, is my guess as to the function of this file correct? And second, if so, can I generate a .scatterload file for my own macOS app, to make it launch faster? How would I do that? Seems like a good idea! (I am using Objective-C, but perhaps this question is not specific to that, so I'm not going to tag for it here.)
Scatter loading refers to a way to organize the mapping of your code in memory by specifying which part of code must be near which one, etc. This is to optimize page faults, etc.
You can read about it here Improving locality of reference (HTML)
or here Improving locality of reference (PDF).
.scatterload file is used by the linker to position code in memory layout of the executable.
Except if your app really need tight performance tuning, I would not encourage you to have a look at this.
Is there a way to retrieve more detailed error information when OpenGL has flagged an error? I know there isn't in core OpenGL, but is there perhaps some common extension or platform- or driver-dependent way or anything at all?
My basic problem is that I have a game (written in Java with JOGL), and when people have trouble with it, which they do on certain hardware/software configurations, it can be quite hard to trace down where the root of the problem lies. For performance reasons, I can't keep calling glGetError for each command but only do so at a few points in the program, so it's kind of hard to even find what command even flagged the error to begin with. Even if I could, however, the extremely general error codes that OpenGL have don't really tell me all that much about what happened (seeing as how the manpages on the commands even describe how the various error codes are reused for sometimes quite many different actual error conditions).
It would be tremendously helpful if there were a way to find out what OpenGL command actually flagged the error, and also more details about the error that was flagged (like, if I get GL_INVALID_VALUE, what value to what argument was invalid and why?).
It seems a bit strange that drivers wouldn't provide this information, even if in a completely custom way, but looked as I have, I sure haven't found any way to find it. If it really is that they don't, is there any good reason for why that is so?
Actually, there is a feature in core OpenGL that will give you detailed debug information. But you are going to have to set your minimum version requirement pretty high to have this as a core feature.
Nevertheless, see this article -- even though it only went core in OpenGL 4.3, it existed in extension form for quite some time and it does not require any special hardware feature. So for the most part all you really need is a recent driver from NV or AMD.
I have an example of how to use this extension in an answer I wrote a while back, complete with a few utility functions to make the output easier to read. It is written in C, so I do not know how helpful it will be, but you might find something useful.
Here is the sort of output you can expect from this extension (AMD Catalyst):
OpenGL Error:
=============
Object ID: 102
Severity: Medium
Type: Performance
Source: API
Message: glDrawElements uses element index type 'GL_UNSIGNED_BYTE' that is not
optimal for the current hardware configuration; consider using
'GL_UNSIGNED_SHORT' instead.
Not only will it give you error information, but it will even give you things like performance warnings for doing something silly like using 8-bit vertex indices (which desktop GPUs do not like).
To answer another one of your questions, if you set the debug output to synchronous and install a breakpoint in your debug callback you can easily make any debugger break on an OpenGL error. If you examine the callstack you should be able to quickly identify exactly what API call generated most errors.
Here are some suggestions.
According to the man pages, glGetError returns the value of the error flag and then resets it to GL_NO_ERROR. I would use this property to track down your bug - if nothing else you can switch up where you call it and do a binary search to find where the error occurs.
I doubt calling glGetError will give you a performance hit. All it does is read back an error flag.
If you don't have the ability to test this on the specific hardware/software configurations those people have, it may be tricky. OpenGL drivers are implemented for specific devices, after all.
glGetError is good for basically saying that the previous line screwed up. That should give you a good starting point - you can look up in the man pages why that function will throw the error, rather than trying to figure it out based on its enum name.
There are other specific error functions to call, such as glGetProgramiv, and glGetFramebufferStatus, that you may want to check, as glGetError doesn't check for every type of error. IE Just because it reads clean doesn't mean another error didn't happen.
I'm afraid that asking this question may result in some downvotes, but after making some not satisfying research I decided to take a risk and ask more experienced people...
There are many questions here referring to some specific problems connected with the XCode Analayzer Tool. It seems to be very helpful solution. But I would like to ask you - as a beginner in iOS world - what kind of memory management stuff cannot be noticed by this tool.
In other words, are there any common memory management aspects, about which the iOS beginners should think "Oh, be careful with that, because in this case XCode Analyzer may not warn you about your mistake"...
For instance, I've found here Why cannot XCode static analyzer detect un-released retained properties? that:
(...)the analyzer can't reliably detect retain/release issues across
method/library boundaries(...)
It sounds like a good hint to consider, but maybe you know about some other common issues...
The analyzer is very good at finding the routine leaks that plague new programmers writing non-ARC code (failures to call release, returning objects of the wrong retain count, etc.).
In my experience, there are a couple of types of memory issues it does not find:
It cannot generally identify strong reference cycles (a.k.a. retain cycles). For example, you add a repeating NSTimer to a view controller, unaware that the timer maintains a strong reference to the view controller, and if you don't invalidate the timer (or do it in the wrong place, such as the dealloc method), neither the view controller nor the timer will get released.
It cannot find circular logic errors. For example, if you have some circular references where view controller A presents view controller B, which in turn presents a new copy of A (rather than dismissing/popping to get back to A).
It cannot find many non-reference counting memory issues. While it's getting better in dealing with Core Foundation functions, if you have code that is doing manual memory allocations (such as via malloc and free), the static analyzer may be of limited use. The same is true whenever you're using non-reference counting code (e.g. you use SQLite sqlite3_prepare_v2 and fail to call sqlite3_finalize).
I'm sure that's not a complete list of what it doesn't find, but those are the common issues I see asked about on Stack Overflow for which the static analyzer will be of limited help. But the analyzer is still a wonderful tool (it finds issues other than memory issues, too) and for those individuals not using ARC, it's invaluable.
Having said that, while the static analyzer is an under-appreciated first line of defense, you really should use Instruments to find leaks. See Locating Memory Issues in Your App in the Instruments User Guide. That's the best way to identify leaks.
I want to know if there are method to quickly find bugs in the program.
It seems that the more you master the architecture of your software, the more quickly
you can locate the bugs.
How the programmers improve their ability to find a bug?
Logging, and unit tests. The more information you have about what happened, the easier it is to reproduce it. The more modular you can make your code, the easier it is to check that it really is misbehaving where you think it is, and then check that your fix solves the problem.
Divide and conquer. Whenever you are debugging, you should be thinking about cutting down the possible locations of the problem. Every time you run the app, you should be trying to eliminate a possible source and zero in on the actual location. This can be done with logging, with a debugger, assertions, etc.
Here's a prophylactic method after you have found a bug: I find it really helpful to take a minute and think about the bug.
What was the bug exactly in essence.
Why did it occur.
Could you have found it earlier, easier.
Anything else you learned from the bug.
I find taking a minute to think about these things will make it far less likely that you will produce the same bug in the future.
I will assume you mean logic bugs. The best way I have found to capture logic bugs is to implement some sort of testing scheme. Check out jUnit as the standard. Pretty much you define a set of accepted outputs of your methods. Every time you compile your system it checks all of your test cases. If you have introduced new logic that breaks your tests, you will know about it instantly and know exactly what you have to fix.
Test driven design is a pretty big movement in programming right now. You will be hard pressed to find a language that doesn't support some kind of testing. Even JavaScript has a multitude of test suites.
Experience makes you a better debugger. Pay close attention to the bugs that you AND others commonly make. Try to figure out if/how these bugs apply to ALL code that affects you, not the single instance of where the bug was seen.
Raymond Chen is famous for his powers of psychic debugging.
Most of what looks like psychic
debugging is really just knowing what
people tend to get wrong.
That means that you don't necessarily have to be intimately familiar with the architecture / system. You just need enough knowledge to understand the types of bugs that apply and are easy to make.
I personally take the approach of thinking about where the bug may be in the code before actually opening up the code and taking a look. When you first start with this approach, it may not actually work very well, especially if you are pretty unfamiliar with the code base. However, over time someone will be able to tell you the behavior they are experiencing and you'll have a good idea where the problem is located or you may even know what to fix in the code to remedy the problem before even looking at the code.
I was on a project for several years that maintained by a vendor. They were not very good debuggers and most of the time it was up to us to point them to an area of the code that had the problem. What made our problem worse was that we didn't have a nice way to view the source code, so a lot of our "debugging" was just feeling.
Error checking and reporting. The #1 newbie coder debugging mistake is to turn off error reporting, avoid checking for whether what's going on makes sense, etc etc. In general, people feel like if they can't see anything going wrong then nothing is going wrong. Which of course could not be further from the case.
Instead, your code should be chock full of error conditions that will make lots of noise, with detailed reporting, someplace you will see it. (This doesn't mean inside a production web page.) Then, instead of having to trace an error all over the place because it got passed through sixteen layers of execution before it finally got someplace that broke, your errors start happening proximately to the actual issue.
It seems that the more you master the
architecture of your software ,the
more quickly you can locate the bugs.
After understanding the architecture, one's ability to find bugs in the application increases with their ability to identify and write extensive tests.
Know your tools.
Make sure that you know how to use conditional breakpoints and watches in your debugger.
Use static analysis tools as well - they can point out the more obvious issues.
Sleep and rest.
Use programming methods that produce fewer bugs in the first place.
If to implement a single stand-alone functional requirement it takes N separate point-edits to source code, the number of bugs put into the code is roughly proportional to N, so find programming methods that minimize N. Ways to do this: DRY (don't repeat yourself), code generation, and DSL (domain-specific-language).
Where bugs are likely, have unit tests.
Obviously.IMHO, the best unit tests are monte-carlo.
Make intermediate results visible.
For example, compilers have intermediate representations, in the form of 4-tuples. If there is a bug, the intermediate code can be examined. That tells if the bug is in the first or second half of the compiler.
P.S. Most programmers are not aware that they have a choice of how much data structure to use. The less data structure you use, the less are the chances for bugs (and performance issues) caused by it.
I find tracepoints to be an invaluable debugging tool. They are a bit like logging, except you create them during a debugging session to solve a particular issue, like breakpoints.
Printing the stacktrace in a tracepoint can be especially useful. For example, you can print the hash code and stacktrace in the constructor of an object, and then later on when the object is used again you can search for its hashcode to see which client code created it. Same for seeing who disposed it or called a certain method etc.
They are also great for debugging issues related to window focus changes etc, where the debugger would interfere if you drop in break mode.
Static code tools like FindBugs
Assertions, assertions, and assertions.
Some areas of our code has 4 or 5 assertions for each line of real code. When we get a bug report the first thing that happens is that the customer data is processed in our debug build 99 times out a hundred an assert will fire near the cause of the bug.
Additionally our debug build perform redundant calculations to ensure that an optimized algorithm is returning the correct result, and also debug functions are used to examine the sanity of data structures.
The hardest thing new developers have to contend with is getting their code to survive the assertions of the code gthey are calling.
Additionally we do not allow any code to be putback to toplevel that causes any integration or unit test to fail.
Stepping through the code, examining flow/state where unexpected behavior is occurring. (Then develop a test for it, of course).
Writing Debug.Write(message) in your code and using DebugView is another option. And then run your application find out what is going on.
"Architecture" in software means something like:
Several components
The components interact across clearly-defined interfaces
Each component has a well-defined responsibility
The responsibility of one component is unlike the responsibilities of other components
So, as you said, the better the architecture the easier it is to find bugs.
First: knowing the bug, you can decide which functionality is broken, and therefore know which component implements that functionality. For example, if the bug is that something isn't being logged properly, therefore this bug should be in one of 3 places:
In the component that's responsible for logging (your logging library)
Or, above that in the application code which is using this library
Or, below that in the system code which this library is using
Second: examine the data transfered across the interfaces between components. To continue the previous example above:
Set a debugger breakpoint on the application code which invokes the logger API, to verify whether the logger API is being used correctly (e.g. whether it's being invoked at all, whether parameters are as-expected, etc.).
Doing this tells you whether the bug is in the component above this interface, or in the component that's below this interface.
Repeat (perhaps using binary search if the call stack is very deep) until you've found which component is at fault.
When you come to the point that you think there must be a bug in the OS, check your assertions -- and put them into the code with "assert" statements.
Conversely, as you are writing the code, think of the range of valid inputs for your algorithms and put in assertions to make sure you have what you think you have. Same goes for output: Check that you produced what you think you produced.
E.g. if you expect a non-empty list:
l = getList(input)
assert l, "List was empty for input: %s" % str(input)
I'm part of the QA team # work, and knowing anything about the product and how it is developed, helps a lot in finding bugs, also when I make new QA tools I pass it to our dev team to test it, finding bugs in your own code is just plain hard!
Some people say programmers are tainted, so we cannot see bugs in their own product; we are not talking about code here, we are beyond that, usability and functionality itself.
Meanwhile unit testing seams to be a nice solution to find bugs in your own code, its totally pointless if you're wrong even before writing the unit test, how are you going to find the bugs then? you don't!, let your co-worker find them, hire a QA guy.
Scientific debugging is what I always used, and it greatly helps.
Basically, if you can replicate a bug, you can track its origin. You should then experiment some tests, observe the results, and infer hypotheses on why the bug happens.
Writing about all your hypotheses, attempts, expected results and observed results can help you track down the bugs, particularly if they're nasty.
There are automated tools that can help you with that process, particularly git-bisect (and similar bisection tools on other revision systems) to quickly find which change introduced the bug, unit testing to reproduce a bug and prevent regressions in your code (can be used in combination with bisect), and delta debugging to find the culprit in your code (similar to git-bisect but whereas git-bisect works on the code history, delta debugging works on the code directly).
But whatever the tools you are using, the most important benefit is in the scientific methodology, as this is the formalization of what most experienced debuggers do.
I've been testing out the performance and memory profiler AQTime to see if it's worthwhile spending those big $$$ for it for my Delphi application.
What amazes me is how it can give you source line level performance tracing (which includes the number of times each line was executed and the amount of time that line took) without modifying the application's source code and without adding an inordinate amount of time to the debug run.
The way that they do this so efficiently makes me think there might be some techniques/technologies used here that I don't know about that would be useful to know about.
Do you know what kind of methods they use to capture the execution line-by-line without code changes?
Are there other profiling tools that also do non-invasive line-by-line checking and if so, do they use the same techniques?
I've made an open source profiler for Delphi which does the same:
http://code.google.com/p/asmprofiler/
It's not perfect, but it's free :-). Is also uses the Detour technique.
It stores every call (you must manual set which functions you want to profile),
so it can make an exact call history tree, including a time chart (!).
This is just speculation, but perhaps AQtime is based on a technology that is similar to Microsoft Detours?
Detours is a library for instrumenting
arbitrary Win32 functions on x86, x64,
and IA64 machines. Detours intercepts
Win32 functions by re-writing the
in-memory code for target functions.
I don't know about Delphi in particular, but a C application debugger can do line-by-line profiling relatively easily - it can load the code and associate every code path with a block of code. Then it can break on all the conditional jump instructions and just watch and see what code path is taken. Debuggers like gdb can operate relatively efficiently because they work through the kernel and don't modify the code, they just get informed when each line is executed. If something causes the block to be exited early (longjmp), the debugger can hook that and figure out how far it got into the blocks when it happened and increment only those lines.
Of course, it would still be tough to code, but when I say easily I mean that you could do it without wasting time breaking on each and every instruction to update a counter.
The long-since-defunct TurboPower also had a great profiling/analysis tool for Delphi called Sleuth QA Suite. I found it a lot simpler than AQTime, but also far easier to get meaningful result. Might be worth trying to track down - eBay, maybe?