Strange behavior with printStackTrace() - exception

printStackTrace() acts as if it runs in its own thread after waiting for input. Here's my code:
try {
new Scanner(System.in).nextLine();
throw new Exception();
} catch (Exception e) {
e.printStackTrace();
}
System.out.print("STUFF");
I sometimes get the expected output (with STUFF at the end), but sometimes I get this:
blabla // the scanner input
java.lang.ExceptionSTUFF
at Test.main(Test.java:7)
and sometimes this:
blabla
java.lang.Exception
STUFF at Test.main(Test.java:7)
Replacing the scanner with System.in.read() yields the same results. Removing the line entirely yields the expected result. In the actual program where I noticed this problem, the stack trace was much longer, and the STUFF output always appeared either as expected or as in the second output above - at the beginning of the second line.
What's causing this, and how can I solve it?

printStackTrace, as per the documentation, prints to the standard error stream:
public void printStackTrace() – Prints this throwable and its backtrace to the standard error stream.
...which is System.err. Then you are writing to System.out. Those two are different streams and therefore get flushed to the actual output at different times. Leaving the code as it is, it is equivalent to the problem outlined in this question.
To fix the issue, you could either manually flush your output streams or print your exception to System.out instead of System.err. You could use the variant of printStackTrace that accepts a PrintStream with standard output as a parameter: e.printStackTrace(System.out);

This is actually not a strange behaviour at all; Java is designed to work this way. For most part it's a feature we all love to have which makes our code run more efficiently than we actually wrote it. And what 'it' refers to is that the JVM is designed to re-arrange and optimize our code into better byte-code than we mere mortal developers can bother with even trying to achieve.
You could look at it a little bit like this; Java is kind of a framework we're using through out code that will do what we want it to, in the most efficient way possible (that it's been programmed with at least). The Java API is the API to the Java framework we're using.
And to tie this back to your code; you're initializing two streams, two buffered streams, one is System.out, one is the printStackTrace(). When you execute your code, Java will re-arrange your code and thread it to run as optimal as Java can make it. This means that which ever stream completes first will get to print to console.
Java has no value in what gets printed when, that's a value we humans have; we have a preference in reading things in special orders. That's why Java is a challenge for us developers to write thread-safe code that doesn't care when it gets executed; given the same input it should always return the same output.
Since your System.out stream is faster to print than the stack-trace stream it will probably always print ahead of the stacktrace since they are buffered streams. Buffered streams require time to buffer, something that's both threading and differently time-consuming. Why shouldn't Java give you the stream that's done first and free up that thread and CPU?
Solution:
You should try to counter this by designing your code in a manner where it doesn't matter which gets printed when.

This is the nature of printing things to the console. Everything, standard out, standard error, etc is spooled up to be printed out to the console, but because java is inherently multi-threaded, there's no guarantee for what order these items get added to the queue for printing.
Multi-threading can do funky things!

Related

When is it right time to throw an exception in functional programming

Say I have a web application with UserController. Client sends a HTTP POST request that is about to be handled by the controller. That however first must parse the provided json to UserDTO. For this reason there exist a UserDTOConverter with a method toDTO(json): User.
Given I value functional programming practices for its benefits of referential transparency and pure function the question is. What is the best approach to deal with a possibly inparsable json? First option would be to throw an exception and have it handled in global error handler. Invalid json means that something went terrible wrong (eg hacker) and this error is unrecoverable, hence the exception is on point (even assuming FP). The second option would be to return Maybe<User> instead of User. Then in the controller we can based on the return type return HTTP success response or failure response. Ultimately both approaches results in the same failure/success response, which one is preferable though?
Another example. Say I have a web application that needs to retrieve some data from remote repository UserRepository. From a UserController the repository is called getUser(userId): User. Again, what is the best way to handle the error of possible non existent user under provided id? Instead of returning User I can again return Maybe<User>. Then in controller this result can be handled by eg returning "204 No Content". Or I could throw an exception. The code stays referentially transparent as again I am letting the exception to bubble all the way up to global error handler (no try catch blocks).
Whereas in the first example I would lean more towards throwing an exception in the latter one I would prefer returning a Maybe. Exceptions result in cleaner code as the codebase is not cluttered with ubiquitous Eithers, Maybes, empty collections, etc. However, returning these kinds of data structure ensure explicitness of the calls, and imo results in better discoverability of the error.
Is there a place for exceptions in functional programming? What is the biggest pitfall of using exceptions over returning Maybes or Eithers? Does it make sense to be throwing exceptions in FP based app? If so is there a rule of thumb for that?
TL;DR
If there are Maybes/Eithers all over the codebase, you generally have a problem with I/O being mixed promiscuously with business logic. This doesn't get any better if you replace them with exceptions (or vice versa).
Mark Seemann has already given a good answer, but I'd like to address one specific bit:
Exceptions result in cleaner code as the codebase is not cluttered with ubiquitous Eithers, Maybes, empty collections, etc.
This isn't necessarily true. Either part.
Problem with Exceptions
The problem with exceptions is that they circumvent the normal control flow, which can make the code difficult to reason about. This seems so obvious as to barely be worthy of mention, until you end up with an error thrown 20 calls deep in a call stack where it isn't clear what triggered the error in the first place: even though the stack trace might point you to the exact line in the code you might have a very hard time figuring out the application state that caused the error to happen. The fact that you can be undisciplined about state transitions in an imperative/procedural program is of course the whole thing that FP is trying to fix.
Maybe, Maybe not: It might be Either one
You shouldn't have ubiquitous Maybes/Eithers all over the codebase, and for the same reason that you shouldn't be throwing exceptions willy-nilly all over the codebase: it complicates the code too much. You should have files that are entry points to the system, and those I/O-concerned files will be full of Maybes/Eithers, but they should then delegate to normal functions that either get lifted or dispatched to through some other mechanism depending on language (you don't specify the language). At the very least languages with option types almost always support first-class functions, you can always use a callback.
It's kind of like testability as a proxy for code quality: if your code is hard to test it probably has structural problems. If your codebase is full of Maybes/Eithers in every file it probably has structural problems.
You're asking about a couple of different scenarios, and I'll try to address each one.
Input
The first question pertains to converting a UserDTO (or, in general, any input) into a stronger representation (User). Such a conversion is usually self-contained (has no external dependencies) so can be implemented as a pure function. The best way to view such a function is as a parser.
Usually, parsers will return Either values (AKA Result), such as Either<Error, User>. The Either monad is, however, short-circuiting, meaning that if there's more than one problem with the input, only the first problem will be reported as an error.
When validating input, you often want to collect and return a list of all problems, so that the client can fix all problems and try again. A monad can't do that, but an applicative functor can. In general, I believe that validation is a solved problem.
Thus, you'll need to model validation as a type that isomomorphic to Either, but has different applicative functor behaviour, and no monad interface. The above links already show some examples, but here's a realistic C# example: An applicative reservation validation example in C#.
Data access
Data access is different, because you'd expect the data to already be valid. Reading from a data store can, however, 'go wrong' for two different reasons:
The data is not there
The data store is unreachable
The first issue (querying for missing data) can happen for various reasons, and it's usually appropriate to plan for that. Thus, a database query for a user should return Maybe<User>, indicating to the client that it should be ready to handle both cases: the user is there, or the user is not there.
The other issue is that the data store may sometimes be unreachable. This can be caused by a network partition, or if the database server is experiencing problems. In such cases, there's usually not much client code can do about it, so I usually don't bother explicitly modelling those scenarios. In other words, I'd let the implementation throw an exception, and the client code would typically not catch it (other than to log it).
In short, only throw exceptions that are unlikely to be handled. Use sum types for expected errors.
I have seen code like below, where exceptions are wrapped in a generic error. What i don't like about this approach is that we need to write a handler to deal with this UnexpectedError, inspect it, extract the exception and log it. Not sure if this is the correct way to do it.
override suspend fun update(
reservation: Reservation,
history: ReservationHistory
): Either<ReservationError, Reservation> {
return Either.catch {
mongoClient.startSession().use { clientSession ->
clientSession.startTransaction()
mongoClient.getDatabase(database)
.getCollection<ReservationDocument>()
.updateOneById(reservation.reservationId.value, MapToReservationDocument.invoke(reservation))
mongoClient.getDatabase(database)
.getCollection<ReservationHistoryDocument>()
.insertOne(MapToReservationHistoryDocument.invoke(history))
reservation
}
}.mapLeft {
UnexpectedError(it)
}
}

n-layer using try catch

I'm working on an n-tier application, and doing try/catch only in my presentation layer. If an error occurs in the data layer or business layer, this error is captured by the try/catch in my presentation layer. Is this good, or should I work with try catch in every method of each layer?
In general, it is better to catch an exception as close to where it happens to allow for your code to potentially do something to fix/adapt/react to the issue. What this "do something" is depends upon the circumstance. For instance if you have a service layer call that fails, you may want to retry the call, because the service may have been too busy; whereas if your stored procedure is broken, then it does not matter how many times you retry, it will be broken until the logic is corrected in the database.
If all you want to do is log errors, then catching an error as close to where it happens is less useful.
Every project I have ever worked on had try-catch blocks in every layer of the application.
A corollary to try-catch is the concept of Fail Fast, which generally says that debugging productivity increases when a system immediately fails instead of failing slowly (read: after hours, days, weeks, months or even years of operation).
A good example of failing fast in the .NET Framework is the usage of Convert.ToInt32() versus a straight up cast using (int), like this:
int? settingValue = Convert.ToInt32(SomeSettingString);
if(settingValue == null)
{
// Do something here
}
else
{
// Do something else here
}
If SomeSettingString can be converted to an int, then the value is set to and Do something else logic is executed. Suppose a year from now, the setting changes and null is returned, because the conversion fails, now all of a sudden the Do something here logic executes and it is a debugging adventure to figure out that this condition happens, if you can find out at all. Most issues like this seem to only happen in PRODUCTION and not DEV.
Now let's look at the same thing, but by failing fast, like this:
try
{
int settingValue = (int)SomeSettingString;
}
catch(Exception ex)
{
// Fail fast and throw exception
throw new Exception("Fail fast");
}
Now the exception happens immediately when the setting string causes a conversion to int failure.
Note: Beware that failing fast can be sabotaged by empty catch blocks that "eat" exceptions. try blocks with empty catch blocks should be avoided, because they invariably lead to the "eaten" exception scenario.
Don't do this:
try
{
// Exception waiting to happen here
}
catch(Exception ex)
{
// Catch-all, because all exceptions derive from Exception class
// So this will eat exceptions and pretend like they never happened
}
Here's what you want to avoid at any level: a bunch of methods that all look like this:
void method()
{
try
{
// some code here that may potentially throw an exception
}
catch ( /* anything here */)
{
// code right here to handle that exception
}
}
If that's what you're doing, you may just as well go back to VB's old On Error Goto system, because you haven't gained anything. Exceptions provide two major advantages for error handling: the ability to easily handle different types of errors in different ways, and the ability for errors to be caught further up in the program's call stack. It's the second advantage that you're asking about here.
So we see that you do want to allow exceptions to "bubble up" to higher layers, as it's a big part of why we have exceptions at all... but do you always want to handle them at the presentation layer? No, we can do better. Sometimes, there may be business rules about how to respond to certain exceptions from the data layer. Sometimes, the data layer itself may be able to handle and recover from an exception without alerting the layer above it.
On the other hand, an advantage of exceptions is that it can leave you to write simpler code in the lowers layers, with fewer breaks from the normal flow of program execution for error handling code. That comes at the price of instead placing more of try/catch in the presentation tier. Again, this doesn't mean that the presentation tier is the only place to handle them, but this is the place to make the effort to ensure they don't get past your presentation layer un-caught. If you can't handle them anywhere else, do have a way to catch them in the presentation layer and show them to the user in a friendly way. It's also a good idea to use the the same mechanism to log or report your exceptions, so you can get good metrics on where you applications fails, and then use that information to make your application better.
When you do get to the point that you're inside an last-ditch exception handler, you may also want to consider terminating the application. If you really have unexpected things going on, such that unhandled exceptions make it through the presentation tier, there's a valid school of thought that suggests it may not be a good idea to continue running the program. But even in this case, you'll want to catch and try to report the exception, and then crash as gracefully as possible.

Why should I not wrap every block in "try"-"catch"?

I have always been of the belief that if a method can throw an exception then it is reckless not to protect this call with a meaningful try block.
I just posted 'You should ALWAYS wrap calls that can throw in try, catch blocks.' to this question and was told that it was 'remarkably bad advice' - I'd like to understand why.
A method should only catch an exception when it can handle it in some sensible way.
Otherwise, pass it on up, in the hope that a method higher up the call stack can make sense of it.
As others have noted, it is good practice to have an unhandled exception handler (with logging) at the highest level of the call stack to ensure that any fatal errors are logged.
As Mitch and others stated, you shouldn't catch an exception that you do not plan on handling in some way. You should consider how the application is going to systematically handle exceptions when you are designing it. This usually leads to having layers of error handling based on the abstractions - for example, you handle all SQL-related errors in your data access code so that the part of the application that is interacting with domain objects is not exposed to the fact that there is a DB under the hood somewhere.
There are a few related code smells that you definitely want to avoid in addition to the "catch everything everywhere" smell.
"catch, log, rethrow": if you want scoped based logging, then write a class that emits a log statement in its destructor when the stack is unrolling due to an exception (ala std::uncaught_exception()). All that you need to do is declare a logging instance in the scope that you are interested in and, voila, you have logging and no unnecessary try/catch logic.
"catch, throw translated": this usually points to an abstraction problem. Unless you are implementing a federated solution where you are translating several specific exceptions into one more generic one, you probably have an unnecessary layer of abstraction... and don't say that "I might need it tomorrow".
"catch, cleanup, rethrow": this is one of my pet-peeves. If you see a lot of this, then you should apply Resource Acquisition is Initialization techniques and place the cleanup portion in the destructor of a janitor object instance.
I consider code that is littered with try/catch blocks to be a good target for code review and refactoring. It indicates that either exception handling is not well understood or the code has become an amœba and is in serious need of refactoring.
Because the next question is "I've caught an exception, what do I do next?" What will you do? If you do nothing - that's error hiding and the program could "just not work" without any chance to find what happened. You need to understand what exactly you will do once you've caught the exception and only catch if you know.
You don't need to cover every block with try-catches because a try-catch can still catch unhandled exceptions thrown in functions further down the call stack. So rather than have every function have a try-catch, you can have one at the top level logic of your application. For example, there might be a SaveDocument() top-level routine, which calls many methods which call other methods etc. These sub-methods don't need their own try-catches, because if they throw, it's still caught by SaveDocument()'s catch.
This is nice for three reasons: it's handy because you have one single place to report an error: the SaveDocument() catch block(s). There's no need to repeat this throughout all the sub-methods, and it's what you want anyway: one single place to give the user a useful diagnostic about something that went wrong.
Two, the save is cancelled whenever an exception is thrown. With every sub-method try-catching, if an exception is thrown, you get in to that method's catch block, execution leaves the function, and it carries on through SaveDocument(). If something's already gone wrong you likely want to stop right there.
Three, all your sub-methods can assume every call succeeds. If a call failed, execution will jump to the catch block and the subsequent code is never executed. This can make your code much cleaner. For example, here's with error codes:
int ret = SaveFirstSection();
if (ret == FAILED)
{
/* some diagnostic */
return;
}
ret = SaveSecondSection();
if (ret == FAILED)
{
/* some diagnostic */
return;
}
ret = SaveThirdSection();
if (ret == FAILED)
{
/* some diagnostic */
return;
}
Here's how that might be written with exceptions:
// these throw if failed, caught in SaveDocument's catch
SaveFirstSection();
SaveSecondSection();
SaveThirdSection();
Now it's much clearer what is happening.
Note exception safe code can be trickier to write in other ways: you don't want to leak any memory if an exception is thrown. Make sure you know about RAII, STL containers, smart pointers, and other objects which free their resources in destructors, since objects are always destructed before exceptions.
Herb Sutter wrote about this problem here. For sure worth reading.
A teaser:
"Writing exception-safe code is fundamentally about writing 'try' and 'catch' in the correct places." Discuss.
Put bluntly, that statement reflects a fundamental misunderstanding of exception safety. Exceptions are just another form of error reporting, and we certainly know that writing error-safe code is not just about where to check return codes and handle error conditions.
Actually, it turns out that exception safety is rarely about writing 'try' and 'catch' -- and the more rarely the better. Also, never forget that exception safety affects a piece of code's design; it is never just an afterthought that can be retrofitted with a few extra catch statements as if for seasoning.
As stated in other answers, you should only catch an exception if you can do some sort of sensible error handling for it.
For example, in the question that spawned your question, the questioner asks whether it is safe to ignore exceptions for a lexical_cast from an integer to a string. Such a cast should never fail. If it did fail, something has gone terribly wrong in the program. What could you possibly do to recover in that situation? It's probably best to just let the program die, as it is in a state that can't be trusted. So not handling the exception may be the safest thing to do.
If you always handle exceptions immediately in the caller of a method that can throw an exception, then exceptions become useless, and you'd better use error codes.
The whole point of exceptions is that they need not be handled in every method in the call chain.
The best advice I've heard is that you should only ever catch exceptions at points where you can sensibly do something about the exceptional condition, and that "catch, log and release" is not a good strategy (if occasionally unavoidable in libraries).
I was given the "opportunity" to salvage several projects and executives replaced the entire dev team because the app had too many errors and the users were tired of the problems and run-around. These code bases all had centralized error handling at the app level like the top voted answer describes. If that answer is the best practice why didn't it work and allow the previous dev team to resolve issues? Perhaps sometimes it doesn't work? The answers above don't mention how long devs spend fixing single issues. If time to resolve issues is the key metric, instrumenting code with try..catch blocks is a better practice.
How did my team fix the problems without significantly changing the UI? Simple, every method was instrumented with try..catch blocked and everything was logged at the point of failure with the method name, method parameters values concatenated into a string passed in along with the error message, the error message, app name, date, and version. With this information developers can run analytics on the errors to identify the exception that occurs the most! Or the namespace with the highest number of errors. It can also validate that an error that occurs in a module is properly handled and not caused by multiple reasons.
Another pro benefit of this is developers can set one break-point in the error logging method and with one break-point and a single click of the "step out" debug button, they are in the method that failed with full access to the actual objects at the point of failure, conveniently available in the immediate window. It makes it very easy to debug and allows dragging execution back to the start of the method to duplicate the problem to find the exact line. Does centralized exception handling allow a developer to replicate an exception in 30 seconds? No.
The statement "A method should only catch an exception when it can handle it in some sensible way." This implies that developers can predict or will encounter every error that can happen prior to release. If this were true a top level, app exception handler wouldn't be needed and there would be no market for Elastic Search and logstash.
This approach also lets devs find and fix intermittent issues in production! Would you like to debug without a debugger in production? Or would you rather take calls and get emails from upset users? This allows you to fix issues before anyone else knows and without having to email, IM, or Slack with support as everything needed to fix the issue is right there. 95% of issues never need to be reproduced.
To work properly it needs to be combined with centralized logging that can capture the namespace/module, class name, method, inputs, and error message and store in a database so it can be aggregated to highlight which method fails the most so it can be fixed first.
Sometimes developers choose to throw exceptions up the stack from a catch block but this approach is 100 times slower than normal code that doesn't throw. Catch and release with logging is preferred.
This technique was used to quickly stabilize an app that failed every hour for most users in a Fortune 500 company developed by 12 Devs over 2 years. Using this 3000 different exceptions were identified, fixed, tested, and deployed in 4 months. This averages out to a fix every 15 minutes on average for 4 months.
I agree that it is not fun to type in everything needed to instrument the code and I prefer to not look at the repetitive code, but adding 4 lines of code to each method is worth it in the long run.
I agree with the basic direction of your question to handle as many exceptions as possible at the lowest level.
Some of the existing answer go like "You don't need to handle the exception. Someone else will do it up the stack." To my experience that is a bad excuse to not think about exception handling at the currently developed piece of code, making the exception handling the problem of someone else or later.
That problem grows dramatically in distributed development, where you may need to call a method implemented by a co-worker. And then you have to inspect a nested chain of method calls to find out why he/she is throwing some exception at you, which could have been handled much easier at the deepest nested method.
The advice my computer science professor gave me once was: "Use Try and Catch blocks only when it's not possible to handle the error using standard means."
As an example, he told us that if a program ran into some serious issue in a place where it's not possible to do something like:
int f()
{
// Do stuff
if (condition == false)
return -1;
return 0;
}
int condition = f();
if (f != 0)
{
// handle error
}
Then you should be using try, catch blocks. While you can use exceptions to handle this, it's generally not recommended because exceptions are expensive performance wise.
If you want to test the outcome of every function, use return codes.
The purpose of Exceptions is so that you can test outcomes LESS often. The idea is to separate exceptional (unusual, rarer) conditions out of your more ordinary code. This keeps the ordinary code cleaner and simpler - but still able to handle those exceptional conditions.
In well-designed code deeper functions might throw and higher functions might catch. But the key is that many functions "in between" will be free from the burden of handling exceptional conditions at all. They only have to be "exception safe", which does not mean they must catch.
I would like to add to this discussion that, since C++11, it does make a lot of sense, as long as every catch block rethrows the exception up until the point it can/should be handled. This way a backtrace can be generated. I therefore believe the previous opinions are in part outdated.
Use std::nested_exception and std::throw_with_nested
It is described on StackOverflow here and here how to achieve this.
Since you can do this with any derived exception class, you can add a lot of information to such a backtrace!
You may also take a look at my MWE on GitHub, where a backtrace would look something like this:
Library API: Exception caught in function 'api_function'
Backtrace:
~/Git/mwe-cpp-exception/src/detail/Library.cpp:17 : library_function failed
~/Git/mwe-cpp-exception/src/detail/Library.cpp:13 : could not open file "nonexistent.txt"
I feel compelled to add another answer although Mike Wheat's answer sums up the main points pretty well. I think of it like this. When you have methods that do multiple things you are multiplying the complexity, not adding it.
In other words, a method that is wrapped in a try catch has two possible outcomes. You have the non-exception outcome and the exception outcome. When you're dealing with a lot of methods this exponentially blows up beyond comprehension.
Exponentially because if each method branches in two different ways then every time you call another method you're squaring the previous number of potential outcomes. By the time you've called five methods you are up to 256 possible outcomes at a minimum. Compare this to not doing a try/catch in every single method and you only have one path to follow.
That's basically how I look at it. You might be tempted to argue that any type of branching does the same thing but try/catches are a special case because the state of the application basically becomes undefined.
So in short, try/catches make the code a lot harder to comprehend.
Besides the above advice, personally I use some try+catch+throw; for the following reason:
At boundary of different coder, I use try + catch + throw in the code written by myself, before the exception being thrown to the caller which is written by others, this gives me a chance to know some error condition occured in my code, and this place is much closer to the code which initially throw the exception, the closer, the easier to find the reason.
At the boundary of modules, although different module may be written my same person.
Learning + Debug purpose, in this case I use catch(...) in C++ and catch(Exception ex) in C#, for C++, the standard library does not throw too many exception, so this case is rare in C++. But common place in C#, C# has a huge library and an mature exception hierarchy, the C# library code throw tons of exception, in theory I(and you) should know every exceptions from the function you called, and know the reason/case why these exception being thrown, and know how to handle them(pass by or catch and handle it in-place)gracefully. Unfortunately in reality it's very hard to know everything about the potential exceptions before I write one line of code. So I catch all and let my code speak aloud by logging(in product environment)/assert dialog(in development environment) when any exception really occurs. By this way I add exception handling code progressively. I know it conflit with good advice but in reality it works for me and I don't know any better way for this problem.
You have no need to cover up every part of your code inside try-catch. The main use of the try-catch block is to error handling and got bugs/exceptions in your program. Some usage of try-catch -
You can use this block where you want to handle an exception or simply you can say that the block of written code may throw an exception.
If you want to dispose your objects immediately after their use, You can use try-catch block.

Conventions for exceptions or error codes [closed]

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Yesterday I was having a heated debate with a coworker on what would be the preferred error reporting method. Mainly we were discussing the usage of exceptions or error codes for reporting errors between application layers or modules.
What rules do you use to decide if you throw exceptions or return error codes for error reporting?
In high-level stuff, exceptions; in low-level stuff, error codes.
The default behaviour of an exception is to unwind the stack and stop the program, if I'm writing a script an and I go for a key that's not in a dictionary it's probably an error, and I want the program to halt and let me know all about that.
If, however, I'm writing a piece of code which I must know the behaviour of in every possible situation, then I want error codes. Otherwise I have to know every exception that can be thrown by every line in my function to know what it will do (Read The Exception That Grounded an Airline to get an idea of how tricky this is). It's tedious and hard to write code that reacts appropriately to every situation (including the unhappy ones), but that's because writing error-free code is tedious and hard, not because you're passing error codes.
Both Raymond Chen and Joel have made some eloquent arguments against using exceptions for everything.
I normally prefer exceptions, because they have more contextual information and can convey (when properly used) the error to the programmer in a clearer fashion.
On the other hand, error codes are more lightweight than exceptions but are harder to maintain. Error checking can inadvertently be omitted. Error codes are harder to maintain because you have to keep a catalog with all error codes and then switch on the result to see what error was thrown. Error ranges can be of help here, because if the only thing we are interested in is if we are in the presence of an error or not, it is simpler to check (e.g., an HRESULT error code greater or equal to 0 is success and less than zero is failure). They can inadvertently be omitted because there is no programmatic forcing that the developer will check for error codes. On the other hand, you cannot ignore exceptions.
To summarize I prefer exceptions over error codes in almost all situations.
I prefer exceptions because
they interupt the flow of logic
they benefit from class hierarchy which gives more features/functionality
when used properly can represent a wide range of errors (e.g. an InvalidMethodCallException is also a LogicException, as both occur when there's a bug in your code that should be detectable before runtime), and
they can be used to enhance the error (i.e. a FileReadException class definition can then contain code to check whether the file exists, or is locked, etc)
Error codes can be ignored (and often are!) by the callers of your functions. Exceptions at least force them to deal with the error in some way. Even if their version of dealing with it is to have an empty catch handler (sigh).
Exceptions over error codes, no doubt about it. You get much of the same benefits from exceptions as you do with error codes, but also much more, without the shortcomings of error codes. The only knock on exceptions is that it is slightly more overhead; but in this day and age, that overhead should be considered negligible for nearly all applications.
Here are some articles discussing, comparing and contrasting the two techniques:
Object Oriented Exception Handling in Perl
Exceptions vs. status returns
There are some good links in those that can give you further reading.
I would never mix the two models...it's too hard to convert from one to the other as you move from one part of the stack which is using error codes, to a higher piece that is using exceptions.
Exceptions are for "anything that stops or inhibits the method or subroutine from doing what you asked it to do" ... NOT to pass messages back about irregularities or unusual circumstances, or the state of the system, etc. Use return values or ref (or out) parameters for that.
Exceptions allow methods to be written (and utilized) with semantics that are dependent on the method's function, i.e. a method that returns an Employee object or List of Employees can be typed to do just that, and you can utilize it by calling.
Employee EmpOfMonth = GetEmployeeOfTheMonth();
With error codes, all methods return an error code, so, for those that need to return something else to be used by the calling code, you have to pass a reference variable to be populated with that data, and test the return value for the error code, and handle it, on every function or method call.
Employee EmpOfMonth;
if (getEmployeeOfTheMonth(ref EmpOfMonth) == ERROR)
// code to Handle the error here
If you code so that each method does one and only one simple thing, then you should throw an exception whenever the method cannot accomplish the method's desired objective. Exceptions are much richer and easier to use in this way than error codes. Your code is much cleaner - The standard flow of the "normal" code path can be devoted strictly to the case where the method IS able to accomplish what you wanted it to do... And then the code to clean up, or handle the "exceptional" circumstances when something bad happens that prevents the method from completing successfully can be siloed away from the normal code. Additionally, if you can't handle the exception where it occurred, and must pass it up the stack to a UI, (or worse, across the wire from a mid-tier component to a UI), then with the exception model, you don't need to code every intervening method in your stack to recognize and pass the exception up the stack... The exception model does this for you automagically.... With error codes, this piece of the puzzle can get onerous very rapidly.
You should use both. The thing is to decide when to use each one.
There are a few scenarios where exceptions are the obvious choice:
In some situations you can't do anything with the error code, and you just need to handle it in an upper level in the call stack, usually just log the error, display something to the user or close the program. In these cases, error codes would require you to bubble up the error codes manually level by level which is obviously much easier to do with exceptions. The point is that this is for unexpected and unhandleable situations.
Yet about situation 1 (where something unexpected and unhandleable happens you just wan't to log it), exceptions can be helpful because you might add contextual information. For example if I get a SqlException in my lower-level data helpers, I will want to catch that error in the low-level (where I know the SQL command that caused the error) so I can capture that information and rethrow with additional information. Please note the magic word here: rethrow, and not swallow.
The first rule of exception handling: do not swallow exceptions. Also, note that my inner catch doesn't need to log anything because the outer catch will have the whole stack trace and may log it.
In some situations you have a sequence of commands, and if any of them fail you should cleanup/dispose resources(*), whether or not this is an unrecoverable situation (which should be thrown) or a recoverable situation (in which case you can handle locally or in the caller code but you don't need exceptions). Obviously it's much easier to put all those commands in a single try, instead of testing error codes after each method, and cleanup/dispose in the finally block. Please note that if you want the error to bubble up (which is probably what you want), you don't even need to catch it - you just use the finally for cleanup/dispose - you should only use catch/retrow if you want to add contextual information (see bullet 2).
One example would be a sequence of SQL statements inside a transaction block. Again, this also a "unhandleable" situation, even if you decide to catch it early (treat it locally instead of bubbling up to the top) it's still a fatal situation from where the best outcome is to abort everything or at least abort a large part of the process.
(*) This is like the on error goto that we used in old Visual Basic
In constructors you can only throw exceptions.
Having said that, in all other situations where you're returning some information on which the caller CAN/SHOULD take some action, using return codes is probably a better alternative. This includes all expected "errors", because probably they should be handled by the immediate caller, and will hardly need to be bubbled up too many levels up in the stack.
Of course it's always possible to treat expected errors as exceptions, and catch then immediately one level above, and it's also possible to encompass every line of code in a try catch and take actions for each possible error. IMO, this is bad design, not only because it's much more verbose, but specially because the possible exceptions that might be thrown are not obvious without reading the source code - and exceptions could be thrown from any deep method, creating invisible gotos. They break code structure by creating multiple invisible exit points that make code hard to read and inspect. In other words, you should never use exceptions as flow-control, because that would be hard for others to understand and maintain. It can get even difficult to understand all possible code flows for testing.
Again: for correct cleanup/dispose you can use try-finally without catching anything.
The most popular criticism about return codes is that "someone could ignore the error codes, but in the same sense someone can also swallow exceptions. Bad exception handling is easy in both methods. But writing good error-code-based program is still much easier than writing an exception-based program. And if one by any reason decides to ignore all errors (the old on error resume next), you can easily do that with return codes and you can't do that without a lot of try-catchs boilerplate.
The second most popular criticism about return codes is that "it's difficult to bubble up" - but that's because people don't understand that exceptions are for non-recoverable situations, while error-codes are not.
Deciding between exceptions and error codes is a gray area. It's even possible that you need to get an error code from some reusable business method, and then you decide to wrap that into an exception (possibly adding information) and let it bubble up. But it's a design mistake to assume that ALL errors should be thrown as exceptions.
To sum it up:
I like to use exceptions when I have an unexpected situation, in which there's not much to do, and usually we want to abort a large block of code or even the whole operation or program. This is like the old "on error goto".
I like to use return codes when I have expected situations in which the caller code can/should take some action. This includes most business methods, APIs, validations, and so on.
This difference between exceptions and error codes is one of the design principles of the GO language, which uses "panic" for fatal unexpected situations, while regular expected situations are returned as errors.
Yet about GO, it also allows multiple return values , which is something that helps a lot on using return codes, since you can simultaneously return an error and something else. On C#/Java we can achieve that with out parameters, Tuples, or (my favorite) Generics, which combined with enums can provide clear error codes to the caller:
public MethodResult<CreateOrderResultCodeEnum, Order> CreateOrder(CreateOrderOptions options)
{
....
return MethodResult<CreateOrderResultCodeEnum>.CreateError(CreateOrderResultCodeEnum.NO_DELIVERY_AVAILABLE, "There is no delivery service in your area");
...
return MethodResult<CreateOrderResultCodeEnum>.CreateSuccess(CreateOrderResultCodeEnum.SUCCESS, order);
}
var result = CreateOrder(options);
if (result.ResultCode == CreateOrderResultCodeEnum.OUT_OF_STOCK)
// do something
else if (result.ResultCode == CreateOrderResultCodeEnum.SUCCESS)
order = result.Entity; // etc...
If I add a new possible return in my method, I can even check all callers if they are covering that new value in a switch statement for example. You really can't do that with exceptions. When you use return codes, you'll usually know in advance all possible errors, and test for them. With exceptions you usually don't know what might happen. Wrapping enums inside exceptions (instead of Generics) is an alternative (as long as it's clear the type of exceptions that each method will throw), but IMO it's still bad design.
EDIT 2020-10-11:
Since C# 7.0 (March 2017) instead of Generics I prefer to use the new Tuples syntax which allows multiple return values (so we can use GO-like syntax where methods return a result OR an error).
public enum CreateUserResultCodeEnum
{
[Description("Username not available")]
NOT_AVAILABLE,
}
public (User user, CreateUserResultCodeEnum? error) CreateUser(string userName)
// (try to create user, check if not available...)
if (notAvailable)
return (null, CreateUserResultCodeEnum.NOT_AVAILABLE);
return (user, null);
}
// How to call and deconstruct tuple:
(var user, var error) = CreateUser("john.doe");
if (user != null) ...
if (error == CreateUserResultCodeEnum.NOT_AVAILABLE) ...
// Or returning a single object (named tuple):
var result = CreateUser("john.doe");
if (result.user != null) ...
if (result.error == CreateUserResultCodeEnum.NOT_AVAILABLE) ...
EDIT 2021-01-09:
A few days ago I wrote this blog post about how we can (in some cases!) use multiple returns instead of exceptions (like golang convention explained above, not supposed to replace all your exceptions but supposed to give you arsenal to decide between when to use exceptions and when to use return codes).
By the end of the post I'm mixing two models - basically I'm using the ValueTuple syntax (which is very concise and elegant) but yet using Generics as the underlying structure.
Basically I use implicit conversion operator and type deconstructors to convert back and forth between ValueTuple and CommandResult<TEntity, TError>.
In the past I joined the errorcode camp (did too much C programming). But now I have seen the light.
Yes exceptions are a bit of a burden on the system. But they simplify the code, reducing the number of errors (and WTF's).
So use exception but use them wise. And they will be your friend.
As a side note. I have learned to document which exception can be thrown by which method. Unfortunately this is not required by most languages. But it increases the chance of handling the right exceptions at the right level.
There may be a few situations where using exceptions in a clean, clear, correct way is cumbersome, but the vast majority of the time exceptions are the obvious choice. The biggest benefit exception handling has over error codes is that it changes the flow of execution, which is important for two reasons.
When an exception occurs, the application is no longer following it's 'normal' execution path. The first reason why this is so important is that unless the author of the code goes well and truly out of their way to be bad, the program will halt and not continue doing unpredictable things. If an error code doesn't get checked and appropriate actions aren't taken in response to a bad error code, the program will keep on doing what it's doing and who knows what the result of that action will be. There are lots of situations where having the program do 'whatever' could wind up being very expensive. Consider a program that retrieves performance information for various financial instruments a company sells, and delivers that information to brokers/wholesalers. If something goes wrong and the program keeps going, it could ship erroneous performance data to the brokers and wholesalers. I don't know about anybody else, but I don't want to be the one sitting in a VPs office explaining why my code caused the company to get 7-figures worth of regulatory fines. Delivering an error message to customers is generally preferable to delivering wrong data that could look to be 'real', and the latter situation is much easier to run into with a much less aggressive approach like error codes.
The second reason why I like exceptions and their breaking of the normal execution is that it makes it much, much easier to keep the 'normal things are happening' logic separate from the 'something went wrong logic'. To me, this:
try {
// Normal things are happening logic
catch (// A problem) {
// Something went wrong logic
}
...is preferable to this:
// Some normal stuff logic
if (errorCode means error) {
// Some stuff went wrong logic
}
// Some normal stuff logic
if (errorCode means error) {
// Some stuff went wrong logic
}
// Some normal stuff logic
if (errorCode means error) {
// Some stuff went wrong logic
}
There are other little things about exceptions that are nice, as well. Having a bunch of conditional logic to keep track of whether any of the methods being called in a function had an error code returned, and return that error code higher up is a lot of boiler plate. In fact, it's a lot of boiler plate that can go wrong. I have a lot more faith in the exception system of most languages than I do a rats nest of if-else-if-else statements that 'Fresh-out-of-college' Fred wrote, and I have a lot better things to do with my time than code reviewing said rat's nest.
My reasoning would be if you are writing a low-level driver that really needs performance, then use error codes. But if you're using that code in a higher-level application and it can handle a bit of overhead, then wrap that code with an interface which checks those error codes and raises exceptions.
In all other cases, exceptions are probably the way to go.
My approach is that we can use both, i.e. Exceptions and Errors codes at the same time.
I'm used to define several types of Exceptions (ex: DataValidationException or ProcessInterruptExcepion) and inside each exception define a more detailed description of each problem.
A Simple Example in Java:
public class DataValidationException extends Exception {
private DataValidation error;
/**
*
*/
DataValidationException(DataValidation dataValidation) {
super();
this.error = dataValidation;
}
}
enum DataValidation{
TOO_SMALL(1,"The input is too small"),
TOO_LARGE(2,"The input is too large");
private DataValidation(int code, String input) {
this.input = input;
this.code = code;
}
private String input;
private int code;
}
In this way i use Exceptions to define category errors, and error codes to define more detailed info about the problem.
I may be sitting on the fence here, but...
It depends on the language.
Whichever model you choose, be consistent about how you use it.
In Python, use of exceptions is standard practice, and I'm quite happy to define my own exceptions. In C you don't have exceptions at all.
In C++ (in the STL at least), exceptions are typically only thrown for truly exceptional errors (I virtually never see them myself). I see no reason to do anything different in my own code. Yes it's easy to ignore return values, but C++ doesn't force you to catch exceptions either. I think you just have to get into the habit of doing it.
The code base I work on is mostly C++ and we use error codes almost everywhere, but there's one module that raises exceptions for any error, including very unexceptional ones, and all the code that uses that module is pretty horrible. But that might just be because we've mixed exceptions and error codes. The code that consistently uses error codes is much easier to work with. If our code consistently used exceptions, maybe it wouldn't be as bad. Mixing the two doesn't seem to work so well.
Since I work with C++, and have RAII to make them safe to use, I use exceptions almost exclusively. It pulls error handling out of the normal program flow and makes the intent more clear.
I do leave exceptions for exceptional circumstances though. If I'm expecting that a certain error is going to happen a lot I'll check that the operation will succeed before performing it, or call a version of the function that uses error codes instead (Like TryParse())
Method signatures should communicate to you what the method does. Something like
long errorCode = getErrorCode();
might be fine, but
long errorCode = fetchRecord();
is confusing.
Exceptions are for exceptional circumstances - ie, when they are not part of the normal flow of the code.
It's quite legitimate to mix Exceptions and error codes, where error codes represent the status of something, rather than an error in the running of the code per se (e.g. checking the return code from a child process).
But when an exceptional circumstance occurs I believe Exceptions are the most expressive model.
There are cases where you might prefer, or have, to use error codes in place of Exceptions, and these have been adequately covered already (other than other obvious constrains such as compiler support).
But going in the other direction, using Exceptions allows you to build even higher level abstractions to your error handling, that can make your code even more expressive and natural. I would highly recommend reading this excellent, yet underrated, article by C++ expert Andrei Alexandrescu on the subject of what he calls, "Enforcements": http://www.ddj.com/cpp/184403864. Although it's a C++ article the principles are generally applicable, and I have translated the enforcements concept to C# quite successfully.
First, I agree with Tom's answer that for high-level stuff use exceptions, and for low-level stuff use error codes, as long as it is not Service Oriented Architecture (SOA).
In SOA, where methods may be called across different machines, exceptions may not be passed over the wire, instead, we use success/failure responses with a structure like below (C#):
public class ServiceResponse
{
public bool IsSuccess => string.IsNullOrEmpty(this.ErrorMessage);
public string ErrorMessage { get; set; }
}
public class ServiceResponse<TResult> : ServiceResponse
{
public TResult Result { get; set; }
}
And use like this:
public async Task<ServiceResponse<string>> GetUserName(Guid userId)
{
var response = await this.GetUser(userId);
if (!response.IsSuccess) return new ServiceResponse<string>
{
ErrorMessage = $"Failed to get user."
};
return new ServiceResponse<string>
{
Result = user.Name
};
}
When these are used consistently in your service responses it creates a very nice pattern of handling success/failures in the application. This allows easier error handling in async calls within services as well as across services.
I would prefer Exceptions for all error cases, except when a failure is an expectable bug-free result of a function that returns a primitive datatype. E.g. finding the index of a substring within a larger string would usually return -1 if not found, instead of raising a NotFoundException.
Returning invalid pointers that might be dereferenced (e.g. causing NullPointerException in Java) is not acceptable.
Using multiple different numerical error codes (-1, -2) as return values for the same function is usually bad style, as clients might do a "== -1" check instead of "< 0".
One thing to keep in mind here is the evolution of APIs over time. A good API allows to change and extend failure behavior in several ways without breaking clients. E.g. if a client error handle checked for 4 error cases, and you add a fifth error value to your function, the client handler may not test this and break. If you raise Exceptions, this will usually make it easier for clients to migrate to a newer version of a library.
Another thing to consider is when working in a team, where to draw a clear line for alldevelopers to make such a decision. E.g. "Exceptions for high-level stuff, error codes for low-level stuff" is very subjective.
In any case, where more than one trivial type of error is possible, the source code should never use the numeric literal to return an error code or to handle it (return -7, if x == -7 ...), but always a named constant (return NO_SUCH_FOO, if x == NO_SUCH_FOO) .
If you work under big project, you can't use only exceptions or only error codes. In different cases you should use different approaches.
For example, you decide to use exceptions only. But once you decide to use async event processing. It is bad idea to use exceptions for error handling in this situations. But use error codes everywhere in application is tedious.
So my opinion that it is normal to use both exceptions and error codes simultaneous.
For most applications, exceptions are better. The exception is when the software has to communicate with other devices. The domain I work in is industrial controls. Here errors codes are preferred and expected. So my answer is that it does depend on the situation.
I think it also depends on whether you really need information like stack trace from the result. If yes, you definitely go for Exception which provide object full with lots of information about problem. However, if you are just interested in result and don't care why that result then go for error code.
e.g. When you are processing file and face IOException, client might interested in knowing from where this was triggered, in opening file or parsing file etc. So better you return IOException or its specific subclass. However, scenario like you have login method and you want to know it was successful or not, there either you just return boolean or to show correct message, return error code. Here Client is not interested in knowing which part of logic caused that error code. He just know if its Credential invalid or account lock etc.
Another usecase I can think of is when data travels on network. Your remote method can return just error code instead of Exception to minimize data transfer.
My general rule is:
Only one error could appear in a function: use error code (as parameter of the function)
More than one specific error could appear: throw exception
Error codes also don't work when your method returns anything other than a numeric value...

What is the best implementation of an exception mechanism?

Most program languages have some kind of exception handling; some languages have return codes, others have try/catch, or rescue/retry, etc., each with its own pecularities in readability, robustness, and practical effectiveness in a large group development effort. Which one is the best and why ?
I would say that depends on the nature of your problem. Different problem domains could require almost arbitrary error messages, while other trivial tasks just can return NULL or -1 on error.
The problem with error return codes is that you're polluting/masking the error since it can be ignored (sometimes without the API client not knowing they should check for the error code). It gives a (reasonably) valid output from the method at hand.
Imagine you have an API where you ask for a index key for some map, store it in a list, and then continue running. The API then at a later moment sends a callback, and that method might then traverse the table, using the key which might be -1 in this example (the error code). BOOM, the application crashes as you index to -1 in some array, and those kinds of problems can be very hard to nail down. This is still a trivial example, but it illustrates a problem with error codes.
On the other hand, error codes are faster than throwing exceptions, and you might want to use them for frequently accessed method calls - if it is appropriate to return such an error code. I would say that trying to encapsulate these kinds of error codes within a private assembly would be quite OK since you're not exposing those error codes to the client of the API. Always remember to document these methods rigorously since these kinds of application nukes can linger around in an application for a long time since they were triggered before it goes off.
Personally, I prefer a mix of them both to some extent. I use exceptions just for that - exceptions - when the program runs into a state which was not expected and needs to inform something has gone way out of plan. I am not a sucker of writing try/catch blocks all over my code, but it's all down to personal preference.
Best for what? Language design is always about tradeoffs. The advantage of return codes is that they don't require any runtime support beyond regular function calls; the disadvantages are 1) you always have to check them 2) the return type has to have a failure value that isn't a valid result of the function call.
The advantage of automatic exception handling is that error conditions in your code don't disappear.
The differences between exception handling semantics in various languages (and Lisp's condition system, E's ejectors, etc) mainly show up in how stack unwinding is dealt with when program execution should continue.
To summarize, though: automatic exception handling is extremely valuable when you need to write readable, robust software, especially in a large team. Letting the computer track error conditions for you gives you one less thing to think about when reading code, and it removes an opportunity for error. The only time I'd use return codes to indicate errors is if I was implementing a language with exception handling in one that didn't have it.
try/catch/finally does the job admirably.
It allows the programmer to handle specific conditions as well as general failures gracefully.
All said and done I'm sure that each is as good as any other.
I'd have to go with the try / catch concept. I feel like in terms of readability this provides the most to a code maintainer. It should be fairly straight forward to find the chain of function calls as long as the exception is properly typed and the associated message contains detailed enough data (I personally do not like including stack traces but I know plenty who do and this would make this even more traceable.) The return code implementation requires an external table of code definitions on a program by program basis. Which from personal experience is both unwieldy to maintain and reference.
For unusual perspective on exception handling, see Haskell's Control.Exception monad