Showing posts with label handling. Show all posts
Showing posts with label handling. Show all posts

Sunday, March 16, 2014

Pants on Fire: 9 Lies That Programmers Tell Themselves

Pants on Fire: 9 Lies That Programmers Tell Themselves
Software developers, like everybody else, aren't always honest with themselves. Here are some common untruths that they can come to believe are true.



Everybody lies to themselves now and again (“I can’t weigh that much; my scale must be off”) in both their personal and professional lives. Some professions, however, may be more prone to it than others. Software developers, who often work - alone - for long hours under tight deadlines seem to be particularly susceptible to a little self-delusion. By reaching out to developers on social media and reviewing developer comments in discussion forums and elsewhere online, ITworld has compiled 9 of the most common white lies that programmers will tell themselves. How little these white lies are is left up to the reader.


This code doesn’t need commenting
Commenting code is, let's face it, kind of drag, so developers will often find reasons to not do it, or, at least, put it off until later. Sometimes the reasons may be valid but other times, not so much.

"I don't need to comment this, I'll know what's going on. I wrote it for god's sake." Alek

"No one could possibly fail to understand my simple user interface" John Morrow

"I'll remember what I did here without adding a comment to explain it." Avenger

"Code is self documenting." Toby Thain

"I don't need comments because I know what the commands do" Shaun Bebbington



This code doesn’t need commenting
Commenting code is, let's face it, kind of drag, so developers will often find reasons to not do it, or, at least, put it off until later. Sometimes the reasons may be valid but other times, not so much.

"I don't need to comment this, I'll know what's going on. I wrote it for god's sake." Alek

"No one could possibly fail to understand my simple user interface" John Morrow

"I'll remember what I did here without adding a comment to explain it." Avenger

"Code is self documenting." Toby Thain

"I don't need comments because I know what the commands do" Shaun Bebbington



I can do it better myself
The growth of open source has made all sorts of code, tools and applications available to developers for free, but that hasn’t stopped them from often preferring to "role their own." Software engineers are nothing if not a confident in their own abilities.

"My homebrew framework will be nimble, lightweight, debugged, and easy to use." Toby Thain

"I don't need to following the interface norms of X because my way of doing things is better…" Mark Harrison

"I can write assembly that outperforms gcc -O3" Alex Feinberg

"My own parser will do fine." Toby Thain

"My code is better than your code." William Emmanuel Yu



I’ll fix this later
Programmers are often faced with the tradeoff of doing something fast or doing it "right," whether it's to fix a critical bug or meet a deadline. Coding compromises are often made in the name of saving time with the intention to fix or clean up the not-quite-perfect code later - often with the knowledge that later will never come.

"I know this is dirty code, I will rewrite it later." GerardYin

"We'll fix this in a later release." notgeorgelucas

"I'll come back and comment this later" schrodingerspanda

"This bug can be ignored for now" makemehumanagain

"I'll refactor this before I release it." Dave Cole



It’s only a small change
When making a change to code, either to fix a bug or add some functionality, even the smallest tweak can often turn into a bigger task than expected due to unexpected dependencies. No matter how many time they've experienced this, though, coders can still forget that there are rarely truly minor code changes.

"That is going to be a simple minor change." Hummigbird1

"It's just one line... it won't break anything" bleepster

"it will not affect the rest of the program code!" just cool stuff

"No need for database transactions, nothing can possibly fail here!" Ahmet Alp Balkan

"This minor unrelated change in the code could not possibly be the cause for the unit tests failing." Hummigbird1



It’s not a bug
Sometimes developers don't like to admit that their code is doing something wrong or has a bug. After all, they wrote it, they tested it (hopefully) and it works fine for them. Either the users are doing something wrong or they just misunderstand how the tool or application is supposed to work. At least that's what a developer may think.

"It works on my machine" Madsdad

"It's not a bug, it's a feature!" Ron007

"if it compiles, it must be correct!" Philip Guo

"If it passes tests, it must be correct." Michal Pise

"It works" Alec Heller



I know what I’m doing
Programmers' overconfidence can sometimes, wrongly, convince them they know what they're doing which, believe it or not, isn't always the case. It can lead them to cut corners, charge blindly into the fray or generally not be careful, all of which can lead to trouble.

"I can skip design and architecture and leap right into coding." Toby Thain

"I totally understand that legacy code!" Hummigbird1

"I know what the client wants." DutchS

"I don't need version control." Toby Thain

"I know what I'm doing." Kyle



I can safely skip that test
Testing is a necessary part of creating software and not always so much fun. Much like writing comments, programmers can sometimes find an excuse for not writing or performing tests or otherwise properly putting their code through it’s paces.

"Tests are usually redundant, it is working now with this input and it proves that." Ahmet Alp Balkan

"If I write some unit tests, I don't need type checking." Toby Thain

"It's a simple one-line change, we don't need to test it." Sami Kukkonen



I’m using <NAME OF FAVORITE PROGRAMMING LANGUAGE HERE> so we’re good
Software developers have their favorite programming languages, ones that they come to know well, trust and depend on. Their love of and loyalty to their favorite language, however, can sometimes make them less than honest with themselves about that language’s possible faults, drawbacks or limitations.

"If it's written in C, it will be fast." Toby Thain

"It's written in Python, so it's easy to extend." Alec Heller

"Java runs everywhere." Ahmet Alp Balkan


Wednesday, January 29, 2014

automatic jUnit test generators - review

This could be scary one. 

When I heard term “automatic jUnit test generator” I was thinking: “no one should go that path”, ”units test should be written by the developers”, “do you want to replace devs?”, “test should be written before code!”.

But I gave it closer look, and actually “closer think” – did I really expect that there is some AI module which will go through code and automatically write tests – if so why there is no AI which automatically write code in first place … [maybe soon ;-)]

Before you send thousands of hate comments, let’s give it quick look what is definition and what should you expect by automatic jUnit test generator:
  • it's everywhere - right click on class in eclipse or intelliJ and you’ll have it - that's point first and should be breakthrough in your thinking about generators ;-)
  • if you want to write jUnit for class A that is dependent on: log, dbDao, jmsHelper, etc... - there are few different schools, but for simplicity let’s say that you'll write mocks for each of them
  • then if you'll have:
    • class B,C dependent on jmsHelper and log
    • class D,E dependent on dbDao and log
    • etc ...
  • and there is team of people working on same code
Result => we will see developer per class / copy-paste pattern.

What if instead standard eclipse jUnit plugin you’ll use tool that where you'll create "mappers/patterns" for each class that will produce that mocks automatically?
Then you'll run "generator" and it will create same structure as eclipse/intelliJ "right click", but with all mocks already copied - no need to create boilerplate code by each developer separately?

And … there will be no real test code there - plain output jUnit just like in "right click".

If I calculate it properly, I spend like 50% of testing time - writing boilerplate code [setting up all mocks, adding standard "patterns", etc...].
To speed up it I usually finish with copy-paste pattern which from other hand I'm extreme oppositionist.

Using generators I'll not to do it again - yes, of course I need to do it once at beginning, maybe some maintenance, but then it will be reused, and whole solution will be consistent.

So, now we should be on same page.

At first I was skeptic if something like that could exist, but ..

Generators:
I've take 4 generators for review:

  • AgitarOne
  • JTest - Parasoft
  • Randoop
  • CodePro AnalytiX - google
there are probably more - but to speed up process of speeding up process I  also have some time constrains  ;-)


Test scenario:
1.     Choose few most “typical” classes for that project – together easy and more complicated.
2.     Using different tools generate test cases.
3.     Compare generated jUnits from usability perspective (what was generated, how many methods, what amount of code was there,..)  also from percentage of code covered.


Output:

  • AgitarOne - quite nice, but is not generating plain jUnits, there is strong dependency on Agitar version of jUnits and if you don’t have license it will not work - so I’ll not take it into consideration [commercial]
  • Randoop - created random "stress" test cases, quite different from others - delivers almost full tests, finds typical corner case scenarios (NPE, OutOfIndex, ..) [opensource]
  • jTest Parasoft - created boilerplate test code using plain jUnit (which is significant plus compared to Agitar) - it works just like standard jUnit eclipse/intelliJ plugin which means one test for one method, no code analysis[commercial] 
  • CodePro AnalytiX - created boilerplate test code using plain jUnit and EasyMock, with static code analysis - created number of test per method depends on "if-cases" which was quite good especially in the case when we go through existing stuff - definitely that will speed up writing, there are other cool tools in the pack, supporting: code coverage, dependency analysis, metrics computation, audit, etc... which also is pretty cool as developer don't need to wait till Sonar give you stats after commits - you can have it on-demand [freeware]

Recommendation / Winner:
CodePro AnalytiX

Discussion:
CodePro is good call - is generating lots of boilerplate code for a developer and save lots of time. Still complex code cannot be completely automated, and developer need to fill gaps - but it is showing you that gaps, suggesting what should be tested.
In different scenario (and I'm thinking also about code reviews) I will give a try to randoop - as is generating whole test, developer  don't need to touch the code (almost ;-) ), and is testing specific corner cases - which you can miss otherwise.

Note:
Of course there are some promises that "generators will exercise" code, which at end will look like (i.e.: method that is adding two ints):
public void testAdd_1() throws Exception
{
     int x=1;
     int y=2;
     int result = Tested.add(x, y);
    // add test code here
}

Still developer need to go there and:
- add asserts,
- change name of the method to something meaningful,
- add comments,
- [change whatever is specific to your team process/code quality]

I my opinion CodePro is really good replacement for standard eclipse jUnit generator - in worst case (day first) you'll have exactly same output, in best case - you'll need to add only asserts!

Wednesday, October 2, 2013

Java: Best Practices for Exception Handling

We as programmers want to write quality code that solves problems. Unfortunately, exceptions come as side effects of our code. No one likes side effects, so we soon find our own ways to get around them.


  • Throw exceptions when the method cannot handle the exception, and more importantly, should be handled by the caller. A good example of this happens to present in the Servlet API - doGet() and doPost() throw ServletException or IOException in certain circumstances where the request could not be read correctly. Neither of these methods are in a position to handle the exception, but the container is (which results in the 50x error page in most cases).
  •  Bubble the exception if the method cannot handle it. This is a corollary of the above, but applicable to methods that must catch the exception. If the caught exception cannot be handled correctly by the method, then it is preferable to bubble it.
  •  Throw the exception right away. This might sound vague, but if an exception scenario is encountered, then it is a good practice to throw an exception indicating the original point of failure, instead of attempting to handle the failure via error codes, until a point deemed suitable for throwing the exception. In other words, attempt to minimize mixing exception handling with error handling.
  • Either log the exception or bubble it, but don't do both. Logging an exception often indicates that the exception stack has been completely unwound, indicating that no further bubbling of the exception has occurred. Hence, it is not recommended to do both at the same time, as it often leads to a frustrating experience in debugging.
  •  Use subclasses of java.lang.Exception (checked exceptions), when you except the caller to handle the exception. This results in the compiler throwing an error message if the caller does not handle the exception. Beware though, this usually results in developers "swallowing" exceptions in code.
  •  Use subclasses of java.lang.RuntimeException (unchecked exceptions) to signal programming errors. The exception classes that are recommended here include IllegalStateException, IllegalArgumentException, UnsupportedOperationException etc. Again, one must be careful about using exception classes like NullPointerException (almost always a bad practice to throw one).
  •  Use exception class hierarchies for communicating information about exceptions across various tiers. By implementing a hierarchy, you could generalize the exception handling behavior in the caller. For example, you could use a root exception like DomainException which has several subclasses like InvalidCustomerException, InvalidProductException etc. The caveat here is that your exception hierarchy can explode very quickly if you represent each separate exceptional scenario as a separate exception.
  • Avoid catching exceptions you cannot handle. Pretty obvious, but a lot of developers attempt to catch java.lang.Exception or java.lang.Throwable. Since all subclassed exceptions can be caught, the runtime behavior of the application can often be vague when "global" exception classes are caught. After all, one wouldn't want to catch OutOfMemoryError - how should one handle such an exception?
  • Wrap exceptions with care. Rethrowing an exception resets the exception stack. Unless the original cause has been provided to the new exception object, it is lost forever. In order to preserve the exception stack, one will have to provide the original exception object to the new exception's constructor.
  •  Convert checked exceptions into unchecked ones only when required. When wrapping an exception, it is possible to wrap a checked exception and throw an unchecked one. This is useful in certain cases, especially when the intention is to abort the currently executing thread. However, in other scenarios this can cause a bit of pain, for the compiler checks are not performed. Therefore, adapting a checked exception as an unchecked one is not meant to be done blindly.




We as programmers want to write quality code that solves problems. Unfortunately, exceptions come as side effects of our code. No one likes side effects, so we soon find our own ways to get around them. I have seen some smart programmers deal with exceptions the following way:

public void consumeAndForgetAllExceptions(){
    try {
        ...some code that throws exceptions
    } catch (Exception ex){
        ex.printStacktrace();
    }
}

What is wrong with the code above?
Once an exception is thrown, normal program execution is suspended and control is transferred to the catch block. The catch block catches the exception and just suppresses it. Execution of the program continues after the catch block, as if nothing had happened.
How about the following?
public void someMethod() throws Exception{
}

This method is a blank one; it does not have any code in it. How can a blank method throw exceptions? Java does not stop you from doing this. Recently, I came across similar code where the method was declared to throw exceptions, but there was no code that actually generated that exception. When I asked the programmer, he replied "I know, it is corrupting the API, but I am used to doing it and it works."
It took the C++ community several years to decide on how to use exceptions. This debate has just started in the Java community. I have seen several Java programmers struggle with the use of exceptions. If not used correctly, exceptions can slow down your program, as it takes memory and CPU power to create, throw, and catch exceptions. If overused, they make the code difficult to read and frustrating for the programmers using the API. We all know frustrations lead to hacks and code smells. The client code may circumvent the issue by just ignoring exceptions or throwing them, as in the previous two examples.

The Nature of Exceptions

Broadly speaking, there are three different situations that cause exceptions to be thrown:

  • Exceptions due to programming errors: In this category, exceptions are generated due to programming errors (e.g., NullPointerException and IllegalArgumentException). The client code usually cannot do anything about programming errors.
  •  Exceptions due to client code errors: Client code attempts something not allowed by the API, and thereby violates its contract. The client can take some alternative course of action, if there is useful information provided in the exception. For example: an exception is thrown while parsing an XML document that is not well-formed. The exception contains useful information about the location in the XML document that causes the problem. The client can use this information to take recovery steps.
  • Exceptions due to resource failures: Exceptions that get generated when resources fail. For example: the system runs out of memory or a network connection fails. The client's response to resource failures is context-driven. The client can retry the operation after some time or just log the resource failure and bring the application to a halt.

Types of Exceptions in Java

Java defines two kinds of exceptions:

  • Checked exceptions: Exceptions that inherit from the Exception class are checked exceptions. Client code has to handle the checked exceptions thrown by the API, either in a catch clause or by forwarding it outward with the throws clause.
  •  Unchecked exceptions: RuntimeException also extends from Exception. However, all of the exceptions that inherit from RuntimeException get special treatment. There is no requirement for the client code to deal with them, and hence they are called unchecked exceptions.

I have seen heavy use of checked exceptions and minimal use of unchecked exceptions. Recently, there has been a hot debate in the Java community regarding checked exceptions and their true value. The debate stems from fact that Java seems to be the first mainstream OO language with checked exceptions. C++ and C# do not have checked exceptions at all; all exceptions in these languages are unchecked.
A checked exception thrown by a lower layer is a forced contract on the invoking layer to catch or throw it. The checked exception contract between the API and its client soon changes into an unwanted burden if the client code is unable to deal with the exception effectively. Programmers of the client code may start taking shortcuts by suppressing the exception in an empty catch block or just throwing it and, in effect, placing the burden on the client's invoker.

Checked exceptions are also accused of breaking encapsulation. Consider the following:

public List getAllAccounts() throws
    FileNotFoundException, SQLException{
    ...
}

The method getAllAccounts() throws two checked exceptions. The client of this method has to explicitly deal with the implementation-specific exceptions, even if it has no idea what file or database call has failed within getAllAccounts(), or has no business providing filesystem or database logic. Thus, the exception handling forces an inappropriately tight coupling between the method and its callers.

Best Practices for Designing the API

Having said all of this, let us now talk about how to design an API that throws exceptions properly.

1. When deciding on checked exceptions vs. unchecked exceptions, ask yourself, "What action can the client code take when the exception occurs?"


If the client can take some alternate action to recover from the exception, make it a checked exception. If the client cannot do anything useful, then make the exception unchecked. By useful, I mean taking steps to recover from the exception and not just logging the exception. To summarize:
Client's reaction when exception happens           Exception type
Client code cannot do anything                           Make it an unchecked exception
Client code will take some useful recovery          Make it a checked exception
 action based on information in exception           
Moreover, prefer unchecked exceptions for all programming errors: unchecked exceptions have the benefit of not forcing the client API to explicitly deal with them. They propagate to where you want to catch them, or they go all the way out and get reported. The Java API has many unchecked exceptions, such as NullPointerException, IllegalArgumentException, and IllegalStateException. I prefer working with standard exceptions provided in Java rather than creating my own. They make my code easy to understand and avoid increasing the memory footprint of code.

2. Preserve encapsulation.


Never let implementation-specific checked exceptions escalate to the higher layers. For example, do not propagate SQLException from data access code to the business objects layer. Business objects layer do not need to know about SQLException. You have two options:
·         Convert SQLException into another checked exception, if the client code is expected to recuperate from the exception.
·         Convert SQLException into an unchecked exception, if the client code cannot do anything about it.
Most of the time, client code cannot do anything about SQLExceptions. Do not hesitate to convert them into unchecked exceptions. Consider the following piece of code:

public void dataAccessCode(){
    try{
        ..some code that throws SQLException
    }catch(SQLException ex){
        ex.printStacktrace();
    }
}
This catch block just suppresses the exception and does nothing. The justification is that there is nothing my client could do about an SQLException. How about dealing with it in the following manner?
public void dataAccessCode(){
    try{
        ..some code that throws SQLException
    }catch(SQLException ex){
        throw new RuntimeException(ex);
    }
}

This converts SQLException to RuntimeException. If SQLException occurs, the catch clause throws a new RuntimeException. The execution thread is suspended and the exception gets reported. However, I am not corrupting my business object layer with unnecessary exception handling, especially since it cannot do anything about an SQLException. If my catch needs the root exception cause, I can make use of the getCause() method available in all exception classes as of JDK1.4.
If you are confident that the business layer can take some recovery action when SQLException occurs, you can convert it into a more meaningful checked exception. But I have found that just throwing RuntimeException suffices most of the time.

3. Try not to create new custom exceptions if they do not have useful information for client code.


What is wrong with following code?
public class DuplicateUsernameException
    extends Exception {}

It is not giving any useful information to the client code, other than an indicative exception name. Do not forget that Java Exception classes are like other classes, wherein you can add methods that you think the client code will invoke to get more information.
We could add useful methods to DuplicateUsernameException, such as:
public class DuplicateUsernameException
    extends Exception {
    public DuplicateUsernameException
        (String username){....}
    public String requestedUsername(){...}
    public String[] availableNames(){...}
}

The new version provides two useful methods: requestedUsername(), which returns the requested name, and availableNames(), which returns an array of available usernames similar to the one requested. The client could use these methods to inform that the requested username is not available and that other usernames are available. But if you are not going to add extra information, then just throw a standard exception:

throw new Exception("Username already taken");

Even better, if you think the client code is not going to take any action other than logging if the username is already taken, throw a unchecked exception:

throw new RuntimeException("Username already taken");
Alternatively, you can even provide a method that checks if the username is already taken.
It is worth repeating that checked exceptions are to be used in situations where the client API can take some productive action based on the information in the exception. Prefer unchecked exceptions for all programmatic errors. They make your code more readable.

4. Document exceptions.


You can use Javadoc's @throws tag to document both checked and unchecked exceptions that your API throws. However, I prefer to write unit tests to document exceptions. Tests allow me to see the exceptions in action and hence serve as documentation that can be executed. Whatever you do, have some way by which the client code can learn of the exceptions that your API throws. Here is a sample unit test that tests for IndexOutOfBoundsException:

public void testIndexOutOfBoundsException() {
    ArrayList blankList = new ArrayList();
    try {
        blankList.get(10);
        fail("Should raise an IndexOutOfBoundsException");
    } catch (IndexOutOfBoundsException success) {}
}

The code above should throw an IndexOutOfBoundsException when blankList.get(10) is invoked. If it does not, the fail("Should raise an IndexOutOfBoundsException") statement explicitly fails the test. By writing unit tests for exceptions, you not only document how the exceptions work, but also make your code robust by testing for exceptional scenarios.


Friday, March 22, 2013

Java: Best Practices for Using Exceptions

The next set of best practices show how the client code should deal with an API that throws checked exceptions.

1. Always clean up after yourself


If you are using resources like database connections or network connections, make sure you clean them up. If the API you are invoking uses only unchecked exceptions, you should still clean up resources after use, with try - finally blocks.

public void dataAccessCode(){
    Connection conn = null;
    try{
        conn = getConnection();
        ..some code that throws SQLException
    }catch(SQLException ex){
        ex.printStacktrace();
    } finally{
        DBUtil.closeConnection(conn);
    }
}

class DBUtil{
    public static void closeConnection
        (Connection conn){
        try{
            conn.close();
        } catch(SQLException ex){
            logger.error("Cannot close connection");
            throw new RuntimeException(ex);
        }
    }
}

DBUtil is a utility class that closes the Connection. The important point is the use of finally block, which executes whether or not an exception is caught. In this example, the finally closes the connection and throws a RuntimeException if there is problem with closing the connection.

2. Never use exceptions for flow control


Generating stack traces is expensive and the value of a stack trace is in debugging. In a flow-control situation, the stack trace would be ignored, since the client just wants to know how to proceed.
In the code below, a custom exception, MaximumCountReachedException, is used to control the flow.
public void useExceptionsForFlowControl() {
    try {
        while (true) {
            increaseCount();
        }
    } catch (MaximumCountReachedException ex) {
    }
    //Continue execution
}

public void increaseCount()
    throws MaximumCountReachedException {
    if (count >= 5000)
        throw new MaximumCountReachedException();
}

The useExceptionsForFlowControl() uses an infinite loop to increase the count until the exception is thrown. This not only makes the code difficult to read, but also makes it slower. Use exception handling only in exceptional situations.

3. Do not suppress or ignore exceptions


When a method from an API throws a checked exception, it is trying to tell you that you should take some counter action. If the checked exception does not make sense to you, do not hesitate to convert it into an unchecked exception and throw it again, but do not ignore it by catching it with {} and then continue as if nothing had happened.

4. Do not catch top-level exceptions


Unchecked exceptions inherit from the RuntimeException class, which in turn inherits from Exception. By catching the Exception class, you are also catching RuntimeException as in the following code:

try{
..
}catch(Exception ex){
}
The code above ignores unchecked exceptions, as well.

5. Log exceptions just once


Logging the same exception stack trace more than once can confuse the programmer examining the stack trace about the original source of exception. So just log it once.

Kowalski: The Rust-native Agentic AI Framework Evolves to v0.5.0 🦀

  TL;DR: Kowalski v0.5.0 brings deep refactoring, modular architecture, multi-agent orchestration, and robust docs across submodules. If yo...