Posts Tagged ‘java’

Continuous Delivery Slides

Posted in agile, continuous delivery, continuous integration, deployment, java, management, software development, testing, version control on July 5th, 2011 by Joerg – Be the first to comment

The last Java User Group event in Berlin was hosted at Hypoport. It was about Continuous Delivery. We had about 100 guests.

There where two talks. One by Axel Fontaine who introduced Continuous Delivery especially in a Java environment. You can find his talk on Parleys or on his Blog.

I had the pleasure to introduce our experiences with Continuous Delivery. We are currently developing a new product. Since we started about a year ago we consequently used Continuous Delivery. We learned quite some lessons on our way which I presented that evening. My Slides are available here. (As this was a german event the slides are in german)

Thanks to everyone who attended the event. It was a really nice evening. Special thanks to everybody who helped organizing it.

Scripting magic with Groovy, Grape and Jetty

Posted in groovy, java, tools on December 31st, 2009 by Joerg – 4 Comments

Groovy 1.7 has just been release and it’s time to play again. One of the new features, Grape inspired me to the try the following. I created a script that acts as a simple webserver using embedded jetty without the need to install anything else than Groovy 1.7 on your computer. Just save the script as simpleWebServer, make it executable and start it like

./simpleWebServer -d someDirWithHTMLFiles -p 9000

Surf to http://localhost:9000 and you will see.

Here is the full script. I will explain the details further down.

#!/usr/bin/env groovy

import org.mortbay.jetty.*;
import org.mortbay.jetty.handler.*

def cli = new CliBuilder (usage:'simpleHtmlServer -p PORT -d DIRECTORY')
cli.with {
 h longOpt:'help', 'Usage information'
 p longOpt:'port',argName:'port', args:1, type:Number.class,'Default is 8080'
 d longOpt:'dir', argName:'directory', args:1, 'Default is .'

def opts = cli.parse(args)
if(!opts) return
if( {

def server = new Server(opts.port.toInteger()?:8080)
def resourceHandler = new ResourceHandler(welcomeFiles:["index.html"],
server.handler = new HandlerList(handlers:[resourceHandler, new DefaultHandler()])


Here are the magic details about the script:

1. The Shebang

The first important thing about this script is the shebang.

#!/usr/bin/env groovy

If you are using a real operating system (sorry Windows users), this will let you start the script like a normal executable. I usually skip the .groovy appendix on script files, so it really feels like you are using a normal command line utility.

2. Grape

The next line uses the new feature of Groovy 1.7, called Grape. This is a dependency System that allows to load any dependency, that is available in the maven-repositories to be used inside a script.


The syntax is pretty easy. It uses the maven notation: groupId:artifactId:version. There is an alternative version that uses separate attributes for each but I prefer the shortcut.
This line will lookup the dependency in the maven repository, download it and store it in ~/.groovy/grape. So the first start of the script might take a moment. The second time will be faster.
Grape allows to use the full java ecosystem in a simple groovy script without any additional install. Groovy 1.7 is enough. I think this makes scripting in groovy incredible powerful.

3. The CliBuilder
The script should really feel like a command line utility. Therefore it needs to deal with parameters. This is where the CliBuilder comes in.

def cli = new CliBuilder (usage:'simpleHtmlServer -p PORT -d DIRECTORY')
cli.with {
 h longOpt:'help', 'Usage information'
 p longOpt:'port',argName:'port', args:1, type:Number.class,'Default is 8080'
 d longOpt:'dir', argName:'directory', args:1, 'Default is .'

def opts = cli.parse(args)
if(!opts) return
if( {

Groovy includes Apache commons CLI. But where the Java version is already helpful in parsing parameters, the Groovy version gets really simple. The example above creates one CliBuilder, that provides a “DSL” for defining the parameters. Further down they are three parameters defined. This is all thats needed.
After the args are parsed we can just simply use them using Groovy properties syntax like opts.parameterName. Even a pretty usage statement can be printed, when –help is called.

4. Dynamic constructors
I used one of the embedded Jetty examples ( as the foundation of my script. The configuration of the handlers looked something like that in Java:

ResourceHandler resource_handler=new ResourceHandler();
resource_handler.setWelcomeFiles(new String[]{"index.html"});

HandlerList handlers = new HandlerList();
handlers.setHandlers(new Handler[]{resource_handler,new DefaultHandler()});

Thats pretty long. Now the Groovy version looks like that:

def resourceHandler = new ResourceHandler(welcomeFiles:["index.html"],
server.handler = new HandlerList(handlers:[resourceHandler, new DefaultHandler()])

It uses dynamic constructors. Groovy allows to call a virtual constructor with a map of arguments, where the elements are actually bean properties. This allows a much more concise construction of an object, even if the original creator wasn’t so kind to provide a convenience constructor.

5. The Elvis Operator

You probably wondered what the following statement did in the last example:


Well, that was Elvis. In Java there is the ternary operator, which goes like this:

(condition)?(result if true):(result if false) 

In Grovvy there is something called the Groovy truth, which says if a statement is null, then it is false, else it is true. This makes the Elvis operator possible. Elvis says, if the statement is true (as in Groovy truth) then use the value of the statement, else use the value after the colon. This is a very concise way for realizing default values, which is often needed in scripts

With all the scripting features that were added in earlier versions and with Grape in 1.7 I think Groovy is finally a great alternative to usual scripting languages. When you are experienced in Java it’s probably much simpler to write a script in Groovy than in Perl, Ruby or even Bash. For me this is definitely true.

Well done, Groovy team!

IntelliJ IDEAs new directory-based project format

Posted in java, software development, tools on October 17th, 2009 by Joerg – 9 Comments

I am currently playing with the EAP-Version (Early Access Program) of my favorite IDE IntelliJ IDEA. Since the new version is not that far away it is time to learn the new features and I discovered one that surprised me. A small but pretty nice change.

(Update: Thanks to Strug I have realized that this feature is already present in Idea 8, you can use the action “Open in New (Directory based) format” to convert your project. Fortunately they renamed it to “Save as Directory-Based Format …” in Maia. )

IDEA has a new format to store the project files. It is called directory-based. Instead of using the three famous files .ipr .iml and .iws IDEA will now store all information into a directory, which is simply called .idea. It is located in the root folder of the project. This seems to be somewhat similar to eclipse’s .project folder. In a small example project I created the content of the new directory looks like this:

-rw-r--r--  1 joerg  joerg    163 17 Okt 09:53 ant.xml
-rw-r--r--  1 joerg  joerg   2107 17 Okt 09:53 compiler.xml
drwxr-xr-x  3 joerg  joerg    102 17 Okt 09:53 copyright
drwxr-xr-x  3 joerg  joerg    102 17 Okt 09:53 dictionaries
-rw-r--r--  1 joerg  joerg    277 17 Okt 09:53 encodings.xml
-rw-r--r--  1 joerg  joerg    170 17 Okt 09:53 fileColors.xml
-rw-r--r--  1 joerg  joerg   1595 17 Okt 09:53 misc.xml
-rw-r--r--  1 joerg  joerg    258 17 Okt 09:53 modules.xml
-rw-r--r--  1 joerg  joerg    207 17 Okt 09:53 templateLanguages.xml
-rw-r--r--  1 joerg  joerg    169 17 Okt 09:53 vcs.xml
-rw-r--r--  1 joerg  joerg  38245 17 Okt 10:21 workspace.xml

The files included in this directory depend on the settings you change in the IDE. So, if you would for instance set the SQL dialect for your project there will be another file called sqldialects.xml containing all settings about this.

There is one special file in there, which is workspace.xml. This file contains individual settings for the workspace, which are definitely not intended to be shared via version control. This is equivalent to the .iws file of the old format. IDEA will put this file automatically on the ignore list of your version control.

I see some advantages of the new format.

  • First of all it is easier to find specific settings. The filenames are meaningful and the files are small.
  • The new structure allows a very detailed control of which settings you want to share with your colleagues. If you don’t want to share e.g. your file coloring (another new feature of Maia) just put the file on the ignore list.
  • Directories of the projects saved in the new format will be recognized as projects in the open-project dialog. In the past this was one annoying additional click as you had to choose the .ipr file before.

The new directory based format is a small change but a very good one. It is often a sum of little detail-improvements that save a lot of trouble in daily work. So I am looking forward to the other details to be discovered.

By the way JetBrains released an open source version of IDEA two days ago. So if you want to try this just go to and download the Community Edition.

Scala Pattern Matching explained

Posted in java, scala, software development on April 26th, 2009 by Joerg – 1 Comment

I am currently reading Programming in Scala. For a programmer coming from an imperative world there many new concepts to learn. One of them is Pattern Matching. There are already lots of articles about it, but explaining something is still one of the best ways to learn. Here are the first 4 levels of understanding Pattern Matching.

Level 1 – Pattern Matching as simple switch/case replacement

Pattern Matching can simply be used to replace Java switch/case statements. This is called constant pattern and looks like this:

  def constantMatch(value:Any) = {
    value match {
      case "Hello" => "You said hello!"
      case 1 => "Oh, thats a 1!"
      case _ => "Don't know what you want!"

ConstantMatch is a function that takes a parameter of type Any. Any is the Scala pendant to java.lang.Object. This value is now matched against several constants. The first case is a String the second an Int and the last case is a wildcard for any other value.
There are a few differences to Java. First, there is no “fall through”. If a pattern has been matched its value will be returned. Thats the part after the => operator. This can be a full code block. The example above just shows the short version. The second difference is if no pattern matches Scala will throw a MatchError Exception. This is why the wildcard pattern is needed as the last line. This is more or less the same as the default clause of Java.

Level 2 – Introducing Variable patterns

Now level 1 was already more powerful than Java switch/case. But there are some more levels to go. The next step is introducing variable pattern. Here is an example:

 def variableMatch(value:Any) = {
    value match {
      case 1 =>"Oh, thats a 1!"
      case x =>"And thats a"+x+"!";

Instead of validating every possibly value the value itself is put into a variable. This variable can then be processed in the result block. You might recognize that there is no wildcard case(case _ => …). This is not necessary as the variable pattern will match any possible value. A wildcard would not even be possible. The compiler will complain that it is unreachable code.

Level 3 – Type Patterns

Type patterns allow to calculate the result based on the type of the value. Instead of using instanceof in Java or isInstanceOf in Scala this can just be done in a case statement. Let’s assume we have a class hierarchy used to calculate the financial value of different types of property.

abstract class Property {
  val value: BigDecimal

case class House(address: Address, override val value:BigDecimal) extends Property
case class Car(horsepower: Int, override val value:BigDecimal) extends Property
case class Horse(Age:Int, override val value:BigDecimal) extends Property
case class Address(street: String, city: String)

Ignore the case keyword for the moment. This is level 4. For all Java people, this code can be put in one file, although it is not recommended practice. I just do it here for simplicity. Property is the abstract base class. It defines a field value as all property needs to have a value. House, Car and Horse inherit from Property and add additional information. Address will be used in a later example.

For a special calculation the value will be applied based on the type of property. Houses will be applied with 80% of their value, Horses with 50% and the value of Cars will not be applied at all. Using Pattern Matching this looks like this:

  def applyPropertyValue(property:Property):BigDecimal = property match {
    case house:House => house.value * 0.8
    case horse:Horse => horse.value * 0.5
    case car:Car => 0
    case _ => property.value

Without any instanceof or casting the value has been calculated based on the type of property. Here is a wildcard pattern used in the last line again. If there is another type of property the full value will be applied.

Level 4 – Constructor patterns and Case Classes
The last example already used case classes even if it would have worked with normal classes too. Case classes have some special characteristics.

  • There is a special factory method that allows the class to be instantiated without the new keyword. Car(150,20000) creates a Car object with 150 horsepower and a value of 20.000.
  • All parameters in the constructor are automatically defined as val. So they are fields and can be accessed from other objects.
  • The compiler generates meaningful implementations of equals, hashcode and toString.
  • And of course they can be used in constructor patterns.

In our example we need some very special cases to calculate the value. If a house is in Berlin 90% instead of 80% of the value can be applied. Cars with a horsepower of more than 150 can be applied with 50% of their value instead of 0. Our function now gets two more lines:

  def applyPropertyValue(property:Property):BigDecimal = property match {
    case House(Address(_,"Berlin"),value) => value * 0.9 //Deep match
    case Car(horsepower, value) if horsepower > 150 => value * 0.5 //Pattern Guard
    case house:House => house.value * 0.8
    case horse:Horse => horse.value * 0.5
    case car:Car => 0
    case _ => property.value

The more special a case is the earlier it has to be validated. If the general case for Car would be matched first, the more specialized pattern would never be validated. In simple cases the Scala compiler complains about the code being unreachable.
The two new lines use the constructor pattern, that is only possible for case classes. But both also demonstrate other features of Pattern Matching. The House pattern shows a nested pattern. The important condition is in class Address, which is nested inside House. This kind of deep matches can save a lot of code. Imagine how many if statements, casts and instanceofs this needs in Java. The Car example shows another syntax for pattern matching. It is called Pattern Guards. An additional if after the pattern allows to validate conditions, before the pattern code will be excecuted.

Level 5 and above
This is still not all that can be learned about Pattern Matching. The story goes on with sequence patterns, sealed classes, partial functions and much more. But by now you should be able to understand most Pattern Matching statements that can be found in Scala. For more details I can only recommend reading Programming in Scala. It contains a lot of fun stuff like that.

Five random lessons learned about Scala

Posted in java, scala, software development on April 15th, 2009 by Joerg – 7 Comments

Since a week I am playing around with Scala to see what all this fuss is about. After Twitter has anounced that they are using Scala (see this presentation) there is a real hype now. So far I must admit I am impressed. This language is really nice. I will certainly have a very detailed look. The book “Programming in Scala” is already on its way from Amazon.

The following lessons learned are just a kind of note to self. These are some random experiences I made when playing around. Your first lessons will probably be completely different.

1. Scala != Groovy
Although this is obvious, when you have prior experience in Groovy it is tempting to fall into your Groovy habits. Both languages look similar at a glance but are very different in detail. For instance I very often write def when defining a variable where it should be val or var. The fact that def is a valid keyword in Scala and is used to define methods is not helpful in this regard. There are so many other subtile differences that I can’t mention them here. Just be aware of that.

2. Use a decompiler
A decompiler can be very useful when learning Scala. Just compile the Scala class and then decompile it. This way you can easily see, what the Scala compiler is creating when using certain language features. I discovered a nice decompiler while doing this. It can be found here. The decompiler was key for solving the next issue.

3. Be careful with field level annotations
It is a great feature of Scala that you can use established Java frameworks and just replace the Java code with Scala. This way you can easily use Spring and the likes. I did that but had sudden problems with the Spring @Autowired annotation. I annotated the field like that:

var pollService: IPollService = _;

Spring was starting to complain about missing parameters on the annotated method. What?
Ok, I was aware that Scala generates corresponding methods for a field just like Groovy does. But what was the issue here? The Spring annotation is defined as field level and method level annotation. But when it is used on a method it has to be a setter which gets at least one parameter. The decompiler saved the day. It shows that Scala is applying the annotation three times. At the field, at the setter pollService_$eq() and the getter pollService(). The last causes the Spring exception. (For all Scala experts, the @BeanProperty annotation does not solve the problem)
The (ugly) workaround is to create the setter manually and annotate only this. Here is how:

var pollService: IPollService = _;

def setPollService(pollService: IPollService) = {this.pollService = pollService}

4. Switch of “Compile Scala files first” in IDEA

There is a small bug/inconvinience in the current Scala plugin of IntelliJ Idea. It occurs when you have a project with combined Java and Scala sources. Any Java class that is located in a test source folder will not compile. You will get an error message “ClassX is already defined as class ClassX”. To fix this you can simply change the Scala compiler settings. Go to Settings->Compiler->Scala and uncheck “Compile Scala Files First”. It is not perfect, as you might need to manually (Ctrl-Shift-F9) compile Scala sources that Java files depend on. But at least you can compile everything now.

5. Use Scalatest!
If you want to write tests in Scala try Scalatest. It shows perfectly what can be done in Scala. It enables different styles of testing like xUnit or BDD just by applying different traits. And it enables you to use TestNG in your Scala tests. This way you can just start tests in Scala as if they where Java, at least in Intellij Idea. Here is a small example how a Test can look like:

@Test def testCreateTopicPoll() = {
  val pollDto = preparePoll
  val pollId = pollService saveOrUpdateTopicPoll pollDto;
  pollId should not be null

Look at the last line. Isn’t that beautiful? This is real code. You would not need any comments to explain, what is under test here.

I can strongly recommend that you have a look into Scala. It is a very interesting language with some nice concepts. I hope that some of my lessons learned help you when doing your first steps. Then let me know what lessons you learned!