I needed to diff some OPML files today and came across this project. Even through it's 10 years old, it still mostly worked and the best part is it's a source distrib... :) The XML Diff and Patch GUI Tool Amol Kher Microsoft Corporation July 2004 Applies to: the XML Diff and Patch GUI tool Summary: This article shows how to use the XmlDiff class to compare two XML files and show these differences as an HTML document in a .NET Framework 1.1 application. The article also shows how to build a WinForms application for comparing XML files. Contents Introduction An Overview of the XML Diff and Patch API XML Diff and Patch Meets Winforms Working with XML DiffGrams Other Features of the XML Diff and Patch Tool Introduction There is no good command line tool that can be used to compare two XML files and view the differences. There is an online tool called XML Diff and Patch that's available on the GotDotNet website under the XML Tools section. For those who have not, you can find it at Microsoft XML Diff and Patch 1.0 [GD: yes, this link is busted... you can download it below]. It is a very convenient tool for those who want to compare the difference between two XML files. Comparing XML files is different from comparing regular text files because one wants to compare logical differences in the XML nodes not just differences in text. For example one may want to compare XML documents and ignore white space between elements, comments or processing instructions. The XML Diff and Patch tool allows one to perform such comparisons but it is primarily available as an online web application. We cannot take this tool and use it from command line. This article focuses on developing a command-line tool by reusing code from the XML Diff and Patch installation and samples. The tool works very similar to the WinDiff utility; it presents the differences in a separate window and highlights them. The XML Diff and Patch tool contains a library that contains an XmlDiff class, which can be used to compare two XML documents. The Compare method on this class takes two files and either returns true, if the files are equal, or generates an output file called an XML diffgram containing a list of differences between the files. The XmlDiff class can be supplied an options class XmlDiffOptions that can be used to set the various options for comparing files. ... Microsoft Downloads - XML Diff & Patch GUI Tool Winforms application that can be used to compare 2 XML files. Version: 1.0 Date Published: 7/14/2004 xmldiffgui.msi, 278 KB This code sample shows how to build a Windows forms application that utilizes the XML Diff & Patch library to show the difference between 2 XML files. There's a bug somewhere in it in that it was giving me an error when trying to load the HTML into an IE window, but that's likely a path thing. In the end, it executed and diff'd the two XML files. And since we do have the source... :) Another blast from the past is that this was available on the old GotDotNet site. I miss that site... :(

Since JBoss EAP 6.1 / AS 7.2.0 is modular and you can exclude what modules are visible to your webapp, you would expect it to be easy to ignore the built-in implementation of JAX-RS (Rest Easy 2.3.6) and use a custom one (3.0.6). However, sadly, this is not the case. You are stuck with what the official guide suggests, i.e.upgrading Rest Easy globally – provided that no other webapp running on the server becomes broken by the upgrade. This should be enough to exclude the built-in Rest Easy and be able to use a version included in the webapp: However it is far from working. This nearly does the job (though few of the exclusions might be unnecessary): However, only nearly. The problem is that the exclusion of javax.ws.rs.api has no effect. It seems as the core Java EE APIs cannot be excluded. Dead end. BTW, this are my final jax-rs related dependencies: // resteasyVersion = '3.0.6.Final' compile group: 'org.jboss.resteasy', name: 'jaxrs-api', version: resteasyVersion compile group: 'org.jboss.resteasy', name: 'resteasy-jaxrs', version: resteasyVersion compile group: 'org.jboss.resteasy', name: 'resteasy-jackson2-provider', version: resteasyVersion // JSONP compile group: 'org.jboss.resteasy', name: 'async-http-servlet-3.0', version: resteasyVersion // Required at runtime compile group: 'org.jboss.resteasy', name: 'resteasy-servlet-initializer', version: resteasyVersion // Required at runtime An approximate history of failed attempts I do not remember anymore exactly all the dead ends I went through but here is an approximate overview of the exceptions I got at deployment or runtime. java.lang.ClassNotFoundException: org.jboss.resteasy.plugins.server.servlet.HttpServlet30Dispatcher - fixed likely by adding org.jboss.resteasy:async-http-servlet-3.0:3.0.6.Final to the dependencies java.lang.ClassCastException: myapp.rs.RestApplication cannot be cast to javax.servlet.Servlet - fixed likely by adding org.jboss.resteasy:resteasy-servlet-initializer:3.0.6.Final to the dependencies java.lang.NoSuchMethodError: org.jboss.resteasy.spi.ResteasyProviderFactory.(Lorg/jboss/resteasy/spi/ResteasyProviderFactory;)V - fixed likely by adding more of the RestEasy/Jackson modules to the exclusion list java.lang.NoSuchMethodError: org.jboss.resteasy.specimpl.BuiltResponse.getHeaders()Ljavax/ws/rs/core/MultivaluedMap; - this is the ultimate one that cannot be fixed; the problem is that BuiltResponse from resteasy-jaxrs inherits from javax.ws.rs.core.Response however the version of this class from jaxrs-api-3.0.6.Final.jar is ignored in favour of Response from JAX-RS 1.1 from the javax.ws.rs.api module (/jboss-eap-6.1.0/modules/system/layers/base/javax/ws/rs/api/main/jboss-jaxrs-api_1.1_spec-1.0.1.Final-redhat-2.jar), which lacks the getHeaders method and, as mentioned, cannot be excluded. (Thanks to allprog for hinting at this confilct!) Conclusion The only way to use a newer JAX-RS is to upgrade the JBoss modules. If that would break some other webapps, you are stuck. Lessons learned: Application servers with the plenty of out-of-the-box, well-integrated (?) functionality seem attractive but when you run into conflicting libraries and classloading issues, their value diminishes rapidly. Starting with something simple that you control fully, such as Jettty, is perhaps in the long run a better solution. Also, running multiple webapps on the same server was perhaps smart in 2000 but is not worth the pain nowadays. We have plenty of disk space and memory so reuse of libraries is unimportant and the ability to manage global settings for all apps at one place has certainly better alternatives. Microservices FTW! Update: As Yannick has pointed out , the conclusion seems too general and unjustified. That is because I have arrived to it already before and this problem with JBoss serves only as another confirmation. Solution? Bill Burke has proposed a solution : I’ve lived through your pain and here’s a solution that works on AS7.1.1, EAP6.x, and Wildfly: https://github.com/keycloak/keycloak/blob/master/server/src/main/webapp/WEB-INF/jboss-deployment-structure.xml JBoss Modules don’t suck. The implicit dependencies do. The culprit is the “javaee.api” module which you have missing from your exclude. This module includes every single Java EE API. I haven’t tried, but I think if you reduce your excludes to just that module and the “resteasy” subsystem, it will work. ... FYI, I believe the “javaee.api” module problem is fixed in Wildfly so you won’t have to do the extra exclude.

At the end of last year I was playing around with running scheduled tasks to monitor a Neo4j cluster and one of the problems I ran into was that the monitoring would sometimes exit. I eventually realised that this was because a RuntimeException was being thrown inside the Runnable method and I wasn’t handling it. The following code demonstrates the problem: import java.util.ArrayList; import java.util.List; import java.util.concurrent.*; public class RunnableBlog { public static void main(String[] args) throws ExecutionException, InterruptedException { ScheduledExecutorService executor = Executors.newSingleThreadScheduledExecutor(); executor.scheduleAtFixedRate(new Runnable() { @Override public void run() { System.out.println(Thread.currentThread().getName() + " -> " + System.currentTimeMillis()); throw new RuntimeException("game over"); } }, 0, 1000, TimeUnit.MILLISECONDS).get(); System.out.println("exit"); executor.shutdown(); } } If we run that code we’ll see the RuntimeException but the executor won’t exit because the thread died without informing it: Exception in thread "main" pool-1-thread-1 -> 1391212558074 java.util.concurrent.ExecutionException: java.lang.RuntimeException: game over at java.util.concurrent.FutureTask$Sync.innerGet(FutureTask.java:252) at java.util.concurrent.FutureTask.get(FutureTask.java:111) at RunnableBlog.main(RunnableBlog.java:11) at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57) at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) at java.lang.reflect.Method.invoke(Method.java:601) at com.intellij.rt.execution.application.AppMain.main(AppMain.java:120) Caused by: java.lang.RuntimeException: game over at RunnableBlog$1.run(RunnableBlog.java:16) at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:471) at java.util.concurrent.FutureTask$Sync.innerRunAndReset(FutureTask.java:351) at java.util.concurrent.FutureTask.runAndReset(FutureTask.java:178) at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.access$301(ScheduledThreadPoolExecutor.java:178) at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.run(ScheduledThreadPoolExecutor.java:293) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1110) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:603) at java.lang.Thread.run(Thread.java:722) At the time I ended up adding a try catch block and printing the exception like so: public class RunnableBlog { public static void main(String[] args) throws ExecutionException, InterruptedException { ScheduledExecutorService executor = Executors.newSingleThreadScheduledExecutor(); executor.scheduleAtFixedRate(new Runnable() { @Override public void run() { try { System.out.println(Thread.currentThread().getName() + " -> " + System.currentTimeMillis()); throw new RuntimeException("game over"); } catch (RuntimeException e) { e.printStackTrace(); } } }, 0, 1000, TimeUnit.MILLISECONDS).get(); System.out.println("exit"); executor.shutdown(); } } This allows the exception to be recognised and as far as I can tell means that the thread executing the Runnable doesn’t die. java.lang.RuntimeException: game over pool-1-thread-1 -> 1391212651955 at RunnableBlog$1.run(RunnableBlog.java:16) at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:471) at java.util.concurrent.FutureTask$Sync.innerRunAndReset(FutureTask.java:351) at java.util.concurrent.FutureTask.runAndReset(FutureTask.java:178) at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.access$301(ScheduledThreadPoolExecutor.java:178) at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.run(ScheduledThreadPoolExecutor.java:293) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1110) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:603) at java.lang.Thread.run(Thread.java:722) pool-1-thread-1 -> 1391212652956 java.lang.RuntimeException: game over at RunnableBlog$1.run(RunnableBlog.java:16) at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:471) at java.util.concurrent.FutureTask$Sync.innerRunAndReset(FutureTask.java:351) at java.util.concurrent.FutureTask.runAndReset(FutureTask.java:178) at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.access$301(ScheduledThreadPoolExecutor.java:178) at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.run(ScheduledThreadPoolExecutor.java:293) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1110) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:603) at java.lang.Thread.run(Thread.java:722) pool-1-thread-1 -> 1391212653955 java.lang.RuntimeException: game over at RunnableBlog$1.run(RunnableBlog.java:16) at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:471) at java.util.concurrent.FutureTask$Sync.innerRunAndReset(FutureTask.java:351) at java.util.concurrent.FutureTask.runAndReset(FutureTask.java:178) at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.access$301(ScheduledThreadPoolExecutor.java:178) at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.run(ScheduledThreadPoolExecutor.java:293) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1110) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:603) at java.lang.Thread.run(Thread.java:722) This worked well and allowed me to keep monitoring the cluster. However, I recently started reading ‘Java Concurrency in Practice‘ (only 6 years after I bought it!) and realised that this might not be the proper way of handling the RuntimeException. public class RunnableBlog { public static void main(String[] args) throws ExecutionException, InterruptedException { ScheduledExecutorService executor = Executors.newSingleThreadScheduledExecutor(); executor.scheduleAtFixedRate(new Runnable() { @Override public void run() { try { System.out.println(Thread.currentThread().getName() + " -> " + System.currentTimeMillis()); throw new RuntimeException("game over"); } catch (RuntimeException e) { Thread t = Thread.currentThread(); t.getUncaughtExceptionHandler().uncaughtException(t, e); } } }, 0, 1000, TimeUnit.MILLISECONDS).get(); System.out.println("exit"); executor.shutdown(); } } I don’t see much difference between the two approaches so it’d be great if someone could explain to me why this approach is better than my previous one of catching the exception and printing the stack trace.

Before starting, you would need the Ultimate version of IDEA to run WebLogic Server (yes, the paid version or the 30 days trial). The Community edition of IDEA will not support Application Server deployment. I also assume you have already setup WebLogic Server and a user domain as per my previous blog instructions. So now let's setup the IDE to boost your development. Create a simple HelloWorld web application in IDEA. For your HelloWorld, you can go into the Project Settings > Artifacts, and add "web:war exploded" entry for your application. You will add this into your app server later. Ensure you have added the Application Server Views plugin with WebLogic Server. (It's under Settings > IDE Settings > Application Server) Click + and enter Name: WebLogic 12.1.2 WebLogic Home: C:\apps\wls12120 Back to your editor, select Menu: Run > Edit Configuration Click + and add "WebLogic Server" > Local Name: WLS On Server tab, ensure DomainPath is set: C:\apps\wls12120\mydomain On Deployment tab, select "web:war exploded" for your HelloWorld project. Click OK Now Menu: Run > "Run WLS" Your WebLogic Server should now start and running your web application inside. You may visit the browser on http://localhost:7001/web_war_exploded Some goodies with Intellij IDEA and WLS are: Redeploy WAR only without restarting server Deploy application in exploded mode and have IDE auto make and sync Debug application with server running within IDE Full control on server settings NOTE: As noted in previous blog, if you do not set MW_HOME as system variable, then you must add this in IDEA's Run Configuration. Or you edit your "mydomain/bin/startWebLogic.cmd" and"stopWebLogic.cmd" scripts directly.

Learn how to convert XML objects to Java, and vice versa.

Within this blog post I describe how you can use AspectJ to automatically translate one type of exception to another. The problem Sometimes we are in situations where we have to convert an exception (often thrown by a third-party library) to another type of exception. Assume you are using a persistence framework like hibernate and you do not want to leak hibernate specific exceptions out of a certain application layer. Maybe you are using more than one persistence technology and you want to wrap technology specific exceptions into a common base exception. In such situations, one can end with code like this: public class MyRepository { public Object getSomeData() { try { // assume hibernate is used to access some data } catch(HibernateException e) { // wrap hibernate specific exception into a general DataAccessException throw new DataAccessException(e); } } } Of course this becomes ugly if you have to do this every time you access a certain framework. The AspectJ way AspectJ is an aspect oriented programming (AOP) extension for Java. With AspectJ we can define Cross-cutting concerns that take care of the exception translation process for us. To get started we first have to add the AspectJ dependency to our project: org.aspectj aspectjrt 1.7.4 Next we have to set up ajc, the compiler and bytecode weaver for AspectJ. This step depends on the developing environment you are using, so I will not go into details here. Eclipse users should have a look at theAspectJ Development Tools (AJDT) for Eclipse. IntelliJ IDEA users should make sure the AspectJ plugin is enabled. There is also an AspectJ Maven plugin available (check this pom.xml for an example configuration). Now let's define our aspect using AspectJ annotations: @Aspect public class ExceptionTranslationAspect { @Around("execution(* com.mscharhag.exceptiontranslation.repository..*(..))") public Object translateToDataAccessException(ProceedingJoinPoint pjp) throws Throwable { try { return pjp.proceed(); } catch (HibernateException e) { throw new DataAccessException(e); } } } Using the @Aspect annotation we can declare a new aspect. Within this aspect we use the @Aroundannotation to define an advice that is always executed if the passed pointcut is matched. Here, the pointcut execution(* com.mscharhag.exceptiontranslation.repository..*(..)) tells AspectJ to call translateToDataAccessException() every time a method of a class inside thecom.mscharhag.exceptiontranslation.repository package is executed. Within translateToDataAccessException() we can use the passed ProceedingJoinPoint object to proceed the method execution we intercepted. In this example we just add a try/catch block around the method execution. Using the ProceedingJoinPoint instance we could also do more interesting things like analyzing the method signature using pjp.getSignature() or accessing method parameters withpjp.getArgs(). We can now remove the try/catch block from the example repository implementation shown above and use a simple test to verify our aspect is working: public class MyRepositoryTest { private MyRepository repository = new MyRepository(); @Test(expected = DataAccessException.class) public void testExceptionTranslation() { this.repository.getSomeData(); } } Conclusion Using AspectJ we can easily automate the conversion of Java runtime exceptions. This simplifies our code by removing try/catch blocks that would otherwise be required for exception translation. You can find the full source of the example project on GitHub.

Security has become a great topic of discussion in the last few years due to the recent releasing of documents from Edward Snowden and the explosion of hacking against online commerce stores like JC Penny, Sony andTarget. While this post will not give you all of the tools to help prevent the use of illegally sourced data, this post will provide a starting point for building a set of tools and tactics that will help prevent the use of data by other parties. This post will show how to adopt AES encryption for strings in a Java environment. It will talk about creating AES keys and storing AES keys in a JCEKS keystore format. A working example of the code in this blog is located athttps://github.com/mike-ensor/aes-256-encryption-utility It is recommended to read each section in order because each section builds off of the previous section, however, this you might want to just jump quickly jump to a particular section. Setup - Setup and create keys with keytool Encrypt - Encrypt messages using byte[] keys Decrypt - Decrypt messages using same IV and key from encryption Obtain Keys from Keystore - Obtain keys from keystore via an alias What is JCEKS? JCEKS stands for Java Cryptography Extension KeyStore and it is an alternative keystore format for the Java platform. Storing keys in a KeyStore can be a measure to prevent your encryption keys from being exposed. Java KeyStores securely contain individual certificates and keys that can be referenced by an alias for use in a Java program. Java KeyStores are often created using the "keytool" provided with the Java JDK. NOTE: It is strongly recommended to create a complex passcode for KeyStores to keep the contents secure. The KeyStore is a file that is considered to be public, but it is advisable to not give easy access to the file. Setup All encryption is governed by laws of each country and often have restrictions on the strength of the encryption. One example is that in the United States, all encryption over 128-bit is restricted if the data is traveling outside of the boarder. By default, the Java JCE implements a strength policy to comply with these rules. If a stronger encryption is preferred, and adheres to the laws of the country, then the JCE needs to have access to the stronger encryption policy. Very plainly put, if you are planning on using AES 256-bit encryption, you must install theUnlimited Strength Jurisdiction Policy Files. Without the policies in place, 256-bit encryption is not possible. Installation of JCE Unlimited Strength Policy This post is focusing on the keys rather than the installation and setup of the JCE. The installation is rather simple with explicit instructions found here (NOTE: this is for JDK7, if using a different JDK, search for the appropriate JCE policy files). Keystore Setup When using the KeyTool manipulating a keystore is simple. Keystores must be created with a link to a new key or during an import of an existing keystore. In order to create a new key and keystore simply type: keytool -genseckey -keystore aes-keystore.jck -storetype jceks -storepass mystorepass -keyalg AES -keysize 256 -alias jceksaes -keypass mykeypass Important Flags In the example above here are the explanations for the keytool's parameters: Keystore Parameters genseckey Generate SecretKey. This is the flag indicating the creation of a synchronous key which will become our AES key keystore Location of the keystore. If the keystore does not exist, the tool will create a new store. Paths can be relative or absolute but must be local storetype this is the type of store (JCE, PK12, JCEKS, etc). JCEKS is used to store symmetric keys (AES) not contained within a certificate. storepass password related to the keystore. Highly recommended to create a strong passphrase for the keystore Key Parameters keyalg algorithm used to create the key (AES/DES/etc) keysize size of the key (128, 192, 256, etc) alias alias given to the newly created key in which to reference when using the key keypass password protecting the use of the key Encrypt As it pertains to data in Java and at the most basic level, encryption is an algorithmic process used to programmatically obfuscate data through a reversible process where both parties have information pertaining to the data and how the algorithm is used. In Java encryption, this involves the use of a Cipher. A Cipher object in the JCE is a generic entry point into the encryption provider typically selected by the algorithm. This example uses the default Java provider but would also work with Bouncy Castle. Generating a Cipher object Obtaining an instance of Cipher is rather easy and the same process is required for both encryption and decryption. (NOTE: Encryption and Decryption require the same algorithm but do not require the same object instance) Cipher cipher = Cipher.getInstance("AES/CBC/PKCS5Padding"); Once we have an instance of the Cipher, we can encrypt and decrypt data according to the algorithm. Often the algorithm will require additional pieces of information in order to encrypt/decrypt data. In this example, we will need to pass the algorithm the bytes containing the key and an initial vector (explained below). Initialization In order to use the Cipher, we must first initialize the cipher. This step is necessary so we can provide additional information to the algorithm like the AES key and the Initial Vector (aka IV). cipher.init(Cipher.ENCRYPT_MODE, secretKeySpecification, initialVector); Parameters The SecretKeySpecification is an object containing a reference to the bytes forming the AES key. The AES key is nothing more than a specific sized byte array (256-bit for AES 256 or 32 bytes) that is generated by the keytool(see above). Alternative Parameteters There are multiple methods to create keys such as a hash including a salt, username and password (or similar). This method would utilize a SHA1 hash of the concatenated strings, convert to bytes and then truncate result to the desired size. This post will not show the generation of a key using this method or the use of a PBE key method using a password and salt. The password and/or salt usage for the keys is handled by the keytool using the inputs during the creation of new keys. Initialization Vector The AES algorithm also requires a second parameter called the Initialiation Vector. The IV is used in the process to randomize the encrypted message and prevent the key from easy guessing. The IV is considered a publicly shared piece of information, but again, it is not recommended to openly share the information (for example, it wouldn't be wise to post it on your company's website). When encrypting a message, it is not uncommon to prepend the message with the IV since the IV will be a set/known size based on the algorithm. NOTE: the AES algorithm will output the same result if using the same IV, key and message. It is recommended that the IV be randomly created each time an encryption takes place. With the newly initialized Cipher, encrypting a message is simple. Simply call: byte[] encryptedMessageInBytes = Cipher.doFinal((message.getBytes("UTF-8")); String base64EncodedEncryptedMsg = BaseEncoding.base64().encode(encryptedMessageInBytes); String base32EncodedEncryptedMsg = BaseEncoding.base32().encode(encryptedMessageInBytes); Encoding Results Byte arrays are difficult to visualize since they often do not form characters in any charset. The best recommendation to solve this is to represent the bytes in HEX (base-16), Double HEX (base-32) or Base64 format. If the message will be passed via a URL or POST parameter, be sure to use a web-safe Base64 encoding. Google Guava library provides a excellent BaseEncoding utility. NOTE: Remember to decode the encoded message before decrypting. Decrypt Decrypting a message is almost a reverse of the encryption process with a few exceptions. Decryption requires a known initialization vector as a parameter unlike the encryption process generating a random IV. Decryption When decrypting, obtain a cipher object with the same process as the encryption method. The Cipher object will need to utilize the exact same algorithm including the method and padding selections. Once the code has obtained a reference to a Cipher object, the next step is to initialize the cipher for decryption and pass in a reference to a key and the initialization vector. // key is the same byte[] key used in encryption SecretKeySpec secretKeySpecification = new SecretKeySpec(key, "AES"); cipher.init(Cipher.DECRYPT_MODE, secretKeySpecification, initialVector); NOTE: The key is stored in the keystore and obtained by the use of an alias. See below for details on obtaining keys from a keystore Once the cipher has been provided the key, IV and initialized for decryption, the cipher is ready to perform the decryption. byte[] encryptedTextBytes = BaseEncoding.base64().decode(message); byte[] decryptedTextBytes = cipher.doFinal(encryptedTextBytes); String origMessage = new String(decryptedTextBytes); Strategies to keep IV The IV used to encrypt the message is important to decrypting the message therefore the question is raised, how do they stay together. One solution is to Base Encode (see above) the IV and prepend it to the encrypted and encoded message: Base64UrlSafe(myIv) + delimiter + Base64UrlSafe(encryptedMessage). Other possible solutions might be contextual such as including an attribute in an XML file with the IV and one for the alias to the key used. Obtain Key from Keystore The beginning of this post has shown how easy it is to create new AES-256 keys that reference an alias inside of a keystore database. The post then continues on how to encrypt and decrypt a message given a key, but has yet shown how to obtain a reference to the key in a keystore. Solution // for clarity, ignoring exceptions and failures InputStream keystoreStream = new FileInputStream(keystoreLocation); KeyStore keystore = KeyStore.getInstance("JCEKS"); keystore.load(keystoreStream, keystorePass.toCharArray()); if (!keystore.containsAlias(alias)) { thrownew RuntimeException("Alias for key not found"); } Key key = keystore.getKey(alias, keyPass.toCharArray()); Parameters keystoreLocation String - Location to local keystore file location keypass String - Password used when creating or modifying the keystore file with keytool (see above) alias String - Alias used when creating new key with keytool (see above) Conclusion This post has shown how to encrypt and decrypt string based messages using the AES-256 encryption algorithm. The keys to encrypt and decrypt these messages are held inside of a JCEKS formatted KeyStore database created using the JDK provided "keytool" utility. The examples in this post should be considered a solid start to encrypting/decrypting symmetric keys such as AES. This should not be considered the only line of defense when encrypting messages, for example key rotation. Key rotation is a method to mitigate risks in the event of a data breach. If an intruder obtains data and manages to hack a single key, the data contained in multiple files should have used several keys to encrypt the data thus bringing down risk of a total exposure loss. All of the examples in this blog post have been condensed into a simple tool allowing for the viewing of keys inside of a keystore, an operation that is not supported out of the box by the JDK keytool. Each aspect of the steps and topics outlined in this post are available at: https://github.com/mike-ensor/aes-256-encryption-utility. NOTE: The examples, sample code and any reference is to be used at the sole implementers risk and there is no implied warranty or liability, you assume all risks.

In this post I would like to describe how to build a fat JAR using NetBeans IDE.

The Spring Expression Language (SpEL) is a powerful expression language that supports querying, manipulating as well as evaluating logical and mathematical expressions.

Introduction When using Spring to asynchronously execute pieces of your code you typically use the @Async annotation on your Spring @Components methods. When using the @Async annotation Spring will use AOP (Aspect Oriented Programming) to wrap your call in a Runnable. This Runnable will then be scheduled for execution on a TaskExecutor. Exception Handling Spring comes with a number of pre-packaged TaskExecutors which are documented in the Spring documentation here. In practice you will likely use the ThreadPoolTaskExecutor or the SimpleAsyncTaskExecutor. When doing so you might at times wonder why a task has not been executed. This happens when an exception occurs inside the method you are trying to execute asynchronous. The aforementioned task executors do not handle the exceptions so the execution fails silently. This problem can be solved by implementing your own AsyncTaskExecutor which handles the exceptions by logging them (or in any other way you wish). Bellow you'll find an example implementation of such a AsyncTaskExecutor. package nl.jborsje.blog.examples; import java.util.concurrent.Callable; import java.util.concurrent.Future; import org.springframework.core.task.AsyncTaskExecutor; import org.springframework.scheduling.concurrent.ThreadPoolTaskExecutor; public class ExceptionHandlingAsyncTaskExecutor implements AsyncTaskExecutor { private AsyncTaskExecutor executor; public ExceptionHandlingAsyncTaskExecutor(AsyncTaskExecutor executor) { this.executor = executor; } public void execute(Runnable task) { executor.execute(createWrappedRunnable(task)); } public void execute(Runnable task, long startTimeout) { executor.execute(createWrappedRunnable(task), startTimeout); } public Future submit(Runnable task) { return executor.submit(createWrappedRunnable(task)); } public Future submit(final Callable task) { return executor.submit(createCallable(task)); } private Callable createCallable(final Callable task) { return new Callable() { public T call() throws Exception { try { return task.call(); } catch (Exception ex) { handle(ex); throw ex; } } }; } private Runnable createWrappedRunnable(final Runnable task) { return new Runnable() { public void run() { try { task.run(); } catch (Exception ex) { handle(ex); } } }; } private void handle(Exception ex) { System.err.println("Error during @Async execution: " + ex); } } This task executor decorates another task executor and wraps all Runnables and Callables in versions which handle the exception. In order to be able to use this task executor it has to be configured in the Spring application context as a managed bean and it has to be passed the real executor (the one that does the actual work) in its constructor. An example of such a configuration can be found bellow. JUnit testing In the application context used for JUnit testing Spring beans the asynchronous execution of methods can be cumbersome. You typically want to validate the inner workings of your methods not Springs asynchronicity. To achieve this you can use the SyncTaskExecutor provided by Spring. This task executor runs the tasks it is given immediately on the thread that adds the task instead of using a thread pool and running the tasks asynchronous. This task executor is configured in the test scope application context as follows.

This technical tip shows how .NET developers can export Microsoft Visio diagram to XML inside their own applications using Aspose.Diagram for .NET. Aspose.Diagram for .NET lets you export diagrams to a variety of formats: image formats, HTML, SVG, SWF and XML formats: VDX defines an XML diagram. VTX defines an XML template. VSX defines an XML stencil. The Diagram class' constructors read a diagram and the Save method is used to save, or export, a diagram in a different file format. The code snippets in this article show how to use the Save method to save a Visio file to VDX, VTX and VSX. Exporting VSD to VDX VDX is a schema-based XML file format that lets you save diagrams in a format that products other than Microsoft Visio can read. It's a useful format for transferring diagrams between software applications and retaining editable data. To export a VSD diagram to VDX first create an instance of the Diagram class and call the Diagram class' Save method to write the Visio drawing file to VDX. Exporting from VSD to VSX VSX is an XML format for defining stencils, the basic objects from which a diagram is built up. When a Visio file is converted to VSX, only the stencils are exported. To export a VSD diagram to VSX first you need to create an instance of the Diagram class and then call the Diagram class' Save method to write the Visio drawing file to VSX. //The Sample code shows how to export VSD to VDX //[C# Sample] //Call the diagram constructor to load diagram from a VSD file Diagram diagram = new Diagram("D:\\Drawing1.vsd"); this.Response.Clear(); this.Response.ClearHeaders(); this.Response.ContentType = "application/vnd.ms-visio"; this.Response.AppendHeader("Content-Disposition", "attachment; filename=Diagram.vdx"); this.Response.Flush(); System.IO.Stream vdxStream = this.Response.OutputStream; //Save input VSD as VDX diagram.Save(vdxStream, SaveFileFormat.VDX); this.Response.End(); //[VB.NET Code Sample] 'Call the diagram constructor to load diagram from a VSD file Dim diagram As New Diagram("D:\Drawing1.vsd") Me.Response.Clear() Me.Response.ClearHeaders() Me.Response.ContentType = "application/vnd.ms-visio" Me.Response.AppendHeader("Content-Disposition", "attachment; filename=Diagram.vdx") Me.Response.Flush() Dim vdxStream As System.IO.Stream = Me.Response.OutputStream 'Save inpupt VSD as VDX diagram.Save(vdxStream, SaveFileFormat.VDX) Me.Response.End() //The Sample code shows how to export VSD to VSX format. [C# Code Sample] // Call the diagram constructor to load diagram from a VSD file Diagram diagram = new Diagram("D:\\Drawing1.vsd"); this.Response.Clear(); this.Response.ClearHeaders(); this.Response.ContentType = "application/vnd.ms-visio"; this.Response.AppendHeader("Content-Disposition", "attachment; filename=Diagram.vsx"); this.Response.Flush(); System.IO.Stream vsxStream = this.Response.OutputStream; //Save input VSD as VSX diagram.Save(vsxStream, SaveFileFormat.VSX); this.Response.End() //[VB.NET Code Sample] 'Call the diagram constructor to load diagram from a VSD file Dim diagram As New Diagram("D:\Drawing1.vsd") Me.Response.Clear() Me.Response.ClearHeaders() Me.Response.ContentType = "application/vnd.ms-visio" Me.Response.AppendHeader("Content-Disposition", "attachment; filename=Diagram.vsx") Me.Response.Flush() Dim vsxStream As System.IO.Stream = Me.Response.OutputStream 'Save input VSD as VSX diagram.Save(vsxStream, SaveFileFormat.VSX) Me.Response.End()

Learn about using Mockito to create autowired fields.

Java SE 7 type inference I taught an introductory Java session on generics, and of course demonstrated the shorthand introduced in Java SE 7 for instantiating an instance of a generic type: // Java SE 6 List l = new ArrayList(); // Java SE 7 List l = new ArrayList<>(); This inference is very friendly, especially when we get into more complex collections: // This Map> m = new HashMap>(); // Becomes Map> m = new HashMap<>(); Not only the key and value type of the map, but the type of object stored in the collection used for the value type can be inferred. Of course, sometimes this inference breaks down. It so happens I ran across an interesting example of this. Imagine populating a set from a list, so as to speed up random access and remove duplicates. Something like this will work: List list = ...; // From somewhere Set nodup = new HashSet<>(list); However, this runs into trouble if the list could be null. The HashSetconstructor will not just return an empty set but will throwNullPointerException. So we need to guard against null here. Of course, like all good programmers, we seize the chance to use a ternary operator because ternary operators are cool. List list = ...; // From somewhere Set nodup = (null == list) ? new HashSet<>() : new HashSet<>(list); And here’s where inference breaks down. Because this is no longer a simple assignment, the statement new HashSet<>() can no longer use the left hand side in order to infer the type. As a result, we get that friendly error message, “Type mismatch: cannot convert from HashSet to Set”. What’s especially interesting is that inference breaks down even though the compiler knows that an object of typeSet is what is needed in order to gain agreement of types. The rules for inference are written to be conservative by doing nothing when an invalid inference might cause issues, while the compiler’s type checking is also conservative in what it considers to be matching types. Also interesting is that we only get that error message for the new HashSet<>(). The statement new HashSet<>(list) that uses the list to populate the set works just fine. This is because the inference is completed using the listparameter. Here’s the constructor: public class HashSet extends ... implements ... { ... public HashSet(Collection c) { ... } ... } The List that we pass in gets captured as Collection and this means that E is bound to String, so all is well. As a result, we wind up with the perfectly valid, if a little funny looking: List list = ...; // From somewhere Set nodup = (null == list) ? new HashSet() : new HashSet<>(list); Of course, I imagine most Java programmers do what I do, which is try to use the shortcut and then add the type parameter when the compiler complains. Following the rule about not meddling in the affairs of compilers (subtle; quick to anger), normally I would just fix it without trying very hard to understand why the compiler liked or didn’t like things done in a certain way. But this one was such a strange case I figured it was worth a longer look.

Note: the following article is purely theoretical. I don’t know if it fits a real-life use-case, but the point is just too good to miss Java’s List sorting has two flavors: one follows the natural ordering of collection objects, the other requires an external comparator. In the first case, Java assumes objects are naturally ordered. From a code point of view, this means types of objects in the list must implement the Comparable interface. For example, such is the case for String and Date objects. If this is not the case, or if objects cannot be compared to one another (because perhapsthey belong to incompatible type as both String and Date). The second case happens when the natural order is not relevant and a comparator has to be implemented. For example, strings are sorted according to the character value, meaning case is relevant. When the use-case requires a case-insensitive sort, the following code will do (using Java 8 enhanced syntax): Collections.sort(strings, (s1, s2) -> s1.compareToIgnoreCase(s2)); The Comparable approach is intrinsic, the Comparator extrinsic; the former case rigid, the latter adaptable to the required context. What applies to lists, however, cannot be applied to Java sets. Objects added to sets have to define equals() and hashCode() and both properties (one could say that it’s only one since they are so coupled together) are intrinsic. There is no way to define an equality that can change depending on the context in the JDK. Enters Trove: The Trove library provide primitive collections with similar APIs to the above. This gap in the JDK is often addressed by using the “wrapper” classes (java.lang.Integer, java.lang.Float, etc.) with Object-based collections. For most applications, however, collections which store primitives directly will require less space and yield significant performance gains. Let’s be frank, Trove is under-documented. However, it offers what is missing regarding extrinsic equality: it provides a dedicated set implementation, that accepts its own extrinsic equality abstraction. A sample code would look like that: HashingStrategy strategy = new MyCustomStrategy(); Set dates = new TCustomHashSet(strategy); A big bonus for using Trove is performance, though: It probably is the first argument to use Trove I never tested that in any context To go further, just have a look at Trove for yourself.

As follow up to previous posts covering JMS, this post will delve into more depth on Spring's CachingConnectionFactory. Spring provides two implementations of the javax.jms.ConnectionFactory interface, namely, the SingleConnectionFactory and the CachingConnectionFactory. The SingleConnectionFactory returns as you might expect the same single connection upon all calls to the createConnection() method. This is fine for certain scenarios and applications but the CachingConnectionFactory provides a more performant and scalable solution. By default, a single session is cached so for a multi threaded application you would set the sessionCacheSize to be a more suitable number although this number wouldn't reflect the true number of sessions cached as this figure refers to the size of cache per session acknowledgement type eg AUTO_ACKNOWLEDGE, CLIENT_ACKNOWLEDGE, DUPS_OK_ACKNOWLEDGE and SESSION_TRANSACTED. By default, the CachingConnectionFactory will cache the Message Producers and Message Consumers for every session. As an aside the Message Consumers are cached using keys which include the JMS selector so the more fine grained the message filter the more Message Consumers there would be, and Message Consumers aren't closed until the session is closed and removed from the pool. An alternative is to use a Listener Container for consuming messages. Also to be noted is that on creating a CachingConnectionFactory instance, the reconnect on exception flag is set to be true. This should mean that the onException method on the default ExceptionListener class gets called which will reset the connections. You can also override the default exception listener with your own implementation. The below snippet of XML shows a simple configuration of a CachingConnectionFactory:

gaurav gupta is a senior software engineer working on the bpmn workflow engine. he's created several plugins for netbeans ide, notably the js css minify compress plugin ( here ) and the jbpmn plugin, which is the topic of this interview. the plugin provides netbeans ide tools for working with business process modeling notation (bpmn). the plugin can be accessed here, including for netbeans ide 7.4 and 8.0 beta, together with screencasts and tutorials: http://plugins.netbeans.org/plugin/50735/jbpmn hi, gaurav, why did you create the bpmn plugin? business process modeling notation is an increasingly important standard for process modelling and has enjoyed high levels of adoption, so the specific intent of the jbpmn plugin is to create a bpmn modeler that supports the complete bpmn specification and can be integrated by multiple bpmn engine vendors into netbeans ide. as a result, different bpmn engine vendors will not need to create separate bpmn modelers for netbeans ide. another reason i created this plugin was to bring the netbeans community closer to the bpm community because bpmn has become the de-facto standard for business process modeling. also, when we talk about "netbeans vs eclipse", the basic conclusion is that netbeans is much more intuitive and easy to use, while eclipse has a wider range of third-party plugins support from more companies. in that context, i have taken this initiative to create the bpm plugin to help the netbeans community. what would you consider to be the best features of the bpmn plugin? the jbpmn nb modeler is a graphical modelling tool which allows the creation and editing of bpmn process diagrams. it provides debugging supports for jbpm 5.0. it is bpmn engine vendor neutral, can be used by any vendor or generated xml, and can run on any bpmn engine which adopts the bpmn 2.0 standard. here's another screenshot: what are the future development plans for this plugin? to cover the complete bpmn ssecification with user friendly gui and properties support. jbpmn currently supports only the bpmn process model, it will also support the bpmn conversation model. it will also provide support to extends the modeller with your own palette elements, properties, and generated xml tags. it will provides debugging supports for jbpm 6.0, activities, and also extensions so that any bpmn engine vendor can integrate debugging functionality within jbpmn. it will also provide a netbeans modeler platform api, which any business modeller can use to easily build solutions such as a bpmn conversation model.

Learn how to set up a four node Hadoop cluster using AWS EC2, PuTTy(gen), and WinSCP.

i’ve been pushing this branching model for something like 14 years now. it’s nice to see facebook say a little more about their trunk based development . of course they’re not doing it because they read anything i wrote, as the practice isn’t mine, it’s been hanging around in the industry for many years, but always as bridesmaid so to speak. if not trunk, what? mainline? mainline as popularized by clearcase is what we’re trying to kill. at least historically. it’s very different to trunk based development, and even having vastly improved merge tools doesn’t make it better – you still risk regressions, and huge nerves around ordering of releases. clearcase’s best-practices also foisted a ‘many repos’ (vobs) on teams using it, and that courted the whole conway’s law prophesy. i mentioned conway’s law before in scaling trunk based development and it concerns undue self-importance of teams around arbitrary separations. multiple small repos for a dvcs ? there is a great statement by a reddit user in the programming section of reddit, in conjunction with the facebook announcement: comment ref or all comments this redditor is right, there’s a lack of atomicity around a many-repos design, that stymies bisect. it could be that git subtrees (not submodules) are a way of getting that back (thanks @chris_stevenson on a back channel). there’s also a real problem moving code easily between repos (with history) though @offbytwo (back channel again) points out that subtrees carefully used can help do that. trunk at google vs facebook tuesday’s announcement was from facebook, and to give some balance, there’s deeper info on google’s trunk design in: google’s scaled trunk based development . subsetting the trunk for checkouts tl;dr: different google have many thousands of buildable and deployable things, which have very different release schedules. facebook don’t as they substantially have the php web-app, and apps for ios and android in different repos. well at least the main php web-app is in the mercurial trunk they talked about on tuesday. i’m not sure how the ios and android apps are managed, but at least the android one is outside the main trunk. google subset their trunk. i posted about that on monday . in that article i pointed out that the checkout can grow (or shrink) depending on the nature of the change being undertaken. it’s very different to a multiple-small-repos design. facebook don’t subset their trunk on checkout, as they do not need to; the head revisions of everything in that trunk are not big enough for a c: drive or ide to buckle. there’s also no compile stage for php , for regular development work. maximized sharing of code tl;dr: the same code is shared using globbed directories within the source tree. it’s shared as source files, in situ, rather than classes in a jar (or equivalent). refactoring tl;dr: the same developers take on refactorings where appropriate. sure it means a bigger atomic commit, but knowing all the affected source is in front of you as you do the refactoring is comforting. at least, knowing that if intellij (or eclipse, etc) completes the refactoring there’s a very strong possibility that the build will stay green, and that you’re only going to have a slight impact on other people’s working copy, and only if they are concurrently editing the same files. bigger refactoring probably still require a warning email. super tooling of the build phase tl;dr: the same google have what amounts to a super-computer doing the compilation for them (all languages that are compiled). all developers and all ci daemons leverage it. and by effective super-computer, i mean previous-compiled bits and pieces are pulled out of an internal cloud-map-thing for source permutations that have been compiled before. the distributed hashmap is possibly lru centric rather that everything forever. facebook don’t have that big hashmap of recently compiled bits and pieces, but they do have hiphop in the toolchain (originally a php to c++ compiler) which is interesting because at face value php is an interpreted language and ‘compile’ makes no sense. hiphop was created to reduce the server footprint and requirements for production deployments, while still being 100% functionally identical to the interpreted php app. it’s also faster in production. more recently hiphop became a virtual machine. it continues to be incrementally improved. like google, facebook can measure cost-benefit of continued work on it (prod rack space & prod electricity vs developer salaries). source-control weapons of choice tl;dr: different google use perforce for their trunk (with additional tooling), and many (but not all) developers use git on their local workstation to gain local-branching with an inhouse developed bridge for interop with perforce. facebook uses mercurial with additional tooling for the central server/repo. it’s unclear whether developers, by habit, exist with the mercurial client software or use git which can interop with mercurial backends. both google and facebook do trunk based development of course. branches & merge pain tl;dr: the same they don’t have merge pain, because as a rule developers are not merging to/from branches. at least up to the central repo’s server they are not. on workstations, developers may be merging to/from local branches, and rebasing when the push something that’s “done” back to the central repo. release engineers might cherry-pick defect fixes from time to time, but regular developers are not merging (you should not count to-working-copy merges) eating own dog-food tl;dr: mostly different all staff at facebook use a not-live-yet version of the web-app for all of their communication, documentation, management etc. if there’s a bug everyone feels it – though selenium2 functional tests and zillions of unit-tests guard against that happening too often. google has too many different apps for the team making each to be said to be a daily user of it. for example the adsense developer may use a dog-food version of gmail, but they are making adsense, so are hardly hurting themselves as they are not minute by minute using the interface as part of their regular existence at google. code review tl;dr: same both google and facebook insist on code reviews before the commit is accepted into the remote repo’s trunk for all others to use. there’s no mechanism of code review that’s more efficient or effective. google back in 2009 were pivoting incoming changes to the trunk around the code-review process managed by mondrian. i wrote about that in “continuous review #1” in december . i think they are unchanged in that respect: developers actively push their commit after a code review has been completed. facebook have just flipped to mercurial (from subversion). in the article linked to at the top of the page, facebook have not mentioned “pull request” or “patch queue”, or indeed “code review”. the article was mostly about speed, robustness and scale. i suspect they are sitting within the semantics of mercurials patch-queue processing though, although assigning a bot to it rather than a human. update: simon stewart pinged me and reminded me that they use (and made) phabricator. he spoke about it in a mobile@scale presentation, and that video is here . in the video he says the review is queue based now, but that they experimenting with landing the change sets into the master now. the video is from november, and was for the android + ios platforms, but it is likely to be used today for the main trunk for the php web-app. automated testing tl;dr: same heavy reliance on unit tests (not necessarily made in a tdd style). later in an build pipeline, selenium2 tests (for web-apps at least) kick in to guard the functional quality of deployed app. manual qa tl;dr: mostly the same both companies have progressively moved way from manual qa and dedicated testing professionals, towards developers testing their own stuff at discrete moments (note the dog-food item above too). prod release frequency tl;dr: it varies. facebook for the main web app, are twice a day presently (at least on weekdays). i published info on that at the start of last year. google have many apps with different release schedules, and some are “many times a day”, while others are “planned releases every few weeks”. many are in between. prod db deployment tl;dr: mostly the same database (or equivalent) table shapes (or equivalent) are designed to be forwards/backwards compatible as far as possible. pull requests as part of workflow tl;dr: same etsy, github, and other high throughput organizations are trunking by some definition, but using pull-requests to merge in things being done. it has different obligations if done, but google and facebook are not doing this in their trunks – they both essentially push (after review). refer the ‘code review’ section above. common code ownership tl;dr: the same you can commit to any part of the source tree, provided it passed a fair code review. notional owners of directories within the source tree take a boy-scout pledge to do their best with unsolicited incoming change-lists. there are strong permissions in the google perforce implementation, but the pledge means that contributions are not often rejected if the merit is there. build is ever broken tl;dr: the same almost never. directionality of merge for prod bug fixes tl;dr: the same trunk receives the defect fix, it gets cherry picked to the release branch. the release branch might have been made from a tag, if it didn’t exist before. binary dependencies tl;dr: the same checked into source-control without version suffixing (harmonized versions across all apps). e.g. – log4j.jar rather than log4j-1.2.8.jar.

One of the great things about git is how fast it is. You can create a new branch, or switch to another branch, almost as fast as you can type the command. This tends to lower the impedance of branching. As a result, many individuals and teams will naturally converge on a process where they create many, many branches. If you’re like me, you may have 30 branches at any given time. This can make viewing all the branches unwieldy. Once I week or so, I would go on a branch deletion spree by manually copying and pasting multiple branch names into a git branch -D statement. The basic use case is that you want to delete any branches that are already merged into master. Here is a python script that automated just that. from subprocess import check_output import sys def get_merged_branches(): ''' a list of merged branches, not couting the current branch or master ''' raw_results = check_output('git branch --merged upstream/master', shell=True) return [b.strip() for b in raw_results.split('\n') if b.strip() and not b.startswith('*') and b.strip() != 'master'] def delete_branch(branch): return check_output('git branch -D %s' % branch, shell=True).strip() if __name__ == '__main__': dry_run = '--confirm' not in sys.argv for branch in get_merged_branches(): if dry_run: print branch else: print delete_branch(branch) if dry_run: print '*****************************************************************' print 'Did not actually delete anything yet, pass in --confirm to delete' print '*****************************************************************' To print the branches that would be deleted, just execute python delete_merged_branches.py. To actually delete the branches, execute python delete_merged_branches.py --confirm.

Nginx-Clojure is a Nginx module for embedding Clojure or Java programs, typically those Ring based handlers.