API 4 Future

Many ideas are excellent on paper. However, people often lack the knowledge of how to implement brilliant concepts into their everyday work. This short workshop aims to bridge the gap between theory and practice and demonstrates the steps needed to achieve a stable API in the long term.

(c) 2021 Marco Schulz, Java PRO Ausgabe 1, S.31-34

When developing commercial software, many people involved often don’t realize that the application will be in use for a long time. Since our world is constantly changing, it’s easy to foresee that the application will require major and minor changes over the years. The project becomes a real challenge when the application to be extended is not isolated, but communicates with other system components. This means that in most cases, the users of the application also have to be adapted. A single stone quickly becomes an avalanche. With good avalanche protection, the situation can still be controlled. However, this is only possible if you consider that the measures described below are solely intended for prevention. But once the violence has been unleashed, there is little that can be done to stop it. So let’s first clarify what an API is.

A Matter of Negotiation

A software project consists of various components, each with its own specialized tasks. The most important are source code, configuration, and persistence. We’ll be focusing primarily on the source code area. I’m not revealing anything new when I say that implementations should always be against interfaces. This foundation is already taught in the introduction to object-oriented programming. In my daily work, however, I often see that many developers aren’t always fully aware of the importance of developing against interfaces, even though this is common practice when using the Java Standard API. The classic example of this is:

List<String> collection = new ArrayList<>();

This short line uses the List interface, which is implemented as an ArrayList. Here we can also see that there is no suffix in the form of an “I” to identify the interface. The corresponding implementation also does not have “Impl” in its name. That’s a good thing! Especially with the implementation class, various solutions may be desired. In such cases, it is important to clearly label them and keep them easily distinguishable by name. ListImpl and ListImpl2 are understandably not as easy to distinguish as ArrayList and LinkedList. This also clears up the first point of a stringent and meaningful naming convention.

In the next step, we’ll focus on the program parts that we don’t want to expose to consumers of the application, as they are helper classes. Part of the solution lies in the structure of how the packages are organized. A very practical approach is:

  • my.package.path.business: Contains all interfaces
  • my.package.path.application: Contains the interface implementations
  • my.package.path.application.helper: Contains internal helper classes

This simple architecture alone signals to other programmers that it’s not a good idea to use classes from the helper package. Starting with Java 9, there are even more far-reaching restrictions prohibiting the use of internal helper classes. Modularization, which was introduced in Java 9 with the Jingsaw project [1], allows packages to be hidden from view in the module-info.java module descriptor.

Separatists and their Escape from the Crowd

A closer look at most specifications reveals that many interfaces have been outsourced to their own libraries. From a technological perspective, based on the previous example, this would mean that the business package, which contains the interfaces, is outsourced to its own library. The separation of API and the associated implementation fundamentally makes it easier to interchange implementations. It also allows a client to exert greater influence over the implementation of their project with their contractual partner, as the developer receives the API pre-built by the client. As great as the idea is, a few rules must be observed to ensure it actually works as originally intended.

Example 1: JDBC. We know that Java Database Connectivity is a standard for connecting various database systems to an application. Aside from the problems associated with using native SQL, MySQL JDBC drivers cannot simply be replaced by PostgreSQL or Oracle. After all, every manufacturer deviates more or less from the standard in their implementation and also provides exclusive functionality of their own product via the driver. If you decide to make extensive use of these additional features in your own project, the easy interchangeability is over.

Example 2: XML. Here, you have the choice between several standards. It’s clear, of course, that the APIs of SAX, DOM, and StAX are incompatible. For example, if you want to switch from DOM to event-based SAX for better performance, this can potentially result in extensive code changes.

Example 3: PDF. Last but not least, I have a scenario for a standard that doesn’t have a standard. The Portable Document Format itself is a standard for how document files are structured, but when it comes to implementing usable program libraries for their own applications, each manufacturer has its own ideas.

These three small examples illustrate the common problems that must be overcome in daily project work. A small rule can have a big impact: only use third-party libraries when absolutely necessary. After all, every dependency used also poses a potential security risk. It’s also not necessary to include a library of just a few MB to save the three lines required to check a string for null and empty values.

Model Boys

If you’ve decided on an external library, it’s always beneficial to do the initial work and encapsulate the functionality in a separate class, which you can then use extensively. In my personal project TP-CORE on GitHub [2], I’ve done this in several places. The logger encapsulates the functionality of SLF4J and Logback. Compared to the PdfRenderer, the method signatures are independent of the logging libraries used and can therefore be more easily exchanged via a central location. To encapsulate external libraries in your own application as much as possible, the following design patterns are available: wrapper, facade, and proxy.

Wrapper: also called the adaptor pattern, belongs to the group of structural patterns. The wrapper couples one interface to another that are incompatible.

Facade: is also a structural pattern and bundles several interfaces into a simplified interface.

Proxy: also called a representative, also belongs to the category of structural patterns. Proxies are a generalization of a complex interface. They can be understood as complementary to the facade, which combines multiple interfaces into a single one.

It is certainly important in theory to separate these different scenarios in order to describe them correctly. In practice, however, it is not critical if hybrid forms of the design patterns presented here are used to encapsulate external functionality. For anyone interested in exploring design patterns in more depth, we recommend the book “Design Patterns from Head to Toe” [3].

Class Reunion

Another step toward a stable API is detailed documentation. Based on the interfaces discussed so far, there’s a small library that allows methods to be annotated based on the API version. In addition to status and version information, the primary implementations for classes can be listed using the consumers attribute. To add API Gaurdian to your project, you only need to add a few lines to the POM and replace the ${version} property with the current version.

 <dependency>
    <groupId>org.apiguardian</groupId>
    <artifactId>apiguardian-api</artifactId>
    <version>${version}</version>
 </dependency>

Marking up methods and classes is just as easy. The @API annotation has the attributes: status, since, and consumers. The following values ​​are possible for status:

  • DEPRECATED: Deprecated, should not be used any further.
  • EXPERIMENTAL: Indicates new features for which the developer would like feedback. Use with caution, as changes can always occur.
  • INTERNAL: For internal use only, may be discontinued without warning.
  • STABLE: Backward-compatible feature that remains unchanged for the existing major version.
  • MAINTAINED: Ensures backward stability for the future major release.

Now that all interfaces have been enriched with this useful meta information, the question arises where the added value can be found. I simply refer you to Figure 1, which demonstrates everyday work.

Figure 1: Suggestion in Netbeans with @API annotation in the JavaDoc

For service-based RESTful APIs, there is another tool called Swagger [4]. This also follows the approach of creating API documentation from annotations. However, Swagger itself scans Java web service annotations instead of introducing its own. It is also quite easy to use. All that is required is to integrate the swagger-maven-plugin and specify the packages in which the web services reside in the configuration. Subsequently, a description is created in the form of a JSON file for each build, from which Swagger UI then generates executable documentation. Swagger UI itself is available as a Docker image on DockerHub [5].

<plugin>
   <groupId>io.swagger.core.v3</groupId>
   <artifactId>swagger-maven-plugin</artifactId>
   <version>${version}</version>
   <configuration>
      <outputFileName>swagger</outputFileName>
      <outputFormat>JSON</outputFormat>
      <resourcePackages>
          <package>org.europa.together.service</package>
      </resourcePackages>
      <outputPath>${project.build.directory}</outputPath>
   </configuration>
</plugin>
Figure 2: Swagger UI documentation of the TP-ACL RESTful API.

Versioning is an important aspect for APIs. Using semantic versioning, a lot can be gleaned from the version number. Regarding an API, the major segment is significant. This first digit indicates API changes that are incompatible with each other. Such incompatibility includes the removal of classes or methods. However, changing existing signatures or the return value of a method also requires adjustments from consumers as part of a migration. It’s always a good idea to bundle work that causes incompatibilities and publish it less frequently. This demonstrates project stability.

Versioning is also recommended for Web APIs. This is best done via the URL by including a version number. So far, I’ve had good experiences with only incrementing the version when incompatibilities occur.

Relationship Stress

The great advantage of a RESTful service, being able to get along well with “everyone,” is also its greatest curse. This means that a great deal of care must be taken, as many clients are being served. Since the interface is a collection of URIs, our focus is on the implementation details. For this, I’ll use an example from my TP-ACL project, which is also available on GitHub.

RolesDO role = rolesDAO.find(roleName);
String json = rolesDAO.serializeAsJson(role);
if (role != null) {
    response = Response.status(Response.Status.OK)
            .type(MediaType.APPLICATION_JSON)
            .entity(json)
            .encoding("UTF-8")
            .build();
} else {
    response = Response.status(Response.Status.NOT_FOUND).build();
}

This is a short excerpt from the try block of the fetchRole method found in the RoleService class. The GET request returns a 404 error code if a role is not found. You probably already know what I’m getting at.

When implementing the individual actions GET, PUT, DELETE, etc. of a resource such as a role, it’s not enough to simply implement the so-called HappyPath. The possible stages of such an action should be considered during the design phase. For the implementation of a consumer (client), it makes a significant difference whether a request that cannot be completed with a 200 failed because the resource does not exist (404) or because access was denied (403). Here, I’d like to allude to the telling Windows message about the unexpected error.

Conclusion

When we talk about an API, we mean an interface that can be used by other programs. A major version change indicates to API consumers that there is an incompatibility with the previous version. This may require adjustments. It is completely irrelevant what type of API it is or whether the application uses it publicly or internally via the fetchRole method. The resulting consequences are identical. For this reason, you should carefully consider the externally visible areas of your application.

Work that leads to API incompatibility should be bundled by release management and, if possible, released no more than once per year. This also demonstrates the importance of regular code inspections for consistent quality.

Resources

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jConf Peru 2021 [2]

Mission accomplished: deploy to Maven Central

Many developers have ideas they work on it in their spare time. The most of us are convinced about open source and share their own projects on platforms like GitHub. But what happen after a publication of the source code? If you really want to gain people to use your project you’re not done yet. It’s also a good idea to publish your artifacts for a simple usage.

The most famous storage for binary Java Artifacts is Maven Central. Doesn‘t matter if you use in your projects Ivy, Gradle or Maven as dependency management, all those technologies access to Maven Central. In this talk you will learn how to publish your artifacts with Maven to Sonatype Nexuss OSS. We pass through all steps from creating accounts until the the binaries are available. In between I give some general hints about the usage of repository managers and helpful tricks for a lightweight Release Management.

Learn things about token replacement, executable jar, BOM, Dependency Management, enforcement, reporting and much more in live demonstrations.

BarCamp República Dominicana 2021

API4Future: A journey how to create a stable API

By experience, enterprise applications have a long lifetime period. This is one oft the  reasons why we need to pay a lot of attention for maintenance. But how we are able to avoid chaos in the project? With some Code Examples in Java I will demonstrate how a stable API get developed. Some questions I will answer in this talk:

  • Quality and Maintenance
  • Architecture & Design Pattern for APIs
  • API Documentation & Versioning

{j}DD Poland 2021

Refactoring Disasters: A Story how I failed

For my small Open Source project TP-CORE, you can find it on GitHub, I had the gorgeous Idea to replace the iText library for OpenPDF. After I made a plan how I could reach my goal I started all necessary activities. But in real life the things never that easy like we have originally in mind. I failed with my idea and in this talk I will let you know what happened exactly. I talk about my motivation why I wanted the replacements and how was my plan to success all activities. You will get to know how it was when I reached the point, I realized I will not make it. I give a brief explanation what I did that this short adventure did not affect the rest of the project.

Acceptance Tests in Java With JGiven

Most of the developer community know what a unit test is, even they don’t write them. But there is still hope. The situation is changing. More and more projects hosted on GitHub contain unit tests.

In a standard set-up for Java projects like NetBeans, Maven, and JUnit, it is not that difficult to produce your first test code. Besides, this approach is used in Test Driven Development (TDD) and exists in other technologies like Behavioral Driven Development (BDD), also known as acceptance tests, which is what we will focus on in this article.

Difference Between Unit and Acceptance Tests

The easiest way to become familiar with this topic is to look at a simple comparison between unit and acceptance tests. In this context, unit tests are very low level. They execute a function and compare the output with an expected result. Some people think differently about it, but in our example, the only one responsible for a unit test is the developer.

Keep in mind that the test code is placed in the project and always gets executed when the build is running. This provides quick feedback as to whether or not something went wrong. As long the test doesn’t cover too many aspects, we are able to identify the problem quickly and provide a solution. The design principle of those tests follows the AAA paradigm. Define a precondition (Arrange), execute the invariant (Act), and check the postconditions (Assume). We will come back to this approach a little later.

When we check the test coverage with tools like JaCoCo and cover more than 85 percent of our code with test cases, we can expect good quality. During the increasing test coverage, we specify our test cases more precisely and are able to identify some optimizations. This can be removing or inverting conditions because during the tests we find out, it is almost impossible to reach those sections. Of course, the topic is a bit more complicated, but those details could be discussed in another article.

Acceptance test are same classified like unit tests. They belong to the family of regression tests. This means we want to observe if changes we made on the code have no effects on already worked functionality. In other words, we want to secure that nothing already is working got broken, because of some side effects of our changes. The tool of our choice is JGiven [1]. Before we look at some examples, first, we need to touch on a bit of theory.

JGiven In-Depth

The test cases we define in JGiven is called a scenario. A scenario is a collection of four classes, the scenario itself, the Given displayed as given (Arrange), the Action displayed as when (Act) and Outcome displayed as then (Assume).

In most projects, especially when there is a huge amount of scenarios and the execution consumes a lot of time, acceptance tests got organized in a separate project. With a build job on your CI server, you can execute those tests once a day to get fast feedback and to react early if something is broken. The code example we demonstrate contains everything in one project on GitHub [2] because it is just a small library and a separation would just over-engineer the project. Usually, the one responsible for acceptance tests is the test center, not the developer.

The sample project TP-CORE is organized by a layered architecture. For our example, we picked out the functionality for sending e-mails. The basic functionality to compose an e-mail is realized in the application layer and has a test coverage of up to 90 percent. The functionality to send the e-mail is defined in the service layer.

In our architecture, we decided that the service layer is our center of attention to defining acceptance tests. Here, we want to see if our requirement to send an e-mail is working well. Supporting this layer with our own unit tests is not that efficient because, in commercial projects, it just produces costs without winning benefits. Also, having also unit tests means we have to do double the work because our JGiven tests already demonstrate and prove that our function is well working. For those reasons, it makes no sense to generate test coverage for the test scenarios of the acceptance test.

Let’s start with a practice example. At first, we need to include our acceptance test framework into our Maven build. In case you prefer Gradle, you can use the same GAV parameters to define the dependencies in your build script.

<dependency>
   <groupId>com.tngtech.jgiven</groupId>
   <artifactId>jgiven-junit</artifactId>
   <version>0.18.2</version>
   <scope>test</scope>
</dependency>
XML

Listing 1: Dependency for Maven.

As you can see in listing 1, JGiven works well together with JUnit. An integration to TestNG also exists , you just need to replace the artifactId for jgiven-testng. To enable the HTML reports, you need to configure the Maven plugin in the build lifecycle, like it is shown in Listing 2.

<build> 
   <plugins> 
      <plugin>
         <groupId>com.tngtech.jgiven</groupId>
         <artifactId>jgiven-maven-plugin</artifactId>
         <version>0.18.2</version>
         <executions>
            <execution>
               <goals>
                  <goal>report</goal>
               </goals>
            </execution>
         </executions>
         <configuration>
            <format>html</format>
         </configuration>
      </plugin>
   </plugins>
</build>
XML

Listing 2: Maven Plugin Configuration for JGiven.

The report of our scenarios in the TP-CORE project is shown in image 1. As we can see, the output is very descriptive and human-readable. This result will be explained by following some naming conventions for our methods and classes, which will be explained in detail below. First, let’s discuss what we can see in our test scenario. We defined five preconditions:

  1. The configuration for the SMPT server is readable
  2. The SMTP server is available
  3. The mail has a recipient
  4. The mail has attachments
  5. The mail is full composed

If all these conditions are true, the action will send a single e-mail got performed. Afterward, after the SMTP server is checked, we see that the mail has arrived. For the SMTP service, we use the small Java library greenmail [3] to emulate an SMTP server. Now it is understandable why it is advantageous for acceptance tests if they are written by other people. This increases the quality as early on conceptional inconsistencies appear. Because as long as the tester with the available implementations cannot map the required scenario, the requirement is not fully implemented.

Producing Descriptive Scenarios

Now is the a good time to dive deeper into the implementation details of our send e-mail test scenario. Our object under test is the class MailClientService. The corresponding test class is  MailClientScenarioTest, defined in the test packages. The scenario class definition is shown in listing 3.

@RunWith(JUnitPlatform.class) 
public class MailClientScenarioTest
       extends <strong>ScenarioTest</strong><MailServiceGiven, MailServiceAction, MailServiceOutcome> { 
    // do something 
}

Listing 3: Acceptance Test Scenario for JGiven.

As we can see, we execute the test framework with JUnit5. In the  ScenarioTest, we can see the three classes: Given, Action, and Outcome in a special naming convention. It is also possible to reuse already defined classes, but be careful with such practices. This can cost some side effects. Before we now implement the test method, we need to define the execution steps. The procedure for the three classes are equivalent.

@RunWith(JUnitPlatform.class) 
public class MailServiceGiven 
       extends <strong>Stage</strong><MailServiceGiven> { 

    public MailServiceGiven email_has_recipient(MailClient client) {
        try { 
            assertEquals(1, client.getRecipentList().size());
        } catch (Exception ex) {
            System.err.println(ex.getMessage);
        }
        return self(); 
    } 
} 

@RunWith(JUnitPlatform.class)
public class MailServiceAction
       extends <strong>Stage</strong><MailServiceAction> { 

    public MailServiceAction send_email(MailClient client) {
        MailClientService service = new MailClientService();
        try {
            assertEquals(1, client.getRecipentList().size());
            service.sendEmail(client);
        } catch (Exception ex) { 
            System.err.println(ex.getMessage);
        }
        return self();
    }
}

@RunWith(JUnitPlatform.class)
public class MailServiceOutcome 
       extends <strong>Stage</strong><MailServiceOutcome> {

    public MailServiceOutcome email_is_arrived(MimeMessage msg) { 
         try {
             Address adr = msg.getAllRecipients()[0];
             assertEquals("JGiven Test E-Mail", msg.getSubject());
             assertEquals("noreply@sample.org", msg.getSender().toString());
             assertEquals("otto@sample.org", adr.toString());
             assertNotNull(msg.getSize());
         } catch (Exception ex) {
             System.err.println(ex.getMessage);
         }
         return self();
    }
}

Listing 4: Implementing the AAA Principle for Behavioral Driven Development.

Now, we completed the cycle and we can see how the test steps got stuck together. JGiven supports a bigger vocabulary to fit more necessities. To explore the full possibilities, please consult the documentation.

Lessons Learned

In this short workshop, we passed all the important details to start with automated acceptance tests. Besides JGiven exist other frameworks, like Concordion or FitNesse fighting for usage. Our choice for JGiven was its helpful documentation, simple integration into Maven builds and JUnit tests, and the descriptive human-readable reports.

As negative point, which could people keep away from JGiven, could be the detail that you need to describe the tests in the Java programming language. That means the test engineer needs to be able to develop in Java, if they want to use JGiven. Besides this small detail, our experience with JGiven is absolutely positive.

The new Java Release Cycle

After Oracle introduces the new release cycle for Java I was not convinced of this new strategy. Even today I still have a different opinion. One of the point I criticize is the disregard of semantic versioning. Also the argument with this new cycle is more easy to deliver more faster new features, I’m not agree. In my opinion could occur some problems in the future. But wait, let’s start from the beginning, before I share my complete thoughts at once.

The six month release cycle Oracle announced in 2017 for Java ensure some insecurity to the community. The biggest fear was formulated by the popular question: Will be Java in future not anymore for free? Of course the answer is a clear no, but there are some impacts for companies they should be aware of it. If we think on huge Applications in production, are some points addressed to the risk management and the business continuing strategy. If the LTS support for security updates after the 3rd year of a published release have to be paid, force well defined strategies for updates into production. I see myself spending in future more time to migrate my projects to new java versions than implement new functionalities. One solution to avoid a permanent update orgy is move away from the Oracle JVM to OpenJDK.

In professional environment is quite popular that companies define a fixed setup to keep security. When I always are forced to update my components without a proof the new features are secure, it could create problems. Commercial projects running under other circumstances and need often special attention. Because you need a well defined environment where you know everything runs stable. Follow the law never touch a running system.

Absolutely I can understand the intention of Oracle to take this step. I guess it’s a way to get rid of old buggy and insecure installations. To secure the internet a bit more. Of course you can not support decades old deprecated versions. This have a heavy financial impact. but I wish they had chosen an less rough strategy. It’s sadly that the business often operate in this way. I wished it exist a more trustful communication.

By experience of preview releases of Java it always was taken a time until they get stable. In this context I remind myself to some heavy issues I was having with the change to 64 bit versions. The typical motto: latest is greatest, could be dangerous. Specially time based releases are good candidates for problems, even when the team is experienced. The pressure is extremely high to deliver in time.

Another fact which could discuss is the semantic versioning. It is a very powerful process, I always recommend. I ask myself If there really every six months new language features to have the reason increasing the Major number? Even for patches and enhancements? But what happens when in future is no new language enhancement? By the way adding by force often new features could decrease quality. In my opinion Java includes many educative features and not every new feature request increase the language capabilities. A simple example is the well known GOTO statement in other languages. When you learn programming often your mentor told you – it exist something if you see it you should run away. Never use GOTO. In Java inner classes I often compare with GOTO, because I think this should avoid. Until now I didn’t find any case where inner classes not a hint for design problems. The same is the heavy usage of functional statements. I can’t find any benefit to define a for loop as lambda function instead of the classical way.

In my opinion it looks like Oracle try to get some pieces from the cake to increase their business. Well this is not something bad,. But in the view of project management I don’t believe it is a well chosen strategy.

Read more: https://www.infoq.com/news/2017/09/Java6Month/