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JUNG the Java Universal Network/Graph Framework--is a software library that provides a common and extendible language for the modeling, analysis, and visualization of data that can be represented as a graph or network. It is written in Java, which allows JUNG-based applications to make use of the extensive built-in capabilities of the Java API, as well as those of other existing third-party Java libraries. The JUNG architecture is designed to support a variety of representations of entities and their relations, such as directed and undirected graphs, multi-modal graphs, graphs with parallel edges, and hypergraphs. It provides a mechanism for annotating graphs, entities, and relations with metadata. This facilitates the creation of analytic tools for complex data sets that can examine the relations between entities as well as the metadata attached to each entity and relation. The current distribution of JUNG includes implementations of a number of algorithms from graph theory, data mining, and social network analysis, such as routines for clustering, decomposition, optimization, random graph generation, statistical analysis, and calculation of network distances, flows, and importance measures (centrality, PageRank, HITS, etc.). JUNG also provides a visualization framework that makes it easy to construct tools for the interactive exploration of network data. Users can use one of the layout algorithms provided, or use the framework to create their own custom layouts. In addition, filtering mechanisms are provided which allow users to focus their attention, or their algorithms, on specific portions of the graph.

This project aims to build a command line tool that can create HTML view with syntax highlighted source code. It uses Jedit syntax highlighting engine and support all languages that are supported in JEdit. Which are currently: ActionScript, Ada 95, ANTLR, Apache HTTPD, APDL, AppleScript, ASP, Aspect-J, Assembly, AWK, B formal method, Batch, BBj, BCEL, BibTeX, C, C++, C#, CHILL, CIL, COBOL, ColdFusion, CSS, CVS Commit, D, DOxygen, DSSSL, Eiffel, EmbPerl, Erlang, Factor, Fortran, Foxpro, FreeMarker, Fortran, Gettext, Groovy, Haskell, HTML, Icon, IDL, Inform, INI, Inno Setup, Informix 4GL, Interlis, Io, Java, JavaScript, JCL, JHTML, JMK, JSP, Latex, Lilypond, Lisp, LOTOS, Lua, Makefile, Maple, ML, Modula-3, MoinMoin, MQSC, NetRexx, NQC, NSIS2, Objective C, ObjectRexx, Occam, Omnimark, Parrot, Pascal, Patch, Perl, PHP, Pike, PL-SQL, PL/I, Pop11, PostScript, Povray, PowerDynamo, Progress 4GL, Prolog, Properties, PSP, PV-WAVE, Pyrex, Python, REBOL, Redcode, Relax-NG, RelationalView, Rest, Rib, RPM spec, RTF, Ruby, Ruby-HTML, RView, S+, S#, SAS, Scheme, SDL/PL, SGML, Shell Script, SHTML, Smalltalk, SMI MIB, SQR, Squidconf, SVN Commit, Swig, TCL, TeX, Texinfo, TPL, Transact-SQL, UnrealScript, VBScript, Velocity, Verilog, VHDL, XML, XSL, ZPT

This project aims to offer an easy-to-extend Java DAS server framework. It offers several advantages: * Implementing data sources is very easy but also flexible and powerful. * Data caching is built into the system, with access to the caching mechanism made available to the data sources. * All aspects of the server are highly configurable, including selecting options where the DAS 1.53 specification offers choices to the implementor. * The latest Java technologies have been used throughout the system to optimise performance and simplify data source development. * Wherever possible the same terminology is used in the API as in the DAS specification and XML - again, making data source development more easy. * The server allows XSLT transforms of the DAS XML to be configured to provide a simple DAS client view (limited to the single DAS source). More details of the DAS protocol, DAS servers and DAS clients can be found at http://www.biodas.org/wiki/Main_Page. The first version of this server is a complete implementation of Distributed Sequence Annotation System (DAS) Version 1.53. If you are interested in learning more about DAS 1.53, the specification is highly recommended as a concise and complete description of the DAS protocol that can be obtained from: http://biodas.org/documents/spec.html

IronPDF Java library offers an extensive compatibility range, making it a go-to solution for a wide array of developers. It fully supports JVM languages like Java, Scala, and Kotlin, making it incredibly versatile. This Java PDF library is also compatible with Java 8 and above, providing optimum performance across multiple platforms. It's been designed with a wide range of users in mind Here's a look at what it supports: JVM Languages: Java, Scala, Kotlin.Platforms: Java 8 and above.Operating Systems: Microsoft Windows, Linux, Docker, Azure, AWS.IDEs: Jetbrains IntelliJ IDEA, Eclipse. You can deploy IronPDF Java across various platforms, including Microsoft Windows, Linux, Docker, Azure, and AWS. It is also fully compatible with popular IDEs like Jetbrains IntelliJ IDEA and Eclipse, facilitating smooth project development and management. Your pom.xml file is essentially the backbone of your project when you're using Maven. It's here where you introduce new dependencies that you wish to include. To make IronPDF Java package a part of your Maven project, you simply need to add the following snippets to your pom.xml: Remember to replace '20xx.xx.xxxx' with the latest version of IronPDF. IronPDF Java simplifies the process of creating PDF files. Convert HTML files, HTML strings, or URLs directly to new PDF documents in a few lines of code. The variety of file formats it handles is vast, as it can even transform images into PDF documents and vice versa. Need to use base 64 encoding, base URLs, or custom file paths? No problem! IronPDF Java has got you coveredFor more detail about installing and using IronPDF Java. When you run your project for the first time post-integration, IronPDF's engine binaries will automatically be downloaded. The engine starts its journey when you call any IronPDF function for the first time and takes a breather when your application is either closed or enters an idle state. It is not an open source java PDF library but here's the best part - IronPDF Java is offering a 30-day free trial. So, why wait? Give it a go and boost your PDF operations today.

Chips-n-Salsa is a Java library of customizable, hybridizable, iterative, parallel, stochastic, and self-adaptive local search algorithms. The library includes implementations of several stochastic local search algorithms, including simulated annealing, hill climbers, as well as constructive search algorithms such as stochastic sampling. Chips-n-Salsa now also includes genetic algorithms as well as evolutionary algorithms more generally. The library very extensively supports simulated annealing. It includes several classes for representing solutions to a variety of optimization problems. For example, the library includes a BitVector class that implements vectors of bits, as well as classes for representing solutions to problems where we are searching for an optimal vector of integers or reals. For each of the built-in representations, the library provides the most common mutation operators for generating random neighbors of candidate solutions, as well as common crossover operators for use with evolutionary algorithms. Additionally, the library provides extensive support for permutation optimization problems, including implementations of many different mutation operators for permutations, and utilizing the efficiently implemented Permutation class of the JavaPermutationTools (JPT) library. Chips-n-Salsa is customizable, making extensive use of Java's generic types, enabling using the library to optimize other types of representations beyond what is provided in the library. It is hybridizable, providing support for integrating multiple forms of local search (e.g., using a hill climber on a solution generated by simulated annealing), creating hybrid mutation operators (e.g., local search using multiple mutation operators), as well as support for running more than one type of search for the same problem concurrently using multiple threads as a form of algorithm portfolio. Chips-n-Salsa is iterative, with support for multistart metaheuristics, including implementations of several restart schedules for varying the run lengths across the restarts. It also supports parallel execution of multiple instances of the same, or different, stochastic local search algorithms for an instance of a problem to accelerate the search process. The library supports self-adaptive search in a variety of ways, such as including implementations of adaptive annealing schedules for simulated annealing, such as the Modified Lam schedule, implementations of the simpler annealing schedules but which self-tune the initial temperature and other parameters, and restart schedules that adapt to run length.

Apache Commons Crypto is a cryptographic library optimized with AES-NI (Advanced Encryption Standard New Instructions). It provides Java API for both cipher level and Java stream level. Developers can use it to implement high performance AES encryption/decryption with the minimum code and effort. Please note that Crypto doesn't implement the cryptographic algorithm such as AES directly. It wraps to OpenSSL or JCE which implement the algorithms. Features -------- 1. Cipher API for low level cryptographic operations. 2. Java stream API (CryptoInputStream/CryptoOutputStream) for high level stream encryption/decryption. 3. Both optimized with high performance AES encryption/decryption. (1400 MB/s - 1700 MB/s throughput in modern Xeon processors). 4. JNI-based implementation to achieve comparable performance to the native C/C++ version based on OpenSsl. 5. Portable across various operating systems (currently only Linux/MacOSX/Windows); Apache Commons Crypto loads the library according to your machine environment (it checks system properties, `os.name` and `os.arch`). 6. Simple usage. Add the commons-crypto-(version).jar file to your classpath. Export restrictions ------------------- This distribution includes cryptographic software. The country in which you currently reside may have restrictions on the import, possession, use, and/or re-export to another country, of encryption software. BEFORE using any encryption software, please check your country's laws, regulations and policies concerning the import, possession, or use, and re-export of encryption software, to see if this is permitted. See <http://www.wassenaar.org/> for more information. The U.S. Government Department of Commerce, Bureau of Industry and Security (BIS), has classified this software as Export Commodity Control Number (ECCN) 5D002.C.1, which includes information security software using or performing cryptographic functions with asymmetric algorithms. The form and manner of this Apache Software Foundation distribution makes it eligible for export under the License Exception ENC Technology Software Unrestricted (TSU) exception (see the BIS Export Administration Regulations, Section 740.13) for both object code and source code. The following provides more details on the included cryptographic software: * Commons Crypto use [Java Cryptography Extension](http://docs.oracle.com/javase/8/docs/technotes/guides/security/crypto/CryptoSpec.html) provided by Java * Commons Crypto link to and use [OpenSSL](https://www.openssl.org/) ciphers

pact-jvm-consumer-specs2 ======================== ## Specs2 Bindings for the pact-jvm library ## Dependency In the root folder of your project in build.sbt add the line: ```scala libraryDependencies += &quot;au.com.dius.pact.consumer&quot; %% &quot;specs2&quot; % &quot;4.0.1&quot; ``` or if you are using Gradle: ```groovy dependencies { testCompile &quot;au.com.dius.pact.consumer:specs2_2.13:4.0.1&quot; } ``` __*Note:*__ `PactSpec` requires spec2 3.x. Also, for spray users there&apos;s an incompatibility between specs2 v3.x and spray. Follow these instructions to resolve that problem: https://groups.google.com/forum/#!msg/spray-user/2T6SBp4OJeI/AJlnJuAKPRsJ ## Usage To author a test, mix `PactSpec` into your spec First we define a service client called `ConsumerService`. In our example this is a simple wrapper for `dispatch`, an HTTP client. The source code can be found in the test folder alongside the `ExamplePactSpec`. Here is a simple example: ``` import au.com.dius.pact.consumer.PactSpec class ExamplePactSpec extends Specification with PactSpec { val consumer = &quot;My Consumer&quot; val provider = &quot;My Provider&quot; override def is = uponReceiving(&quot;a request for foo&quot;) .matching(path = &quot;/foo&quot;) .willRespondWith(body = &quot;{}&quot;) .withConsumerTest { providerConfig =&gt; Await.result(ConsumerService(providerConfig.url).simpleGet(&quot;/foo&quot;), Duration(1000, MILLISECONDS)) must beEqualTo(200, Some(&quot;{}&quot;)) } } ``` This spec will be run along with the rest of your specs2 unit tests and will output your pact json to ``` /target/pacts/&lt;Consumer&gt;_&lt;Provider&gt;.json ``` # Forcing pact files to be overwritten (3.6.5+) By default, when the pact file is written, it will be merged with any existing pact file. To force the file to be overwritten, set the Java system property `pact.writer.overwrite` to `true`. # Test Analytics We are tracking anonymous analytics to gather important usage statistics like JVM version and operating system. To disable tracking, set the &apos;pact_do_not_track&apos; system property or environment variable to &apos;true&apos;.

# pact-jvm-consumer-java8 Provides a Java8 lambda based DSL for use with Junit to build consumer tests. # A Lambda DSL for Pact This is an extension for the pact DSL provided by [pact-jvm-consumer](../pact-jvm-consumer). The difference between the default pact DSL and this lambda DSL is, as the name suggests, the usage of lambdas. The use of lambdas makes the code much cleaner. ## Why a new DSL implementation? The lambda DSL solves the following two main issues. Both are visible in the following code sample: ```java new PactDslJsonArray() .array() # open an array .stringValue(&quot;a1&quot;) # choose the method that is valid for arrays .stringValue(&quot;a2&quot;) # choose the method that is valid for arrays .closeArray() # close the array .array() # open an array .numberValue(1) # choose the method that is valid for arrays .numberValue(2) # choose the method that is valid for arrays .closeArray() # close the array .array() # open an array .object() # now we work with an object .stringValue(&quot;foo&quot;, &quot;Foo&quot;) # choose the method that is valid for objects .closeObject() # close the object and we&apos;re back in the array .closeArray() # close the array ``` ### The existing DSL is quite error-prone Methods may only be called in certain states. For example `object()` may only be called when you&apos;re currently working on an array whereas `object(name)` is only allowed to be called when working on an object. But both of the methods are available. You&apos;ll find out at runtime if you&apos;re using the correct method. Finally, the need for opening and closing objects and arrays makes usage cumbersome. The lambda DSL has no ambiguous methods and there&apos;s no need to close objects and arrays as all the work on such an object is wrapped in a lamda call. ### The existing DSL is hard to read When formatting your source code with an IDE the code becomes hard to read as there&apos;s no indentation possible. Of course, you could do it by hand but we want auto formatting! Auto formatting works great for the new DSL! ```java array.object((o) -&gt; { o.stringValue(&quot;foo&quot;, &quot;Foo&quot;); # an attribute o.stringValue(&quot;bar&quot;, &quot;Bar&quot;); # an attribute o.object(&quot;tar&quot;, (tarObject) -&gt; { # an attribute with a nested object tarObject.stringValue(&quot;a&quot;, &quot;A&quot;); # attribute of the nested object tarObject.stringValue(&quot;b&quot;, &quot;B&quot;); # attribute of the nested object }) }); ``` ## Installation ### Maven ``` &lt;dependency&gt; &lt;groupId&gt;au.com.dius&lt;/groupId&gt; &lt;artifactId&gt;pact-jvm-consumer-java8_2.12&lt;/artifactId&gt; &lt;version&gt;${pact.version}&lt;/version&gt; &lt;/dependency&gt; ``` ## Usage Start with a static import of `LambdaDsl`. This class contains factory methods for the lambda dsl extension. When you come accross the `body()` method of `PactDslWithProvider` builder start using the new extensions. The call to `LambdaDsl` replaces the call to instance `new PactDslJsonArray()` and `new PactDslJsonBody()` of the pact library. ```java io.pactfoundation.consumer.dsl.LambdaDsl.* ``` ### Response body as json array ```java import static io.pactfoundation.consumer.dsl.LambdaDsl.newJsonArray; ... PactDslWithProvider builder = ... builder.given(&quot;some state&quot;) .uponReceiving(&quot;a request&quot;) .path(&quot;/my-app/my-service&quot;) .method(&quot;GET&quot;) .willRespondWith() .status(200) .body(newJsonArray((a) -&gt; { a.stringValue(&quot;a1&quot;); a.stringValue(&quot;a2&quot;); }).build()); ``` ### Response body as json object ```java import static io.pactfoundation.consumer.dsl.LambdaDsl.newJsonBody; ... PactDslWithProvider builder = ... builder.given(&quot;some state&quot;) .uponReceiving(&quot;a request&quot;) .path(&quot;/my-app/my-service&quot;) .method(&quot;GET&quot;) .willRespondWith() .status(200) .body(newJsonBody((o) -&gt; { o.stringValue(&quot;foo&quot;, &quot;Foo&quot;); o.stringValue(&quot;bar&quot;, &quot;Bar&quot;); }).build()); ``` ### Examples #### Simple Json object When creating simple json structures the difference between the two approaches isn&apos;t big. ##### JSON ```json { &quot;bar&quot;: &quot;Bar&quot;, &quot;foo&quot;: &quot;Foo&quot; } ``` ##### Pact DSL ```java new PactDslJsonBody() .stringValue(&quot;foo&quot;, &quot;Foo&quot;) .stringValue(&quot;bar&quot;, &quot;Bar&quot;) ``` ##### Lambda DSL ```java newJsonBody((o) -&gt; { o.stringValue(&quot;foo&quot;, &quot;Foo&quot;); o.stringValue(&quot;bar&quot;, &quot;Bar&quot;); }).build(); ``` #### An array of arrays When we come to more complex constructs with arrays and nested objects the beauty of lambdas become visible! ##### JSON ```json [ [&quot;a1&quot;, &quot;a2&quot;], [1, 2], [{&quot;foo&quot;: &quot;Foo&quot;}] ] ``` ##### Pact DSL ```java new PactDslJsonArray() .array() .stringValue(&quot;a1&quot;) .stringValue(&quot;a2&quot;) .closeArray() .array() .numberValue(1) .numberValue(2) .closeArray() .array() .object() .stringValue(&quot;foo&quot;, &quot;Foo&quot;) .closeObject() .closeArray(); ``` ##### Lambda DSL ```java newJsonArray((rootArray) -&gt; { rootArray.array((a) -&gt; a.stringValue(&quot;a1&quot;).stringValue(&quot;a2&quot;)); rootArray.array((a) -&gt; a.numberValue(1).numberValue(2)); rootArray.array((a) -&gt; a.object((o) -&gt; o.stringValue(&quot;foo&quot;, &quot;Foo&quot;))); }).build(); ``` `object` is a reserved word in Kotlin. To allow using the DSL without escaping, a Kotlin extension `newObject` is available: ```kotlin newJsonArray { rootArray -&gt; rootArray.array { a -&gt; a.stringValue(&quot;a1&quot;).stringValue(&quot;a2&quot;) } rootArray.array { a -&gt; a.numberValue(1).numberValue(2) } rootArray.array { a -&gt; a.newObject { o -&gt; o.stringValue(&quot;foo&quot;, &quot;Foo&quot;) } } }.build(); ```

# Pact Spring/JUnit5 Support This module extends the base [Pact JUnit5 module](../pact-jvm-provider-junit5). See that for more details. For writing Spring Pact verification tests with JUnit 5, there is an JUnit 5 Invocation Context Provider that you can use with the `@TestTemplate` annotation. This will generate a test for each interaction found for the pact files for the provider. To use it, add the `@Provider` and `@ExtendWith(SpringExtension.class)` and one of the pact source annotations to your test class (as per a JUnit 5 test), then add a method annotated with `@TestTemplate` and `@ExtendWith(PactVerificationSpringProvider.class)` that takes a `PactVerificationContext` parameter. You will need to call `verifyInteraction()` on the context parameter in your test template method. For example: ```java @ExtendWith(SpringExtension.class) @SpringBootTest(webEnvironment = SpringBootTest.WebEnvironment.DEFINED_PORT) @Provider(&quot;Animal Profile Service&quot;) @PactBroker public class ContractVerificationTest { @TestTemplate @ExtendWith(PactVerificationSpringProvider.class) void pactVerificationTestTemplate(PactVerificationContext context) { context.verifyInteraction(); } } ``` You will now be able to setup all the required properties using the Spring context, e.g. creating an application YAML file in the test resources: ```yaml pactbroker: host: your.broker.host auth: username: broker-user password: broker.password ``` You can also run pact tests against `MockMvc` without need to spin up the whole application context which takes time and often requires more additional setup (e.g. database). In order to run lightweight tests just use `@WebMvcTest` from Spring and `MockMvcTestTarget` as a test target before each test. For example: ```java @WebMvcTest @Provider(&quot;myAwesomeService&quot;) @PactBroker class ContractVerificationTest { @Autowired private MockMvc mockMvc; @TestTemplate @ExtendWith(PactVerificationInvocationContextProvider.class) void pactVerificationTestTemplate(PactVerificationContext context) { context.verifyInteraction(); } @BeforeEach void before(PactVerificationContext context) { context.setTarget(new MockMvcTestTarget(mockMvc)); } } ``` You can also use `MockMvcTestTarget` for tests without spring context by providing the controllers manually. For example: ```java @Provider(&quot;myAwesomeService&quot;) @PactFolder(&quot;pacts&quot;) class MockMvcTestTargetStandaloneMockMvcTestJava { @TestTemplate @ExtendWith(PactVerificationInvocationContextProvider.class) void pactVerificationTestTemplate(PactVerificationContext context) { context.verifyInteraction(); } @BeforeEach void before(PactVerificationContext context) { MockMvcTestTarget testTarget = new MockMvcTestTarget(); testTarget.setControllers(new DataResource()); context.setTarget(testTarget); } @RestController static class DataResource { @GetMapping(&quot;/data&quot;) @ResponseStatus(HttpStatus.NO_CONTENT) void getData(@RequestParam(&quot;ticketId&quot;) String ticketId) { } } } ``` **Important:** Since `@WebMvcTest` starts only Spring MVC components you can&apos;t use `PactVerificationSpringProvider` and need to fallback to `PactVerificationInvocationContextProvider`

# pact-jvm-consumer-java8 Provides a Java8 lambda based DSL for use with Junit to build consumer tests. # A Lambda DSL for Pact This is an extension for the pact DSL provided by [pact-jvm-consumer](../pact-jvm-consumer). The difference between the default pact DSL and this lambda DSL is, as the name suggests, the usage of lambdas. The use of lambdas makes the code much cleaner. ## Why a new DSL implementation? The lambda DSL solves the following two main issues. Both are visible in the following code sample: ```java new PactDslJsonArray() .array() # open an array .stringValue(&quot;a1&quot;) # choose the method that is valid for arrays .stringValue(&quot;a2&quot;) # choose the method that is valid for arrays .closeArray() # close the array .array() # open an array .numberValue(1) # choose the method that is valid for arrays .numberValue(2) # choose the method that is valid for arrays .closeArray() # close the array .array() # open an array .object() # now we work with an object .stringValue(&quot;foo&quot;, &quot;Foo&quot;) # choose the method that is valid for objects .closeObject() # close the object and we&apos;re back in the array .closeArray() # close the array ``` ### The existing DSL is quite error-prone Methods may only be called in certain states. For example `object()` may only be called when you&apos;re currently working on an array whereas `object(name)` is only allowed to be called when working on an object. But both of the methods are available. You&apos;ll find out at runtime if you&apos;re using the correct method. Finally, the need for opening and closing objects and arrays makes usage cumbersome. The lambda DSL has no ambiguous methods and there&apos;s no need to close objects and arrays as all the work on such an object is wrapped in a lamda call. ### The existing DSL is hard to read When formatting your source code with an IDE the code becomes hard to read as there&apos;s no indentation possible. Of course, you could do it by hand but we want auto formatting! Auto formatting works great for the new DSL! ```java array.object((o) -&gt; { o.stringValue(&quot;foo&quot;, &quot;Foo&quot;); # an attribute o.stringValue(&quot;bar&quot;, &quot;Bar&quot;); # an attribute o.object(&quot;tar&quot;, (tarObject) -&gt; { # an attribute with a nested object tarObject.stringValue(&quot;a&quot;, &quot;A&quot;); # attribute of the nested object tarObject.stringValue(&quot;b&quot;, &quot;B&quot;); # attribute of the nested object }) }); ``` ## Installation ### Maven ``` &lt;dependency&gt; &lt;groupId&gt;au.com.dius&lt;/groupId&gt; &lt;artifactId&gt;pact-jvm-consumer-java8_2.12&lt;/artifactId&gt; &lt;version&gt;${pact.version}&lt;/version&gt; &lt;/dependency&gt; ``` ## Usage Start with a static import of `LambdaDsl`. This class contains factory methods for the lambda dsl extension. When you come accross the `body()` method of `PactDslWithProvider` builder start using the new extensions. The call to `LambdaDsl` replaces the call to instance `new PactDslJsonArray()` and `new PactDslJsonBody()` of the pact library. ```java io.pactfoundation.consumer.dsl.LambdaDsl.* ``` ### Response body as json array ```java import static io.pactfoundation.consumer.dsl.LambdaDsl.newJsonArray; ... PactDslWithProvider builder = ... builder.given(&quot;some state&quot;) .uponReceiving(&quot;a request&quot;) .path(&quot;/my-app/my-service&quot;) .method(&quot;GET&quot;) .willRespondWith() .status(200) .body(newJsonArray((a) -&gt; { a.stringValue(&quot;a1&quot;); a.stringValue(&quot;a2&quot;); }).build()); ``` ### Response body as json object ```java import static io.pactfoundation.consumer.dsl.LambdaDsl.newJsonBody; ... PactDslWithProvider builder = ... builder.given(&quot;some state&quot;) .uponReceiving(&quot;a request&quot;) .path(&quot;/my-app/my-service&quot;) .method(&quot;GET&quot;) .willRespondWith() .status(200) .body(newJsonBody((o) -&gt; { o.stringValue(&quot;foo&quot;, &quot;Foo&quot;); o.stringValue(&quot;bar&quot;, &quot;Bar&quot;); }).build()); ``` ### Examples #### Simple Json object When creating simple json structures the difference between the two approaches isn&apos;t big. ##### JSON ```json { &quot;bar&quot;: &quot;Bar&quot;, &quot;foo&quot;: &quot;Foo&quot; } ``` ##### Pact DSL ```java new PactDslJsonBody() .stringValue(&quot;foo&quot;, &quot;Foo&quot;) .stringValue(&quot;bar&quot;, &quot;Bar&quot;) ``` ##### Lambda DSL ```java newJsonBody((o) -&gt; { o.stringValue(&quot;foo&quot;, &quot;Foo&quot;); o.stringValue(&quot;bar&quot;, &quot;Bar&quot;); }).build(); ``` #### An array of arrays When we come to more complex constructs with arrays and nested objects the beauty of lambdas become visible! ##### JSON ```json [ [&quot;a1&quot;, &quot;a2&quot;], [1, 2], [{&quot;foo&quot;: &quot;Foo&quot;}] ] ``` ##### Pact DSL ```java new PactDslJsonArray() .array() .stringValue(&quot;a1&quot;) .stringValue(&quot;a2&quot;) .closeArray() .array() .numberValue(1) .numberValue(2) .closeArray() .array() .object() .stringValue(&quot;foo&quot;, &quot;Foo&quot;) .closeObject() .closeArray(); ``` ##### Lambda DSL ```java newJsonArray((rootArray) -&gt; { rootArray.array((a) -&gt; a.stringValue(&quot;a1&quot;).stringValue(&quot;a2&quot;)); rootArray.array((a) -&gt; a.numberValue(1).numberValue(2)); rootArray.array((a) -&gt; a.object((o) -&gt; o.stringValue(&quot;foo&quot;, &quot;Foo&quot;))); }).build(); ``` ##### Kotlin Lambda DSL ```kotlin newJsonArray { newArray { stringValue(&quot;a1&quot;) stringValue(&quot;a2&quot;) } newArray { numberValue(1) numberValue(2) } newArray { newObject { stringValue(&quot;foo&quot;, &quot;Foo&quot;) } } } ```