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Advanced Library to Remove Object Relational Impedance. DBvolution translates all database concepts into Object Oriented concepts, allowing you to spend all your time writing Java rather than fixing broken and awkward SQL. DBvolution transforms your schema into classes, reduces the database configuration to sparse annotations on the classes, and allows querying directly from the classes. Queries are created inside your java code and takes as little as one line for a multi-table outer join. Retrieving the rows from the query is only one more method call. Dozens of SQL functions are available without leaving your Java code and use chaining to build complex expressions easily. Transactions are encapsulated into a thread-like API, allowing you to write complex database interactions in complete safety. The queries performed by DBvolution are always available for debugging and checking by DBAs before release. There are examples in nz.co.gregs.dbvolution.examples, and documentation at http://dbvolution.gregs.co.nz.

Advanced Library to Remove Object Relational Impedance. DBvolution translates all database concepts into Object Oriented concepts, allowing you to spend all your time writing Java rather than fixing broken and awkward SQL. DBvolution transforms your schema into classes, reduces the database configuration to sparse annotations on the classes, and allows querying directly from the classes. Queries are created inside your java code and takes as little as one line for a multi-table outer join. Retrieving the rows from the query is only one more method call. Dozens of SQL functions are available without leaving your Java code and use chaining to build complex expressions easily. Transactions are encapsulated into a thread-like API, allowing you to write complex database interactions in complete safety. The actions performed by DBvolution are always available for debugging and checking by DBAs before release. There are examples in nz.co.gregs.dbvolution.examples, and documentation at http://dbvolution.gregs.co.nz and http://sourceforge.net/p/dbvolution/blog/

ThreadFix is a software vulnerability aggregation and management system that reduces the time it takes to fix software vulnerabilities. ThreadFix imports the results from dynamic, static and manual testing to provide a centralized view of software security defects across development teams and applications. The system allows companies to correlate testing results and streamline software remediation efforts by simplifying feeds to software issue trackers. By auto generating application firewall rules, this tool allows organizations to continue remediation work uninterrupted. ThreadFix empowers managers with vulnerability trending reports that show progress over time, giving them justification for their efforts. ThreadFix is developed and maintained by Denim Group, Ltd (http://www.denimgroup.com) For information about commercial support and other services, contact Denim Group about ThreadFix http://www.denimgroup.com/resources-threadfix/

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.

The Source Analyst library is a powerful tool designed to streamline and expedite the tracking of traffic sources for mobile applications. This versatile library is aptly named "Source Analyst" and is an invaluable asset for app developers and marketers seeking to gain deeper insights into the performance of their advertising campaigns. With just one simple function call, Source Analyst empowers you to efficiently investigate the effectiveness of various advertising sources. Key Features: Effortless Tracking: Source Analyst simplifies the complex task of tracking the origins of traffic for your mobile app. No need for convoluted setups or extensive coding – one function is all it takes. Comprehensive Insights: Gain a comprehensive understanding of where your app's users are coming from. Whether it's through social media, search engines, referral links, or other channels, Source Analyst provides you with clear data on traffic sources. Performance Evaluation: Evaluate the performance of your advertising campaigns with precision. Discover which sources are driving the most valuable users to your app, helping you optimize your marketing efforts effectively. Time-Saving: Say goodbye to hours spent on manual data collection and analysis. Source Analyst automates the tracking process, freeing up your time to focus on making data-driven decisions. Customization: Tailor Source Analyst to your specific needs. Customize the library to track the metrics that matter most to your app's success. Real-time Data: Access real-time data, ensuring that you always have up-to-date insights into your traffic sources. Integration-Friendly: Seamlessly integrate Source Analyst into your existing mobile app infrastructure, whether you're developing for Android or iOS. User-Friendly: Source Analyst is designed with user-friendliness in mind. Its intuitive interface and straightforward documentation make it accessible to developers of all levels of expertise. How It Works: Using Source Analyst is as easy as calling a single function within your code. Simply integrate the library into your app, and you can begin tracking traffic sources immediately. From there, Source Analyst compiles and presents the data in a clear and organized manner, allowing you to make data-driven decisions with ease. In a world where understanding the origins of your app's traffic is essential for marketing success, Source Analyst is the go-to solution. Say goodbye to the complexity of tracking sources and embrace the simplicity and effectiveness of Source Analyst for your mobile app. Harness the power of Source Analyst and unlock a new level of insight into your app's performance today!

Mahout's goal is to build scalable machine learning libraries. With scalable we mean: Scalable to reasonably large data sets. Our core algorithms for clustering, classification and batch based collaborative filtering are implemented on top of Apache Hadoop using the map/reduce paradigm. However we do not restrict contributions to Hadoop based implementations: Contributions that run on a single node or on a non-Hadoop cluster are welcome as well. The core libraries are highly optimized to allow for good performance also for non-distributed algorithms. Scalable to support your business case. Mahout is distributed under a commercially friendly Apache Software license. Scalable community. The goal of Mahout is to build a vibrant, responsive, diverse community to facilitate discussions not only on the project itself but also on potential use cases. Come to the mailing lists to find out more. Currently Mahout supports mainly four use cases: Recommendation mining takes users' behavior and from that tries to find items users might like. Clustering takes e.g. text documents and groups them into groups of topically related documents. Classification learns from existing categorized documents what documents of a specific category look like and is able to assign unlabelled documents to the (hopefully) correct category. Frequent itemset mining takes a set of item groups (terms in a query session, shopping cart content) and identifies, which individual items usually appear together.

# 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("Animal Profile Service") @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("myAwesomeService") @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("myAwesomeService") @PactFolder("pacts") 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("/data") @ResponseStatus(HttpStatus.NO_CONTENT) void getData(@RequestParam("ticketId") String ticketId) { } } } ``` **Important:** Since `@WebMvcTest` starts only Spring MVC components you can't use `PactVerificationSpringProvider` and need to fallback to `PactVerificationInvocationContextProvider`

# Pact Junit 5 Extension ## Overview For writing 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 one of the pact source annotations to your test class (as per a JUnit 4 test), then add a method annotated with `@TestTemplate` and `@ExtendWith(PactVerificationInvocationContextProvider.class)` that takes a `PactVerificationContext` parameter. You will need to call `verifyInteraction()` on the context parameter in your test template method. For example: ```java @Provider("myAwesomeService") @PactFolder("pacts") public class ContractVerificationTest { @TestTemplate @ExtendWith(PactVerificationInvocationContextProvider.class) void pactVerificationTestTemplate(PactVerificationContext context) { context.verifyInteraction(); } } ``` For details on the provider and pact source annotations, refer to the [Pact junit runner](../pact-jvm-provider-junit/README.md) docs. ## Test target You can set the test target (the object that defines the target of the test, which should point to your provider) on the `PactVerificationContext`, but you need to do this in a before test method (annotated with `@BeforeEach`). There are three different test targets you can use: `HttpTestTarget`, `HttpsTestTarget` and `AmpqTestTarget`. For example: ```java @BeforeEach void before(PactVerificationContext context) { context.setTarget(HttpTestTarget.fromUrl(new URL(myProviderUrl))); // or something like // context.setTarget(new HttpTestTarget("localhost", myProviderPort, "/")); } ``` ## Provider State Methods Provider State Methods work in the same way as with JUnit 4 tests, refer to the [Pact junit runner](../pact-jvm-provider-junit/README.md) docs. ## Modifying the requests before they are sent **Important Note:** You should only use this feature for things that can not be persisted in the pact file. By modifying the request, you are potentially modifying the contract from the consumer tests! Sometimes you may need to add things to the requests that can't be persisted in a pact file. Examples of these would be authentication tokens, which have a small life span. The Http and Https test targets support injecting the request that will executed into the test template method. You can then add things to the request before calling the `verifyInteraction()` method. For example to add a header: ```java @TestTemplate @ExtendWith(PactVerificationInvocationContextProvider.class) void testTemplate(PactVerificationContext context, HttpRequest request) { // This will add a header to the request request.addHeader("X-Auth-Token", "1234"); context.verifyInteraction(); } ``` ## Objects that can be injected into the test methods You can inject the following objects into your test methods (just like the `PactVerificationContext`). They will be null if injected before the supported phase. | Object | Can be injected from phase | Description | | ------ | --------------- | ----------- | | PactVerificationContext | @BeforeEach | The context to use to execute the interaction test | | Pact | any | The Pact model for the test | | Interaction | any | The Interaction model for the test | | HttpRequest | @TestTemplate | The request that is going to be executed (only for HTTP and HTTPS targets) | | ProviderVerifier | @TestTemplate | The verifier instance that is used to verify the interaction |

This module contains a more general approach to construct AlignmentAlgorithms by relying on the theoretical concept of Algebraic Dynamic Programming (ADP) as developed by Giegerich et al. ADP defines four ingredients for an alignment algorithm: 1.) A signature that defines the permitted alignment operations. Operations are just function templates with an associated arity, meaning the number of arguments it takes from the left sequence and from the right sequence. In the TCSAlignmentToolbox we have a fixed signature with the following operations: REPLACEMENT(1, 1), DELETION(1, 0), INSERTION(0, 1), SKIPDELETION(1, 0) and SKIPINSERTION(0, 1) 2.) A regular tree grammar that produces alignments, that is: sequences of operations, in a restricted fashion. 3.) An algebra that can translate such trees to a cost. In the TCSAlignmentToolbox this is a Comparator. 4.) A choice function, in case of the TCSAlignmentToolbox: the strict minimum or the soft minimum. An alignment algorithm in the TCSAlignmentToolbox sense of the word then is the combination of choice function and grammar. While we provide hardcoded versions of these combinations in the main package, the adp package allows you to create your own grammars. You can combine them with a choice function by instantiating one of the Algorithm classes provided in this package with a grammar of your choice. For example: AlignmentAlgorithm algo = new SoftADPScoreAlgorithm(my_grammar, comparator); creates an alignment algorithm that implicitly produces all possible alignments your grammar can construct with the given input, translates them to a cost using the algebra/comparator you provided and applies the soft minimum to return the score. This all gets efficient by dynamic programming. Note that there is runtime overhead when using this method in comparison with the hardcoded algorithms. But for complicated grammars this is a much easier way to go. For more information on the theory, please refer to my master's thesis: "Adaptive Affine Sequence Alignment using Algebraic Dynamic Programming"