Deequ Alternatives

aqua is an AI-powered advanced Test Management System designed to make the QA process painless. It is ideal for enterprises and SMBs across various sectors, although aqua was initially designed specifically for regulated industries like Fintech, MedTech and GovTech. aqua cloud helps to: - Organize custom testing processes and workflows, - Run testing scenarios of any complexity and scale, - Create extended sets of test data, - Ensure thorough insights with rich reporting capabilities and - Go from manual to automated testing smoothly. Additionally, it includes a unique feature called “Capture," which transforms the process of documenting and reproducing bugs into a 1-click action. aqua integrates with all the most popular issue trackers and automation tools like JIRA, Selenium, Jenkins and others. REST API is also available. aqua's streamlines testing and saves your QA team up to 70% of time, enabling you to deliver high-quality software and releases x2 faster!

Parasoft helps organizations continuously deliver high-quality software with its AI-powered software testing platform and automated test solutions. Supporting embedded and enterprise markets, Parasoft’s proven technologies reduce the time, effort, and cost of delivering secure, reliable, and compliant software by integrating everything from deep code analysis and unit testing to UI and API testing, plus service virtualization and complete code coverage, into the delivery pipeline. A powerful unified C and C++ test automation solution for static analysis, unit testing and structural code coverage, Parasoft C/C++test helps satisfy compliance with industry functional safety and security requirements for embedded software systems.

NUnit is a unit-testing framework for all .Net languages. Initially ported from JUnit, the current production release, version 3, has been completely rewritten with many new features and support for a wide range of .NET platforms. The NUnit Project is a member of the .NET Foundation. The .NET Foundation will provide guidance and support to help ensure the future of the project. The success of NUnit has been made possible through the hard work of our many contributors and team members. The Core Team thanks everyone for the help and contributions that have made NUnit the success that it is. At last count, the various NUnit packages passed 126 million downloads on NuGet.org. We couldn't have done that without the dedication of the many volunteers that donate their time and knowledge to the project. NUnit is Open Source software and NUnit 3 is released under the MIT license.

Catch2 is mainly a unit testing framework for C++, but it also provides basic micro-benchmarking features and simple BDD macros. Catch2's main advantage is that using it is both simple and natural. Test names do not have to be valid identifiers, assertions look like normal C++ boolean expressions, and sections provide a nice and local way to share set-up and tear-down code in tests. You are on the devel branch, where the v3 version is being developed. v3 brings a bunch of significant changes, the big one being that Catch2 is no longer a single-header library. Catch2 now behaves as a normal library, with multiple headers and separately compiled implementation. Quick and easy to get started. Just download two files, add them to your project and you're away. No external dependencies. As long as you can compile C++14 and have the C++ standard library available. Write test cases as, self-registering, functions (or methods, if you prefer).

pytest helps you write better programs. The pytest framework makes it easy to write small tests, yet scales to support complex functional testing for applications and libraries. Due to pytest’s detailed assertion introspection, only plain assert statements are used. Detailed info on failing assert statements. Auto-discovery of test modules and functions. Modular fixtures for managing small or parametrized long-lived test resources. Can run unittest (including trial) and nose test suites out of the box. Supports Python 3.6+ and PyPy 3. Rich plugin architecture, with over 315+ external plugins and thriving community. The maintainers of pytest and thousands of other packages are working with Tidelift to deliver commercial support and maintenance for the open source dependencies you use to build your applications. Save time, reduce risk, and improve code health, while paying the maintainers of the exact dependencies you use.

Refraction is a code-generation tool for developers. It uses AI to generate code for you. You can use it to generate unit tests, documentation, refactor code, and more. Generate code using AI in 34 languages — Assembly, C#, C++, CoffeeScript, CSS, Dart, Elixir, Erlang, Go, GraphQL, Groovy, Haskell, HTML, Java, JavaScript, Kotlin, LaTeX, Less, Lua, MatLab, Objective-C, OCaml, Perl, PHP, Python, R Lang, Ruby, Rust, Sass / SCSS, Scala, Shell, SQL, Swift, and TypeScript. Join thousands of developers around the world using Refraction to generate documentation, create unit tests, refactor code, and more using AI. Use the power of AI to automate the tedious parts of software development like testing, documentation, and refactoring, so you can focus on what matters. Refactor, optimize, fix and style-check your code. Generate unit tests for your code with various test frameworks. Explain the purpose of your code to make it easier to understand.

Bright Security is a developer-centric Dynamic Application Security Testing (DAST) solution that helps organizations ship secure applications and APIs quickly and cost-effectively. Its approach enables quick and iterative scans to identify critical security vulnerabilities early in the SDLC without compromising on quality or delivery speed. Bright empowers AppSec teams to provide governance for securing APIs and web apps while allowing developers to take ownership of security testing and remediation work. Unlike legacy DAST solutions built for AppSec professionals, which are complex to deploy and find vulnerabilities late in the development process, Bright's DAST solution is optimized for the DevOps world. It can be deployed as early as the Unit Testing phase and run throughout the SDLC, learning and optimizing from every scan. By enabling organizations to detect and remediate vulnerabilities early in the SDLC, Bright reduces risk at a lower cost and effort.

Meet Agile development cycles while maintaining high-quality code. Use Jtest’s comprehensive set of Java testing tools to ensure defect-free coding through every stage of software development in the Java environment. Streamline Compliance With Security Standards. Ensure your Java code complies with industry security standards. Have compliance verification documentation automatically generated. Release Quality Software, Faster. Integrate Java testing tools to find defects faster and earlier. Save time and money by mitigating complicated and expensive problems down the line. Increase Your Return From Unit Testing. Achieve code coverage targets by creating a maintainable and optimized suite of JUnit tests. Get faster feedback from CI and within your IDE using smart test execution. Parasoft Jtest integrates tightly into your development ecosystem and CI/CD pipeline for real-time, intelligent feedback on your testing and compliance progress.

Continuously build, test, release, and monitor apps for every platform. Connect to GitHub, Bitbucket, GitLab, or Azure DevOps and build your app in the cloud on every commit. Automatically run unit tests, release to testers and stores, or test your UI on real devices. Commit to a feature branch to build and test. Commit to a beta branch to distribute to testers. Commit to master to submit to the App Store. Customize to fit your team’s workflow. Does your app still work after your latest change? How does it perform on an LG G2? Find out by testing your app in a hosted device lab with 1000s of real iOS and Android devices. You’ll receive test results, full-resolution screenshots of every step, along with performance metrics. Whether you prefer private distribution, public open betas, Microsoft Intune, TestFlight, Google Play, or the App Store, App Center makes releasing your app a delight.

The toolkit is provided as a set of artifacts deployed to the Maven Central repository. It requires Java 7 or newer for test execution; tests must use JUnit or TestNG. For instructions on how to add the library to a Java project, see Running tests with JMockit. In this tutorial we examine the APIs available in the library, with the help of example tests (using Java 8). The central API - a single annotation - provides support for the automatic instantiation and initialization of the objects to be tested. Then we have the mocking API (also known as the "Expectations" API), intended for tests which use mocked dependencies. Finally, there is a small faking API (aka the "Mockups" API), which can be used for the creation and application of fake implementations that avoid the full cost of external components.

TestNG is a testing framework inspired from JUnit and NUnit but introducing some new functionalities that make it more powerful and easier to use, such as annotations, or the possibility to run your tests in arbitrarily big thread pools with various policies available (all methods in their own thread, one thread per test class, etc.). You can test that your code is multithread safe, there is flexible test configuration, support for data-driven testing (with @DataProvider), support for parameters, powerful execution model (no more TestSuite). There is a supported by a variety of tools and plug-ins (Eclipse, IDEA, Maven, etc.), it also embeds BeanShell for further flexibility, and there is default JDK functions for runtime and logging (no dependencies), and dependent methods for application server testing. TestNG is designed to cover all categories of tests, unit, functional, end-to-end, integration, etc.

Mockito is a mocking framework that tastes really good. It lets you write beautiful tests with a clean & simple API. Mockito doesn’t give you hangover because the tests are very readable and they produce clean verification errors. Read more about features & motivations. Top 10 Java library across all libraries, not only the testing tools. In late 2013 there was an analysis made of 30.000 GitHub projects. Although Mockito reached number 9 in the main report, mockito-core and mockito-all are the same tool and therefore the factual position of Mockito is number 4, surpassing famous tools like Guava or Spring. Treat this study as an indicator of a big impact that Mockito makes every day on unit tests written in Java.

The powerful, easy-to-use JavaScript testing framework. Easy, zero-configuration setup for any Node.js project and minimal configuration for browser-based projects. Tests can be run anywhere; Node, your browser, even inside a web worker. Test your code where it runs. Flexible APIs for custom assertions, runners, and reporters mean you can extend QUnit to fit your needs. Getting started with QUnit for Node.js projects is quick and easy. First, install the QUnit package using npm. You can now run the test suite through the QUnit CLI. It is recommended that you run the QUnit command via an npm script, which will find the QUnit command automatically from your local dependencies. Check out the API documentation to learn more about the QUnit APIs for organizing tests and making assertions.QUnit follows the Node.js Long-term Support (LTS) schedule and provides support for current, active LTS, and maintenance LTS releases.

Diffblue Cover analyzes your existing Java program and writes unit regression tests that reflect the current behavior of the code. The CLI tool works 100% autonomously, configuring itself from your Maven or Gradle environment. By bringing automation to the test-writing process, the CLI tool provides a speed boost for organizations that are working towards achieving DevOps goals like CI/CD. Since it fits into a CI pipeline, the CLI tool protects the whole codebase from regressions by shifting testing left. Diffblue Cover's unit regression tests run fast and verify new code changes immediately, helping users detect undesirable changes in the code’s behavior as early as possible, when they're the quickest, easiest, and cheapest to fix. And tests are automatically maintained, saving teams even more time.

Storybook provides a sandbox to build UIs in isolation so you can develop hard-to-reach states and edge cases. Implement components and pages without needing to fuss with data, APIs, or business logic. Render components in key states that are tricky to reproduce in an app. Save use cases as stories in plain JavaScript to revisit during development, testing, and QA. Use addons to customize your workflow, automate testing, and integrate with your favorite tools. Stories are a pragmatic, reproducible way to keep track of UI edge cases. Write stories once then reuse them to power automated tests. Whenever you write a story you get a handy test case. Quickly browse stories to make sure your UI looks right. Pinpoint UI changes down to the pixel by comparing image snapshots of stories. Reuse stories in your unit tests to confirm nuanced functionality. Stories show how UIs actually work not just how they're supposed to work. That makes gathering feedback and reproductions easy.

Spark Streaming brings Apache Spark's language-integrated API to stream processing, letting you write streaming jobs the same way you write batch jobs. It supports Java, Scala and Python. Spark Streaming recovers both lost work and operator state (e.g. sliding windows) out of the box, without any extra code on your part. By running on Spark, Spark Streaming lets you reuse the same code for batch processing, join streams against historical data, or run ad-hoc queries on stream state. Build powerful interactive applications, not just analytics. Spark Streaming is developed as part of Apache Spark. It thus gets tested and updated with each Spark release. You can run Spark Streaming on Spark's standalone cluster mode or other supported cluster resource managers. It also includes a local run mode for development. In production, Spark Streaming uses ZooKeeper and HDFS for high availability.

The unittest unit testing framework was originally inspired by JUnit and has a similar flavor as major unit testing frameworks in other languages. It supports test automation, sharing of setup and shutdown code for tests, aggregation of tests into collections, and independence of the tests from the reporting framework. A test fixture represents the preparation needed to perform one or more tests, and any associated cleanup actions. This may involve, for example, creating temporary or proxy databases, directories, or starting a server process. A test suite is a collection of test cases, test suites, or both. It is used to aggregate tests that should be executed together. A test runner is a component which orchestrates the execution of tests and provides the outcome to the user. The runner may use a graphical interface, a textual interface, or return a special value to indicate the results of executing the tests.

Jasmine attempts as best as possible to follow semantic versioning. This means we reserve major versions (1.0, 2.0, etc.) for breaking changes or other significant work. Most Jasmine releases end up being minor releases (2.3, 2.4, etc.). Major releases are very infrequent. Jasmine generally avoids dropping support for browser or Node versions except in major releases. The exceptions to this are Node versions that are past end of life, browsers that we can no longer install locally and/or test against in our CI builds, browsers that no longer receive security updates, and browsers that only run on operating systems that no longer receive security updates. We’ll make reasonable efforts to keep Jasmine working in those environments but won’t necessarily do a major release if they break.

JustMock allows you to easily isolate your testing scenario and lets you focus on the logic you want to verify. It integrates seamlessly with your favorite unit testing framework and makes unit testing and mocking simple and fast. Mock everything like non-virtual methods, sealed classes, static methods and classes, as well as non-public members and types everywhere even members of MsCorLib. The perfect tool for unit testing your .NET code whether you're dealing with complex and hard to maintain legacy code or code written with best practices in mind. From finding what arguments your mock object is called with to why it’s not called or why it’s called repeatedly, the JustMock Debug Window helps you find the answers you are looking for while debugging your unit tests. JustMock allows you to receive critical feedback about the completeness and thoroughness of your unit tests—an absolute must for any organization that strives for high-quality code.

PHPUnit requires the dom and json extensions, which are normally enabled by default. PHPUnit also requires the pcre, reflection, and spl extensions. These standard extensions are enabled by default and cannot be disabled without patching PHP’s build system and/or C sources. The code coverage report feature requires the Xdebug (2.7.0 or later) and tokenizer extensions. Generating XML reports requires the xmlwriter extension. Unit Tests are primarily written as a good practice to help developers identify and fix bugs, to refactor code and to serve as documentation for a unit of software under test. To achieve these benefits, unit tests ideally should cover all the possible paths in a program. One unit test usually covers one specific path in one function or method. However a test method is not necessarily an encapsulated, independent entity. Often there are implicit dependencies between test methods, hidden in the implementation scenario of a test.

The easiest way to unit test. Write tests without changing your code! Even legacy code. Static methods, private methods, non-virtual methods, out parameters and even members and fields. Our professional edition is free for developers around the world. We also have paid support package. Improve your code integrity and deliver quality code. Fake entire object models with a single statement. Mock statics, private, constructors, events, linq, ref args, live, future, static constructors. Our suggest feature creates automated test suggestions suitable for your code. Our smart runner will run only your impact tests and get you super fast feedback. Our coverage feature displays your code coverage in your editor while you code.

Most parts of a software system do not work in isolation, but collaborate with other parts to get their job done. In a lot of cases, we do not care about using real collaborators implementation in unit testing, as we trust these collaborators. Mock objects replace collaborators of the unit under test. To test a unit in isolation or mount a sufficient environment, we have to simulate the collaborators in the test. A Mock Object is a test-oriented replacement for a collaborator. It is configured to simulate the object that it replaces in a simple way. In contrast to a stub, a Mock Object also verifies whether it is used as expected. EasyMock has been the first dynamic Mock Object generator, relieving users of hand-writing Mock Objects, or generating code for them. EasyMock provides Mock Objects by generating them on the fly using Java proxy mechanism.

Appsurify’s patented AI technology determines the areas of an application that have changed after each developer commit and automatically selects and executes just the tests relevant to those changed areas in the CI Pipeline. Appsurify selects and executes only the small subset of tests impacted on a per developer change basis. Optimize CI Pipelines by removing automation testing as a bottleneck and let Builds run faster and more efficiently. Automation Testing and CI Pipelines are slowing productivity by taking too long to complete, delaying important feedback to catch bugs, and pushing release schedules back. With Appsurify, QA & DevOps work is streamlined by allowing focused test execution in only the areas that matter to catch bugs early and keep CI/CD pipelines running smoothly and efficiently.

HUnit is a unit testing framework for Haskell, inspired by the JUnit tool for Java. It's easy to use HUnit, assuming you are familiar with Haskell, though not necessarily with JUnit. A test-centered methodology for software development is most effective when tests are easy to create, change, and execute. The JUnit tool pioneered support for test-first development in Java. HUnit is an adaptation of JUnit to Haskell, a general-purpose, purely functional programming language. With HUnit, as with JUnit, you can easily create tests, name them, group them into suites, and execute them, with the framework checking the results automatically. Test specification in HUnit is even more concise and flexible than in JUnit, thanks to the nature of the Haskell language. HUnit currently includes only a text-based test controller, but the framework is designed for easy extension. Run the tests as a group.

Allows for collaborative parallel development to minimize rework, visualize and reduce conflict, and lower risk while improving team velocity and throughput. Preserves the integrity of known baseline configurations, simplifies rollback and recovery, streamlines approval, and maintains integrity when automating builds and deployments. Identifying issues earlier in the lifecycle saves considerable time and effort. CM allows issues to be identified as soon as a code commit occurs via Pulse. CI build, unit test and code review all drive shift left actions. Features integration with developer friendly repositories and IDEs (such as Git, IntelliJ, Eclipse and Microsoft .net), detailed auditing and logging, and immutable versioning and history. Minimizes the preparation and effort required for audits and regulatory compliance with comprehensive and tamperproof history and audit trails.

Confident AI offers an open-source package called DeepEval that enables engineers to evaluate or "unit test" their LLM applications' outputs. Confident AI is our commercial offering and it allows you to log and share evaluation results within your org, centralize your datasets used for evaluation, debug unsatisfactory evaluation results, and run evaluations in production throughout the lifetime of your LLM application. We offer 10+ default metrics for engineers to plug and use.

Empower everyone on the team to perform robust automated testing on desktop, web and mobile applications, regardless of their experience with functional test automation tools. Ranorex Studio is an all-in-one solution that includes tools for codeless automation as well as a full IDE. With our industry-leading object recognition and shareable object repository, Ranorex Studio makes it possible to automate GUI testing for even the most challenging interfaces, from legacy applications to the latest web and mobile technologies. Ranorex Studio supports cross-browser testing with built-in Selenium WebDriver integration. Perform effortless data-driven testing using CSV files, Excel spreadsheets or SQL database files as input. Ranorex Studio also supports keyword-driven testing: our tools for collaboration allow test automation engineers to build reusable code modules and share them with the team. Download our free 30-day trial for a risk-free start to test automation.

AppHarbor is a fully hosted .NET Platform as a Service. AppHarbor can deploy and scale any standard .NET application to the cloud. AppHarbor is used by thousands of developers and businesses to host anything from personal blogs to high traffic web applications. AppHarbor lets you instantly deploy and scale .NET applications using your favorite versioning tool. Installing add-ons is just as easy. You push .NET and Windows code to AppHarbor using Git, Mercurial, Subversion or Team Foundation Server with the complimentary Git service or through integrations offered in collaboration with Bitbucket, CodePlex and GitHub. When AppHarbor receives your code it will be built by a build server. If the code compiles all unit tests contained in the compiled assemblies will be run. The result and progress of the build and unit test status can be monitored on the application dashboard. AppHarbor will call any service hooks that you add to notify you of the build result.

Our platform intelligently understands your code, seamlessly executing edge cases within your coding environment, ensuring the prompt delivery of impeccable software. Experience accelerated delivery of flawless software with UnitWise at your fingertips. Say goodbye to the tedious process of manually creating test cases and the reliance on prompts for generating test codes. As you delve into coding, UnitWise becomes your steadfast testing companion, providing real-time and pertinent test codes to streamline your development journey. Select the class to test and generate test cases within your IDE in a single click. View the failed test case behaviors and fix the test to eliminate errors. Identify code bugs, enhancing software reliability, while seamlessly correcting identified code issues. We prioritize data security, ensuring the steadfast integrity and exclusivity of your code are meticulously upheld.

Unlock insights from all your data and build artificial intelligence (AI) solutions with Azure Databricks, set up your Apache Spark™ environment in minutes, autoscale, and collaborate on shared projects in an interactive workspace. Azure Databricks supports Python, Scala, R, Java, and SQL, as well as data science frameworks and libraries including TensorFlow, PyTorch, and scikit-learn. Azure Databricks provides the latest versions of Apache Spark and allows you to seamlessly integrate with open source libraries. Spin up clusters and build quickly in a fully managed Apache Spark environment with the global scale and availability of Azure. Clusters are set up, configured, and fine-tuned to ensure reliability and performance without the need for monitoring. Take advantage of autoscaling and auto-termination to improve total cost of ownership (TCO).

The AgitarOne product family helps you work safer, better, and smarter as you develop and maintain your Java applications. AgitarOne JUnit Generator creates thorough JUnit tests on your code. This helps you find regressions and makes it safer and easier to improve your code to reduce the cost to maintain it. AgitarOne Agitator helps developers understand the behavior of their code as they write it. This helps you prevent bugs and prevent code complexity that can become tomorrow's maintenance headache. The AgitarOne family is the best available way to create, use, and manage the unit tests that you need to be truly agile. Automated JUnit Generation, you can automate the generation of JUnit tests to create a "safety net" before you start working with existing code. You can automate the generation of JUnit tests to create a "safety net" before you start working with existing code.

Scapy is a powerful interactive packet manipulation program. It is able to forge or decode packets of a wide number of protocols, send them on the wire, capture them, match requests and replies, and much more. It can easily handle most classical tasks like scanning, tracerouting, probing, unit tests, attacks, or network discovery (it can replace hping, 85% of nmap, arpspoof, arp-sk, arping, tcpdump, tshark, p0f, etc.). It also performs very well at a lot of other specific tasks that most other tools can’t handle, like sending invalid frames, injecting your own 802.11 frames, combining technics (VLAN hopping+ARP cache poisoning, VOIP decoding on WEP encrypted channel), etc. Scapy runs natively on Linux, Windows, OSX, and on most Unixes with libpcap. The same code base now runs natively on both Python 2 and Python 3. Scapy development uses the Git version control system. Scapy reference repository is hosted on GitHub.

WireMock is a simulator for HTTP-based APIs. Some might consider it a service virtualization tool or a mock server. It enables you to stay productive when an API you depend on doesn't exist or isn't complete. It supports testing of edge cases and failure modes that the real API won't reliably produce. And because it's fast it can reduce your build time from hours down to minutes. MockLab is a hosted API simulator built on WireMock, with an intuitive web UI, team collaboration and nothing to install. The 100% compatible API supports drop-in replacement of the WireMock server with a single line of code. Run WireMock from within your Java application, JUnit test, Servlet container or as a standalone process. Match request URLs, methods, headers cookies and bodies using a wide variety of strategies. First class support for JSON and XML. Get up and running quickly by capturing traffic to and from an existing API.

Nova AI automates many of the non-productive testing tasks that developers face during implementation. Our solutions work behind the scenes and complete these tasks without your developers having to use different interfaces or tools. Automatically generate and execute unit, integration, and end-to-end tests from a single platform. Both current and newly generated tests are executed, with results and insights surfaced. All your data is completely isolated and we never share it. We've enabled SSL-encrypted transit and industry-standard 256-bit AES encrypted at rest, and SOC 2 Type 2 is in progress.

Testing and test data management for IBM i, IBM iSeries, AS/400. Complex IBM i applications must be checked from top to bottom, right into the data, wherever it is. TestBench IBM i is a comprehensive, proven test data management, verification and unit testing solution that integrates with other solutions for total application quality. Stop copying the entire live database and hone in on the data you really need. Select or sample data with full referential integrity preserved. Simply decide which fields need to be protected and use a variety of obfuscation methods to protect your data. Track every insert, update and delete including intervening data states. Create rules so that data failures are flagged to you automatically. Avoid the painful save/restores and stop attempting to explain bad test results based on poor initial data. Comparing outputs is a well proven method to verify your test results but it can be laborious and prone to error. This unique solution can save hours.

Writing unit tests can be hard and sometimes good design has to be sacrificed for the sole purpose of testability. Often testability corresponds to good design, but this is not always the case. For example final classes and methods cannot be used, private methods sometimes need to be protected or unnecessarily moved to a collaborator, static methods should be avoided completely and so on simply because of the limitations of existing frameworks. PowerMock is a framework that extends other mock libraries such as EasyMock with more powerful capabilities. PowerMock uses a custom classloader and bytecode manipulation to enable mocking of static methods, constructors, final classes and methods, private methods, removal of static initializers and more. By using a custom classloader no changes need to be done to the IDE or continuous integration servers which simplifies adoption.

The LDRA tool suite is LDRA’s flagship platform that delivers open and extensible solutions for building quality into software from requirements through to deployment. The tool suite provides a continuum of capabilities including requirements traceability, test management, coding standards compliance, code quality review, code coverage analysis, data-flow and control-flow analysis, unit/integration/target testing, and certification and regulatory support. The core components of the tool suite are available in several configurations that align with common software development needs. A comprehensive set of add-on capabilities are available to tailor the solution for any project. LDRA Testbed together with TBvision provide the foundational static and dynamic analysis engine, and a visualization engine to easily understand and navigate standards compliance, quality metrics, and code coverage analyses.

Reducing the time, cost, risk, uncertainty, and stress of DataStage delivery. Ensure all jobs comply with your coding standards, or use MettleCI's extensive library of best practices. Manage code in Git, directly from the DataStage Designer client, without any command line headaches. Promote your code from Development to Production using a fully-automated delivery pipeline. Give sequences the boot and allow MettleCI to build and run your job schedule automatically. Let MettleCI handle the heavy lifting of testing to ensure your builds are deployable without problems. No command lines, hacking, or complex config files. Test, build, and deploy using point-and-click.

Apache Mahout is a powerful, scalable, and versatile machine learning library designed for distributed data processing. It offers a comprehensive set of algorithms for various tasks, including classification, clustering, recommendation, and pattern mining. Built on top of the Apache Hadoop ecosystem, Mahout leverages MapReduce and Spark to enable data processing on large-scale datasets. Apache Mahout(TM) is a distributed linear algebra framework and mathematically expressive Scala DSL designed to let mathematicians, statisticians, and data scientists quickly implement their own algorithms. Apache Spark is the recommended out-of-the-box distributed back-end or can be extended to other distributed backends. Matrix computations are a fundamental part of many scientific and engineering applications, including machine learning, computer vision, and data analysis. Apache Mahout is designed to handle large-scale data processing by leveraging the power of Hadoop and Spark.

Most things that you can do manually in the browser can be done using Puppeteer! Puppeteer-core is intended to be a lightweight version of Puppeteer for launching an existing browser installation or for connecting to a remote one. Be sure that the version of puppeteer-core you install is compatible with the browser you intend to connect to. Puppeteer will be familiar to people using other browser testing frameworks. You create an instance of Browser, open pages, and then manipulate them with Puppeteer's API. By default, Puppeteer downloads and uses a specific version of Chromium so its API is guaranteed to work out of the box. To use Puppeteer with a different version of Chrome or Chromium, pass in the executable's path when creating a Browser instance.

xUnit.net is a free, open source, community-focused unit testing tool for the .NET Framework. Written by the original inventor of NUnit v2, xUnit.net is the latest technology for unit testing C#, F#, VB.NET and other .NET languages. xUnit.net works with ReSharper, CodeRush, TestDriven.NET and Xamarin. It is part of the .NET Foundation, and operates under their code of conduct.

Embunit is a unit testing tool for programmers and testers developing software in C or C++. It is aimed at embedded software development, but can be used to create unit tests for any software written in C or C++. Embunit eliminates the mundane, repetitive aspects of writing unit tests, leaving you free to concentrate on defining the test behaviour. This is achieved by specifying a sequence of actions as shown in the example screenshot below. Embunit generates the unit test source code automatically. Embunit has been developed with flexibility in mind, and can be customised to create unit tests for virtually any hardware platform; even the smallest microcontrollers. It is not tied to any specific toolset and is designed to accommodate the common limitations of embedded C++ compilers.

dbForge Unit Tests for SQL Server is a GUI-based tool available as an add-in for SQL Server Management Studio. This tool enables users to implement and automate unit testing directly within SSMS. Key Features: - Isolated unit testing to avoid affecting the actual database - Writing unit tests in T-SQL without additional tools - Simple installation and uninstalling of the tSQLt framework for writing unit tests - Performing multiple unit tests simultaneously - Integrating unit tests into DevOps processes - Running unit tests via the command line - Access to the collection of unit test examples - Safe refactoring in large databases The tool features a Test List Manager, a separate tab within the SSMS interface for creating, editing, managing, and running unit tests. This integration allows teams to stay within SSMS, eliminating the need for learning and switching between different tools, thus supporting a more comfortable environment and efficient performance.

Create and run unit tests, performance tests, and UI tests for your Xcode project. Use the XCTest framework to write unit tests for your Xcode projects that integrate seamlessly with Xcode's testing workflow. Tests assert that certain conditions are satisfied during code execution, and record test failures (with optional messages) if those conditions aren’t satisfied. Tests can also measure the performance of blocks of code to check for performance regressions and can interact with an application's UI to validate user interaction flows. A test method is a small, self-contained method that tests a specific part of your code. A test case is a group of related test methods. Add test cases and test methods to a test target to confirm that your code performs as expected. The primary class for defining test cases, test methods, and performance tests. An abstract base class for creating, managing, and executing tests.

dotCover is a .NET unit testing and code coverage tool that works right in Visual Studio and in JetBrains Rider, helps you know to what extent your code is covered with unit tests, provides great ways to visualize code coverage, and is Continuous Integration ready. dotCover calculates and reports statement-level code coverage in applications targeting .NET Framework, .NET Core, Mono for Unity, etc. dotCover is a plug-in to Visual Studio and JetBrains Rider, giving you the advantage of analyzing and visualizing code coverage without leaving the code editor. This includes running unit tests and analyzing coverage results right in the IDEs, as well as support for different color themes, new icons and menus. dotCover comes bundled with a unit test runner that it shares with another JetBrains tool for .NET developers, ReSharper. dotCover supports continuous testing, a modern unit testing workflow whereby dotCover figures out on-the-fly which unit tests are affected by your code changes.

TESSY automates the whole unit test cycle including regression testing for your embedded software in C/C++ on different target systems. As an easy-to-install and easy-to-operate testing tool TESSY guides you through the unit test workflow from the project setup through the test design and execution to the result analysis and reporting. TESSY takes additional care of the complete test organization as well as the test management, including requirements, coverage measurement, and traceability. The TESSY test project management feature provides the possibility to define an individual test project structure based on collections and folders, to define environment variables, and to configure your desired compiler/debugger with the help of the integrated Test Environment Editor. The coverage results are displayed directly within the project structure and the test results are stored within test runs which allows for keeping former (successful) results for reporting.

Mocha runs in the browser. Every release of Mocha will have new builds of ./mocha.js and ./mocha.css for use in the browser. By adding an argument (usually named done) to it() to a test callback, Mocha will know that it should wait for this function to be called to complete the test. This callback accepts both an Error instance (or subclass thereof) or a falsy value; anything else is invalid usage and throws an error (usually causing a failed test). These reporters expect Mocha to know how many tests it plans to run before execution. This information is unavailable in parallel mode, as test files are loaded only when they are about to be run. In serial mode, tests results will “stream” as they occur. In parallel mode, reporter output is buffered; reporting will occur after each file is completed. In practice, the reporter output will appear in “chunks” (but will otherwise be identical). If a test file is particularly slow, there may be a significant pause while it’s running.

Apache Spark™ is a unified analytics engine for large-scale data processing. Apache Spark achieves high performance for both batch and streaming data, using a state-of-the-art DAG scheduler, a query optimizer, and a physical execution engine. Spark offers over 80 high-level operators that make it easy to build parallel apps. And you can use it interactively from the Scala, Python, R, and SQL shells. Spark powers a stack of libraries including SQL and DataFrames, MLlib for machine learning, GraphX, and Spark Streaming. You can combine these libraries seamlessly in the same application. Spark runs on Hadoop, Apache Mesos, Kubernetes, standalone, or in the cloud. It can access diverse data sources. You can run Spark using its standalone cluster mode, on EC2, on Hadoop YARN, on Mesos, or on Kubernetes. Access data in HDFS, Alluxio, Apache Cassandra, Apache HBase, Apache Hive, and hundreds of other data sources.

Ensure the quality of your application without sacrificing speed or agility with an easy-to-use, GUI test automation tool. Our AI-powered object recognition engine and script or scriptless flexibility is unmatched, letting you test every desktop, web, and mobile application with ease. TestComplete comes with an intelligent object repository and support for over 500 controls, so you can ensure your GUI tests are scalable, robust, and easy to maintain. More automated quality means more overall quality. Automate UI testing across a wide range of desktop applications, including .Net, Java, WPF and Windows 10. Create reusable tests for all web applications including modern JavaScript frameworks like React and Angular on 2050+ browser and platform configurations. Create and automate functional UI tests on physical or virtual iOS and Android devices. No need to jailbreak your phone.

Try your first CodeRush feature right now and see instantly just how powerful it is. Refactoring for C#, Visual Basic, and XAML, with the fastest test .NET runner available, next generation debugging, and the most efficient coding experience on the planet. Quickly find symbols and files in your solution and easily navigate to code constructions related to the current context. CodeRush includes the Quick Navigation and Quick File Navigation features, which make it fast and easy to find symbols and open files. Using the Analyze Code Coverage feature, you can discover what parts of your solution are covered by unit tests, and find the at-risk parts of your application. The Code Coverage window shows percentage of statements covered by unit tests for each namespace, type, and member in your solution.