Best Unit Testing Software for Cloud - Page 2

Cantata is a unit and integration testing tool, enabling developers to verify standard compliant or business critical code on host native and embedded target platforms. Cantata helps accelerate compliance with the standard’s dynamic testing requirements by automating test framework generation, test execution. results diagnostics and report generation. Cantata is integrated with an extensive set of embedded development toolchains, from compilers and static analysis tools to build and requirements management tools. The ECLIPSE® GUI, tight tool integrations and tests written in the source C/C++ code, all make Cantata easy to use. Cantata has been independently certified by SGS-TÜV SAAR GmbH for the main software safety standards. Standard specific Cantata tool certification kits are provided free of charge and contain everything needed out-of-the-box as well as comprehensive guidance to help you achieve certification for your device software.

Validate executable specifications against your code on any modern development stack. With over 40 million downloads, Cucumber Open is the world’s #1 automation tool for Behavior-Driven Development. Cucumber Open isn't just open source, it's an open platform that plays well with the tools you already use and love. Works with Java, JavaScript, Ruby, .NET and many other platforms. Store plain text specifications alongside your code in your own source control system. Describe how the system should behave in a way that everybody can understand. Automate with Selenium, API calls or direct function calls in the same process. Generate reports in HTML, JSON and other formats, or build your own reports. Integrate with CucumberStudio, JIRA or build your own plugins. Bridge the gap between business and development using BDD. Decrease rework with test automation. Get real-time insights with living documentation. Seamless integration with Git.

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.

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.

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.

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.

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.

Deequ is a library built on top of Apache Spark for defining "unit tests for data", which measure data quality in large datasets. We are happy to receive feedback and contributions. Deequ depends on Java 8. Deequ version 2.x only runs with Spark 3.1, and vice versa. If you rely on a previous Spark version, please use a Deequ 1.x version (legacy version is maintained in legacy-spark-3.0 branch). We provide legacy releases compatible with Apache Spark versions 2.2.x to 3.0.x. The Spark 2.2.x and 2.3.x releases depend on Scala 2.11 and the Spark 2.4.x, 3.0.x, and 3.1.x releases depend on Scala 2.12. Deequ's purpose is to "unit-test" data to find errors early, before the data gets fed to consuming systems or machine learning algorithms. In the following, we will walk you through a toy example to showcase the most basic usage of our library.

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.

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.

Symflower enhances software development by integrating static, dynamic, and symbolic analyses with Large Language Models (LLMs). This combination leverages the precision of deterministic analyses and the creativity of LLMs, resulting in higher quality and faster software development. Symflower assists in identifying the most suitable LLM for specific projects by evaluating various models against real-world scenarios, ensuring alignment with specific environments, workflows, and requirements. The platform addresses common LLM challenges by implementing automatic pre-and post-processing, which improves code quality and functionality. By providing the appropriate context through Retrieval-Augmented Generation (RAG), Symflower reduces hallucinations and enhances LLM performance. Continuous benchmarking ensures that use cases remain effective and compatible with the latest models. Additionally, Symflower accelerates fine-tuning and training data curation, offering detailed reports.

Gru.ai is an innovative AI-driven platform designed to enhance software development workflows by automating tasks like unit testing, bug fixing, and algorithm development. With tools like Test Gru, Bug Fix Gru, and Assistant Gru, Gru.ai helps developers streamline their processes and improve efficiency. Test Gru automates unit test generation, ensuring superior test coverage while reducing manual effort. Bug Fix Gru automatically identifies and resolves issues directly within your GitHub repositories. Assistant Gru is an AI developer that assists with technical challenges like debugging and coding, delivering reliable and high-quality solutions. Gru.ai is tailored for developers looking to optimize their coding processes and reduce repetitive tasks through the power of AI.

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.

CodeBeaver writes and updates your unit tests. Not only that! It highlights bugs in your Pull Requests by running tests and checking out your code. It works natively with GitHub, GitLab and Bitbucket. The onboarding takes 2 clicks! We currently help 30k GitHub stars and counting.