Best Software Testing Tools for GitLab - Page 2

Harness is an AI-native software delivery platform that helps engineering teams achieve excellence by automating and streamlining the entire software delivery lifecycle. It enables continuous integration, continuous delivery, and GitOps for multi-cloud, multi-region deployments with increased speed and reliability. Harness simplifies infrastructure as code, database DevOps, and artifact management to improve collaboration and reduce errors. The platform offers AI-powered testing, incident response, chaos engineering, and feature management to enhance quality and resilience. Harness also provides cloud cost management, security testing orchestration, and developer insights to optimize performance and governance. Trusted by leading enterprises, Harness accelerates innovation while reducing manual effort and risk.

You can have the best developers in the world, but every test is making them slower. 80% of your software tests are pointless. The problem is you don't know which 80%. We find the right 20% using your data so that you can ship faster. We have shrink-wrapped predictive test selection, a machine learning-based approach being used at companies like Facebook so that it can be used by any company. We support multiple languages, test runners, and CI systems. Just bring Git to the table. Launchable uses machine learning to analyze your test failures and source code. It doesn't rely on code syntax analysis. This means it's trivial for Launchable to add support for almost any file-based programming language. It also means we can scale across teams and projects with different languages and tools. Out of the box, we currently support Python, Ruby, Java, JavaScript, Go, C, and C++, and we regularly add support for new languages.

Software developers typically build source code and run tests on their local machines. EngFlow Remote Execution distributes builds and tests across a cluster of machines and remotely caches the results to make them faster. Review your build and test results on various devices, be it your workstation, laptop — or one of your colleague’s. It’s a game-changer for collaborating remotely. Console output is verbose and convoluted. We split data into views to highlight what you’re looking for. Just in case, one view includes the full console output, streamed live as your builds and tests run. Build and test setups vary on machines. We provide the invocation details for each execution, such as platform, git branch and commit, and implicit and explicit flags set. This lets you reproduce a run, both for debugging and for recreating a prior release.

Perform More Testing in Less Time to Meet Performance Demands Hiperstation provides automated load, performance and regression testing capabilities that help DevOps teams perform more testing in less time and on a more consistent basis while ensuring applications meet production performance and reliability criteria. Hiperstation enables developers to create automated, consistent, repeatable regression and performance tests representing application business requirements. Conduct pre-production performance testing for applications and systems software. Analyze test results in which all application response differences are identified. Thoroughly document mainframe application testing results. Simulate server application responses during a user interface test. Test operating system, language environment or subsystem changes. Test application changes without a user interface.

Today’s speed of change demands a new way of testing. Empower your teams to build smart tests that don’t break and can scale in the cloud. Rapidly create AI powered tests using the smart agent (Architect) or convert steps written in plain-text English into automation using natural language processing. Stop wasting time fixing broken tests. Functionize dynamically updates your tests using machine learning to keep up with UI changes. Quickly diagnose test failures with one-click SmartFix suggestions. Quickly diagnose failures with screenshot comparisons and and easy to understand errors. Interact with your test while it runs live on the VM using breakpoints with Live Debug. Update your tests using Smart Screenshots and apply one-click SmartFix suggestions. Eliminate test infrastructure. Run as many tests as often as needed across all major browsers at scale using Functionize’s Test Cloud.

Apache Yetus is a collection of libraries and tools that enable contribution and release processes for software projects. It provides a robust system for automatically checking new contributions against a variety of community accepted requirements, the means to document a well defined supported interface for downstream projects, and tooling to help release managers generate release documentation based on the information provided by community issue trackers and source repositories. Most of the software is written in shell and scripting languages. In honor of the shell code, the project takes its name. Yetus from a synonym of the Cymbium genus of gastropods. The Yetus Precommit build, patch, and CI suite allows projects to codify their patch acceptance criteria and then evaluate incoming contributions prior to review by a committer. Audience Annotations allows you to use Java Annotations to denote which parts of your Java library is publicly consumable.

DevOps is changing the way that software is delivered. With dozens of builds a day and countless tools used by multiple personas to support the delivery pipelines, software quality risks are increasing and the traditional quality management platforms are no longer fit for purpose. SeaLights identifies, analyzes, and communicates every software quality risk, empowering software teams to deliver quality at speed. SeaLights’ technology automatically identifies, analyzes, and communicates every perceivable Quality Risk across the entire delivery pipeline by continuously collecting telemetry data from all stages of the SDLC. It gives real-time insights in context, to every stakeholder, at every control point. With SeaLights, enterprise software teams can mitigate quality risks, focus their testing efforts where it matters, and protect the integrity of production by continuously collecting telemetry data from all stages of the delivery pipeline, analyzing it, and scoring every risk.

Define a test execution consisting of a tool, test repository, and any arguments/parameters. Run any testing tools out of the box with Testkube-supplied workflows, or build your own custom workflow. Combine similar or dissimilar test execution workflows into suites. Create a searchable repository of ready-to-run test executions. Use proactive triggers to start test executions from CI/CD events, manually or on a schedule. Listen for Kubernetes infrastructure events, such as deployments, to automatically trigger test executions. Leverage Kubernetes native scalability to scale the number of concurrent test executions. Access advanced scaling capabilities to scale load tests from one to 1,000. Parallelize to scale functional tests to speed completion. Access logs and artifacts created by executing test tools in a centralized repository. Quickly find errors with log highlighting of failure-related keywords.

About Provar Provar pairs intuitive testing solutions, including Provar Test Automation and Provar Test Manager, with world-class service to help teams capitalize on their Salesforce investment. Its comprehensive suite of testing products is designed to improve release agility, drive down system defects and advance innovation, meeting people at every stage in their journey — from the individual manual tester to comprehensive QA teams with automated workflows.