InfoQ Homepage Automated testing Content on InfoQ
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Exploring AI's Role in Automating Software Testing
QA professionals are increasingly turning to AI to address the growing complexities of software testing. AI-driven automation can improve test coverage, reduce test cycle times, and enhance the accuracy of results, leading to faster software releases with higher quality.
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How Slack Used an AI-Powered Hybrid Approach to Migrate from Enzyme to React Testing Library
Enzyme’s lack of support for React 18 made their existing unit tests unusable and jeopardized the foundational confidence they provided, Sergii Gorbachov said at QCon San Francisco. He showed how Slack migrated all Enzyme tests to React Testing Library (RTL) to ensure the continuity of their test coverage.
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The Value of Using Timeless Testing Tools
According to Benjamin Bischoff, developers find new tools much more interesting than old ones, as they offer an opportunity to learn new technologies and approaches and to expand their tool belt. Using tools that have been around for decades, however, can save time and budget. When evaluating tools, it is more important to understand the problem to be solved than to jump straight into the tools.
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How Testing in the Metaverse Looks
The "metaverse" typically refers to a collective virtual shared space that is created by the convergence of a virtually enhanced physical reality and a persistent virtual reality. According to Jonathon Wright, testing requires a mix of manual testing, automated testing, user testing, emulators, and simulators. Real-world testing environments are used to cover as many scenarios as possible.
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Improving Mobile Test Automation with Continuous Integration, Central Logging, and Metrics Analysis
Continuous integration can enhance automated mobile testing. Test data from multiple mobile devices running parallel tests can be consolidated to support monitoring. Jira tickets from manual testing can trigger the build process to ensure that testers will have the correct software version to do the manual testing.
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MSTest 3.4 Release: Improved Analyzers, WinUI, Playwright and Aspire Support Added
Microsoft released a new version of MSTest, a testing framework for .NET. Version 3.4 introduces a couple of improvements, bug fixes, and new features. Key updates include improvements to MSTest.Analyzers, MSTest.Sdk, and MSTest.Runner, along with added support for WinUI applications.
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Netflix Announces SafeTest, Its Custom Approach to Front-End Testing
Moshe Kolodny recently introduced SafeTest, described as a novel approach to front-end web testing. SafeTest orchestrates a test runner, a browser automation library, a UI framework, and dependency injection capabilities to alleviate the pain points of traditional UI testing methods. SafeTest is currently used at Netflix.
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OpenTofu 1.6.0 Now Generally Available: New Module Testing, Enhanced S3 Backend, and Many More
OpenTofu 1.6.0 is now generally available. A community-driven open-source fork of Terraform under the Linux Foundation, now offers a stable release with many features, including advanced testing features for configurations and modules, enhanced S3 state backend with new authentication methods, a new provider and module registry, and many more improvements and bug fixes.
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Microsoft Playwright Testing: Scalable End-to-End Testing for Modern Web Apps
Microsoft recently announced the public preview of Microsoft Playwright Testing, a new service for running Playwright tests at scale through Azure.
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Terraform 1.6 Makes Testing Framework Generally Available
HashiCorp has released Terraform 1.6 with several new improvements including a new testing framework. Additional improvements include changes to config-driven import, Terraform Cloud CLI workflows, and the Amazon S3 backend. This version marks the first release of Terraform to be under the Business Source License v1.1 (BSL 1.1).
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Testing across a Large Number of Inputs with Property-Based Testing
Property-based testing is an approach that involves specifying statements that should always be true, rather than relying on specific examples. It enables you to test functions across a large number of inputs with fewer tests. Every run of a property-based test will use different inputs, which can give you confidence your code works in a general case.
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How Airbnb Improved its CI Pipeline for iOS Using AWS and Terraform
AirBnb has historically managed its own fleet of Macs to run its iOS continuous integration pipeline. Thanks to AWS providing support for Macs, AirBnb engineers could migrate their iOS CI infrastructure to AWS to increase flexibility, consistency, and efficiency.
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Programming Foundations for Test Automation
Proper programming foundations can improve your test automation, making it easier to maintain testing code, and reduce stress. A foundation of the theory and basic principles of coding and programming can help to bring test automation to the next level. Object-oriented programming principles can help to overcome code smells.
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Generating Text Inputs for Mobile App Testing Using GPT-3
A group of researchers from the Chinese Academy of Sciences and Monash University have presented a new approach to text input generation for mobile app testing based on a pre-trained large language model (LLM). Dubbed QTypist, the approach was evaluated on 106 Android apps and automated test tools, showing a significant improvement of testing performance.
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Scalable Automation Frameworks for Functional and Non-Functional Testing
Separating the capabilities of a testing framework from the actual tests can enable scaling automated testing for complex enterprise products. According to Alexander Velinov, we should agree on the types of tests to execute automatically during release and what should be kept as manually triggered tests.