The Open Testing Platform™ (OTP) is a collaboration hub that assists testers to keep pace with change. It transforms observations from the surrounding Dev-Test infrastructure into action enabling the organisation to test faster, smarter and at a much lower cost. The OTP is also testing tool agnostic, it works with over 100 different open-source and proprietary tools.
The Value of Using The Open Testing Platform
Siloes and manual processes have become a burden to software delivery teams, leading to costly delays in the software delivery lifecycle (SDLC) and exposing business-critical systems to damaging bugs. Comprehensive automation and rigorous in-sprint testing should be considered a key goal for software delivery teams looking to keep pace with agile development. Therefore, organisations that leverage multiple open-source or proprietary testing tools must consider the Open Testing Platform to keep pace with agile and enterprise DevOps initiatives.
The Open Testing Platform can facilitate complete test automation and cutting-edge data analysis to help software teams match the pace of agile development. Furthermore, in the OTP these tools are combined within a complete solution for prioritizing and generating the tests that matter before the next release. Curiosity’s Open Testing Platform is that complete solution, built from the ground up to remove burdens for software delivery teams and enable truly agile development.
Interested in how the Open Testing Platform helps maintain rigorous test automation in-sprint? Learn how to achieve complete test automation by reading Curiosity’s latest eBook; Sustainable Test Automation: Should you hire more people or buy “another testing tool”?
Curiosity’s Open Testing Platform
Curiosity’s OTP is built to facilitate agile development, removing the burdens weighing software delivery teams down. The OTP does this by harnessing the latest data to generate in-sprint tests and compliant test data, it also provides a collaboration hub for cross-functional teams. This is done by using BPMN style flowcharts or models which pool data from across the application development ecosystem, maintaining an up-to-date map of what needs testing in-sprint. In the OTP, models are the centrepiece for collaboration. These models are generated and managed in Test Modeller, a key part of Curiosity’s OTP.
In the OTP, all tasks and data observations either optimize the value of the model or ensure that the tests generated from the model can execute without interruption. Models allow teams to identify critical change impacts quickly and visually. Furthermore, models express test logic abstracted from independent applications or services, allowing system designers, testers and developers to collaborate. Through the use of models, developers are also presented with an accurate map of the latest system changes, avoiding miscommunications and time-consuming rework. However, the OTP would be incomplete without test data.
This is why Curiosity’s OTP comes with integrated Test Data Automation. Curiosity’s Test Data Automation generates complete and compliant data on demand to compliment Test Modeller and round out the OTP. Test Data Automation is also equipped with on-the-fly data masking and generation, with rapid database cloning, capable of producing virtual databases filled with rich test data. This enables testers to test at the speed of system releases. With Curiosity’s OTP, cross-functional teams collaborate to deliver accurately built, fully tested software in short iterations. So, how does it work?
How Does The OTP Work?
Curiosity’s OTP not only combines Test Modeller and Test Data Automation, it also integrates with over 100 tools and has a range of other technologies that testers can take advantage of. The Open Testing Platform is built on the following integrated components:
- Connect: Curiosity’s OTP connects disparate technologies from across the development lifecycle, ensuring that there is sufficient data to identify and generate in-sprint tests. The OTP leverages a fully extendable DevOps integration engine to connect disparate tools. This gathers the data needed to inform in-sprint test generation, avoiding a “garbage in, garbage out” situation when adopting AI/ML technologies in testing.
- Baseline: The rich data gathered from across DevOps toolchains feeds a “Baseline” of real-time data. Baseline aggregates, analyses and converts observations into actionable insights. It exposes the latest changes in requirements, systems, environments, and user behaviours, informing testers of what needs testing in-sprint.
- In-Sprint: Curiosity’s OTP not only identifies what needs testing, it also generates the test cases and automation scripts needed to run those tests. The OTP doesn’t just tell you “how” to test; it tells you “what” to test in-sprint and provide accelerators to building those tests in short iterations. In Curiosity’s OTP, Test Modeller generates the in-sprint tests.
- Pathfinder: Lastly, Curiosity’s OTP provides the data needed to run the in-sprint tests. Unlike outdated approaches to test data management, data is furthermore served up “just in time” as tests are generated and run. Test Data Automation provides this on-the-fly data resolution in Curiosity’s OTP.
Complete Test Automation In-Sprint With The OTP
Built with software delivery teams at the forefront, the Open Testing Platforms key objective is to facilitate collaboration and enable rigorous in-sprint test automation. Curiosity’s Open Testing Platform does this using a methodology that consists of three intuitive steps:
Inform: The OTP analyses data from all available sources, alerting test teams to changes that will impact the current release cycle.
Act: The OTP optimises test suites based on change and risk, identifying the tests that need running in-sprint.
Automate: The OTP automates the tasks needed to test in-sprint, including test generation, test data allocation, and test execution.
To learn more about Curiosity’s Open Testing Platform, check out our complete guide. Curiosity’s in-depth guide explores how the Open Testing Platform analyses data from across the whole application delivery lifecycle, identifying and generating the tests needed in-sprint.
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