Boozang
Simplified Testing Without Code
Empower every member of your team, not just developers, to create and manage automated tests effortlessly.
Address your testing needs efficiently, achieving comprehensive test coverage in mere days instead of several months.
Our tests designed in natural language are highly resilient to changes in the codebase, and our AI swiftly fixes any test failures that may arise.
Continuous Testing is essential for Agile and DevOps practices, allowing you to deploy features to production within the same day.
Boozang provides various testing methods, including:
- A Codeless Record/Replay interface
- BDD with Cucumber
- API testing capabilities
- Model-based testing
- Testing for HTML Canvas
The following features streamline your testing process:
- Debugging directly within your browser console
- Screenshots pinpointing where tests fail
- Seamless integration with any CI server
- Unlimited parallel testing to enhance speed
- Comprehensive root-cause analysis reports
- Trend reports to monitor failures and performance over time
- Integration with test management tools like Xray and Jira, making collaboration easier for your team.
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NeoLoad
Software designed for ongoing performance testing facilitates the automation of API load and application evaluations. In the case of intricate applications, users can create performance tests without needing to write code. Automated pipelines can be utilized to script these performance tests specifically for APIs. Users have the ability to design, manage, and execute performance tests using coding practices. Afterward, the results can be assessed within continuous integration pipelines, leveraging pre-packaged plugins for CI/CD tools or through the NeoLoad API. The graphical user interface enables quick creation of test scripts tailored for large, complex applications, effectively eliminating the time-consuming process of manually coding new or revised tests. Service Level Agreements (SLAs) can be established based on built-in monitoring metrics, enabling users to apply stress to the application and align SLAs with server-level statistics for performance comparison. Furthermore, the automation of pass/fail triggers utilizing SLAs aids in identifying issues effectively and contributes to root cause analysis. With automatic updates for test scripts, maintaining these scripts becomes much simpler, allowing users to update only the impacted sections while reusing the remaining parts. This streamlined approach not only enhances efficiency but also ensures that tests remain relevant and effective over time.
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DC-E DigitalClone for Engineering
DigitalClone® for Engineering stands out as the sole software that seamlessly combines various scales of analysis within a unified platform. Recognized globally as the premier tool for predicting gearbox reliability, DC-E excels not only in its modeling and analysis capabilities specific to gearboxes and gear/bearing interactions but also uniquely incorporates fatigue life modeling through advanced, physics-based methodologies (US Patent 10474772B2).
By enabling the creation of a digital twin for gearboxes, DC-E encompasses every phase of an asset's lifecycle—from the optimization of design and manufacturing processes to the selection of suppliers, followed by thorough root cause analysis of failures and condition-based maintenance along with prognostics. This innovative computational environment significantly decreases both the time and costs associated with launching new designs and ensuring their long-term maintenance, ultimately enhancing operational efficiency. Moreover, it empowers engineers to make informed decisions at every stage, leading to improved performance and reliability.
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UpTrain
Gather metrics that evaluate factual accuracy, quality of context retrieval, adherence to guidelines, tonality, and other relevant criteria. Without measurement, progress is unattainable. UpTrain diligently assesses the performance of your application based on a wide range of standards, promptly alerting you to any downturns while providing automatic root cause analysis. This platform streamlines rapid and effective experimentation across various prompts, model providers, and custom configurations by generating quantitative scores that facilitate easy comparisons and optimal prompt selection. The issue of hallucinations has plagued LLMs since their inception, and UpTrain plays a crucial role in measuring the frequency of these inaccuracies alongside the quality of the retrieved context, helping to pinpoint responses that are factually incorrect to prevent them from reaching end-users. Furthermore, this proactive strategy not only improves the reliability of the outputs but also cultivates a higher level of trust in automated systems, ultimately benefiting users in the long run. By continuously refining this process, UpTrain ensures that the evolution of AI applications remains focused on delivering accurate and dependable information.
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