Adding Automated Testing context

context/README.md

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+# Welcome to Mastering Automated Testing in Power Platform!
+
+Hello, Code First Developers and Low Code Makers!
+
+This context part of the site is designed to look more at the people and process parts of the Development / Operations (DevOps) loop and help you understand the why and how parts of the process. The discussion and example sections will expand on this context with areas of discussion as you work through this journey and provide examples of how you can do it. Any DevOps journey is a transformation, especially as we look at low code where the speed of development is fast and many of the learnings and principles are new to people. 
+
+## Why Testing Matters
+
+In the realm of low code development, testing is often an overlooked yet crucial aspect. Ensuring the reliability, performance, and security of your Power Platform solutions can significantly enhance their quality and user satisfaction. Whether you're a seasoned developer or just starting, understanding and implementing robust testing strategies is key to delivering top-notch solutions.
+
+## The Transformation Power of AI
+
+AI plays a pivotal role in this journey, offering tools and capabilities that can significantly enhance the testing process. From automating repetitive tasks to providing intelligent insights, AI can help streamline your DevOps practices and ensure your solutions are robust and reliable.
+
+## Topics to frame Automated Testing
+
+Before you dive into deeper discussion and examples you the following articles to help frame the discussion. These topics should help you have discussions with Enterprise Architect, Solution Architects and IT decision makers on how Power Platform and Automated Testing applies when looking at the Power Platform
+
+| Article | Notes | Feedback |
+|---------|-------|----------|
+| [Why Automated Testing](./why-automated-testing.md) | Automated testing is essential for ensuring the reliability, security, and performance of applications. It provides a safety net that catches bugs early, reduces manual testing efforts, and ensures consistent quality. This is particularly important in the context of low-code Power Platform solutions, where rapid development cycles can lead to overlooked issues. |  |
+| [Why Not Just Manual Testing](./why-not-just-manual-testing.md) | While manual testing has its place, it is often time-consuming, prone to human error, and not scalable for large or complex applications. Automated testing complements manual testing by handling repetitive tasks, providing faster feedback, and allowing testers to focus on more critical, exploratory testing activities. |  |
+| [Growing to Enterprise Grade](./growing-to-enterprise-grade.md) | As solutions scale, the need for robust testing practices becomes more critical. This article explores how to transition from small-scale projects to enterprise-grade solutions, emphasizing the importance of automated testing in maintaining high standards of reliability, security, and performance. | |
+| [Impacts on People, Process, and Tooling](./impacts-on-people-process-tooling.md) | Implementing automated testing requires a shift in mindset and practices. This article discusses the cultural and organizational changes needed to adopt automated testing, the impact on development and operations processes, and the tools that can facilitate this transformation. | |
+| [Transformative Power of AI](./transformative-power-of-ai.md) | This article explores how AI can observe interactions and inform the agent to suggest happy paths, edge cases, and exception cases. This capability helps deliver a faster path to generate comprehensive test scenarios, enhancing the overall testing process. | An external link was removed to protect your privacy. |
+| [Why Not Just Use Code First Testing Tools](./why-not-just-use-code-first-testing-tools.md) | Code-first testing resources are relatively scarce, and the efficiency of building low-code solutions must be matched by the rapid creation of tests. This article explains why relying solely on code-first testing tools may not be sufficient and how low-code testing tools can complement them. | An external link was removed to protect your privacy. |

context/growing-to-enterprise-grade.md

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+# Growing to Enterprise Grade
+
+As your solutions scale, the need for robust testing practices becomes more critical. Growing to enterprise-grade involves adopting a model that can deploy on demand and rapidly respond to new features, errors, or security requirements. This model relies on the confidence provided by automated tests, allowing you to meet business needs while adhering to continuous integration and deployment (CI/CD) processes.
+
+## The Enterprise-Grade Model
+
+An enterprise-grade model is designed to handle the complexities and demands of large-scale applications. It ensures that your solutions are [sustainable](../discussion/building-a-sustainability-model.md), reliable, secure, and performant, even as they grow in size and complexity. Key components of this model include:
+
+1. **On-Demand Deployment**: The ability to deploy updates and new features quickly and efficiently is crucial for maintaining a competitive edge. Automated testing ensures that these deployments are reliable and do not introduce new issues.
+2. **Rapid Response to Changes**: Whether it's a new feature request, a bug fix, or a security update, the ability to respond quickly is essential. Automated tests provide a safety net that allows you to make changes with confidence, knowing that any issues will be caught early.
+3. **Continuous Integration and Deployment (CI/CD)**: Integrating automated tests into your CI/CD pipeline ensures that every code change is tested and validated before it reaches production. This reduces the risk of defects and ensures that your application remains stable and reliable.
+
+## Benefits of Automated Testing in an Enterprise-Grade Model
+
+Automated testing plays a critical role in achieving and maintaining enterprise-grade quality. Here are some of the key benefits:
+
+1. **Confidence in Deployments**: Automated tests provide assurance that your application will continue to function correctly after each deployment. This confidence allows you to deploy more frequently and with less risk.
+2. **Faster Time to Market**: By automating repetitive testing tasks, you can reduce the time required for testing and accelerate the release of new features and updates.
+3. **Improved Quality**: Automated tests can cover a wide range of scenarios, including edge cases and negative tests, ensuring that your application is thoroughly tested and of high quality.
+4. **Scalability**: Automated testing can handle large volumes of test cases, making it suitable for large-scale applications. It can also be easily scaled to accommodate growing testing needs.
+
+## Conclusion
+
+Growing to enterprise-grade requires a robust testing strategy that includes automated testing. By adopting an enterprise-grade model, you can deploy on demand, respond rapidly to changes, and maintain the confidence provided by automated tests. This approach ensures that your solutions meet business needs while adhering to the expectations of continuous integration and deployment processes.

context/impacts-on-people-process-and-tooling.md

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+# Impacts on People, Process, and Tooling
+
+In the evolving landscape of software development, the integration of low-code solutions with existing automated testing and continuous integration (CI) practices is crucial. This approach, known as the "no cliffs" extensibility model, ensures that investments in automated testing and CI can be seamlessly integrated into low-code environments. This model supports both low-code-only and code-first deployment models, offering the best of both worlds.
+
+## No Cliffs Extensibility Model
+
+The no cliffs extensibility model is designed to bridge the gap between low-code and traditional code-first development. It allows organizations to leverage their existing investments in automated testing and CI while embracing the agility and speed of low-code development. This model ensures that there are no abrupt transitions or "cliffs" when moving between low-code and code-first approaches.
+
+### Integration with Existing Investments
+
+One of the key benefits of the no cliffs model is the ability to integrate existing automated testing and CI practices into low-code environments. This integration ensures that the same rigorous testing and deployment standards are applied across all development efforts, regardless of the approach used.
+
+### Low-Code-Only to Code-First Deployment Models
+
+The no cliffs model supports a range of deployment models, from low-code-only to code-first. This flexibility allows organizations to choose the best approach for each project, leveraging the strengths of both low-code and code-first development. For example, a project may start with a low-code approach to quickly prototype and validate ideas, then transition to a code-first approach for more complex and scalable implementations.
+
+### Leveraging Code-First Team Skills
+
+The no cliffs model also enables organizations to leverage the skills of their code-first development teams to augment and scale low-code practices. Code-first developers can contribute their expertise in automated testing, CI, and other best practices to the low-code maker community, ensuring that low-code solutions meet the same high standards as traditional applications.
+
+## Benefits of the No Cliffs Model
+
+The no cliffs extensibility model offers several benefits:
+
+1. **Seamless Integration**: By integrating existing automated testing and CI practices into low-code environments, organizations can ensure consistent quality and reliability across all development efforts.
+2. **Flexibility**: The ability to choose between low-code-only and code-first deployment models allows organizations to select the best approach for each project, maximizing efficiency and effectiveness.
+3. **Scalability**: Leveraging the skills of code-first development teams helps scale low-code practices, ensuring that low-code solutions can meet enterprise-grade requirements.
+4. **Collaboration**: The no cliffs model fosters collaboration between low-code makers and code-first developers, creating a more cohesive and productive development environment.
+
+## Conclusion
+
+The no cliffs extensibility model is a powerful approach for integrating low-code solutions with existing automated testing and CI practices. By supporting both low-code-only and code-first deployment models, this approach offers the best of both worlds, ensuring that organizations can leverage their existing investments while embracing the agility and speed of low-code development. By fostering collaboration and leveraging the skills of code-first teams, the no cliffs model helps scale low-code practices to meet enterprise-grade requirements.

context/transformative-power-of-ai.md

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+# Transformative Power of AI
+
+The transformative power of AI in the realm of automated testing with the Power Platform lies in its ability to observe by example as you interact with the created low-code solution. By augmenting this with your knowledge and expectations of how the solution should work, Generative AI can suggest comprehensive test suites and cases. These suggestions cover expected "happy path" tests, edge cases, and exception cases, bridging the gap in domain knowledge of testing practices that may be new to many developers.
+
+## Observing by Example
+
+[Generative AI](../discussion/generative-ai.md) when [authoring tests](../discussion/test-authoring.md) with tools like Test Engine can observe your interactions with the low-code solution, learning from the way you use and test the application. This observational capability allows AI to understand the intended functionality and user flows, enabling it to generate relevant test cases that reflect real-world usage scenarios.
+
+## Augmenting with Knowledge and Expectations
+
+By combining its observational insights with your knowledge and expectations, Generative AI can create test cases that are not only accurate but also comprehensive. This includes:
+
+- **Happy Path Tests**: These tests ensure that the application works as expected under normal conditions, following the most common user flows.
+- **Edge Cases**: AI can identify and test scenarios that occur at the boundaries of expected input ranges, ensuring the application handles these situations gracefully.
+- **Exception Cases**: AI can also generate tests for unexpected or erroneous inputs, verifying that the application can handle errors without crashing or producing incorrect results.
+
+## Bridging the Knowledge Gap
+
+For many developers, especially those new to testing practices, understanding how to create effective test cases can be challenging. Generative AI helps bridge this gap by providing intelligent suggestions based on observed interactions and best practices. This support is invaluable for ensuring that all critical aspects of the application are tested thoroughly.
+
+## Common Patterns: Arrange, Act, Assert
+
+Generative AI can also incorporate common testing patterns, such as "Arrange, Act, Assert," which are widely used in traditional software development. This pattern involves:
+
+- **Arrange**: Setting up the initial conditions and inputs for the test.
+- **Act**: Executing the action or function being tested.
+- **Assert**: Verifying that the outcome matches the expected result.
+
+By using these familiar patterns, AI-generated tests can be easily understood and maintained by developers, ensuring consistency and reliability in the testing process. Using approaches like [Data simulation](../discussion/data-simulation.md) bring common patterns to allow this approch to be applied.
+
+## The Role of Power Fx
+
+Power Fx plays a transformational role as an extensible and verifiable language that complements Generative AI. Power Fx allows for the creation of precise and verifiable test steps, ensuring that generated tests align with the available test steps and the application's logic. This combination of Generative AI and Power Fx provides a robust framework for automated testing, enhancing both the accuracy and reliability of the tests.
+
+## Specific Domain Knowledge of Power Fx
+
+Generative AI's specific domain knowledge of the Power Fx language and the object model behind applications, automation, and data structures is crucial. This knowledge allows AI to generate tests that are not just focused on the outer presentation layer but also on the underlying logic and data interactions. This creates more resilient tests that are abstracted from specific point-in-time changes as the Power Platform evolves.
+
+By understanding the Power Fx language and object model, AI can:
+
+- **Generate Accurate Test Steps**: Ensure that test steps are aligned with the application's logic and data structures.
+- **Adapt to Changes**: Create tests that are resilient to changes in the application's presentation layer, focusing on the core functionality and data interactions.
+- **Enhance Reliability**: Provide a deeper level of testing that covers both the user interface and the underlying logic, ensuring comprehensive test coverage.
+
+## Conclusion
+
+The transformative power of AI in automated testing lies in its ability to observe, learn, and generate comprehensive test cases that cover a wide range of scenarios. By leveraging Generative AI and Power Fx, developers can ensure that their low-code solutions are thoroughly tested and meet high standards of quality and reliability. This approach not only bridges the knowledge gap in testing practices but also enhances the overall efficiency and effectiveness of the testing process.

context/why-automated-testing.md

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+# Why Automated Testing?
+
+Automated testing is a cornerstone of modern software development, ensuring that applications are [sustainable](../discussion/building-a-sustainability-model.md), reliable, secure, and performance. In the context of low-code Power Platform solutions, automated testing becomes even more critical due to the rapid development cycles and the need for enterprise-grade reliability.
+
+## Learned Expectations of Automated Testing
+
+In traditional software development, automated testing has proven to be invaluable for catching bugs early, reducing manual testing efforts, and ensuring consistent quality. These benefits are equally applicable to low-code solutions, where the speed of development can sometimes lead to overlooked issues. Automated tests provide a safety net, ensuring that new features do not break existing functionality and that the application remains robust as it evolves.
+
+## Applying Automated Testing to Enterprise-Grade Low-Code Solutions
+
+For enterprise-grade low-code solutions, automated testing is essential to maintain high standards of reliability and security. It supports the pillars of the [Power Well-Architected Framework](https://aka.ms/powa), particularly Operational Excellence, Security, and Reliability.
+
+## Operational Excellence
+
+Automated testing enhances operational excellence by streamlining the development process. It allows for continuous integration and continuous deployment (CI/CD), ensuring that code changes are automatically tested and deployed with confidence. This reduces the risk of human error and accelerates the release cycle, enabling teams to deliver features faster and with higher quality.
+
+## Security
+
+Security is another critical pillar supported by automated testing. By incorporating security tests into the automated testing suite, teams can ensure that their applications are resilient to attacks and comply with security best practices. Automated tests can simulate various attack scenarios, validate access controls, and ensure that data integrity and confidentiality are maintained.
+
+## Reliability
+
+Reliability design principles emphasize the need for a resilient and available system. Automated testing contributes to this by continuously validating the system's ability to handle faults and recover from failures. It ensures that the application can consistently deliver functionality and meet the agreed quality levels.
+
+## Testing Personas and Roles
+
+Automated testing also plays a pivotal role in validating different personas and roles within the application. It ensures that each user type can perform their tasks without issues, maintaining a seamless user experience across the board.
+
+## Continuous Integration / Deployment (CI/CD) and Deployment Confidence
+
+The CI/CD process is integral to maintaining deployment confidence. Automated tests are a key component of this process, providing immediate feedback on the impact of code changes. This continuous validation helps teams identify and address issues early, ensuring that deployments are smooth and reliable.
+
+## Keep It Simple Principle
+
+The "Keep it simple" principle is crucial in automated testing. By leveraging in-product experiences to build, maintain, and execute tests, teams can avoid reinventing the wheel. This approach ensures that testing processes are straightforward, efficient, and aligned with the overall development workflow.
+
+## Conclusion
+
+In summary, automated testing is not just a best practice but a necessity for building and maintaining enterprise-grade low-code solutions. It supports the pillars of the Power Well-Architected Framework, ensuring operational excellence, security, and reliability. By integrating automated testing into the development process, teams can deliver high-quality applications that meet business requirements and provide a robust user experience.