= Evaluation and Testing

== Evaluation Criteria

The evaluation of the One-Click Deployment system employs precisely defined criteria tailored to assess both system performance and user experience. These criteria ensure that results are both quantitatively measurable and qualitatively insightful, accurately reflecting the system’s efficiency, usability, and scalability.

- *User Experience (UX):* The UX assessment primarily focuses on the interface usability as experienced by colleagues during a series of task-based tests. Key methodologies include:
  - *Task Completion:* Observing the ability of participants to complete predefined tasks using the system, noting any usability challenges or navigation issues.
  - *Lighthouse Testing:* Employing Google Lighthouse @monttiGoogleLighthouse2018 to evaluate the frontend performance, assessing metrics such as load times, interactivity, and the overall efficiency of the web interface.

- *System Performance:*
  - *Code Quality Analysis:* Utilizing CodeFactor #footnote[https://support.codefactor.io/i24-analysis-tools-open-source] to scrutinize the quality of the system's codebase, including the Kubernetes operator. This analysis helps identify potential issues in the code such as complexity, maintainability, and security vulnerabilities.
  - *Scalability Testing:* Conducting load tests to evaluate the system's performance under varying loads, ensuring that it can handle multiple concurrent deployments without compromising performance.

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== Testing Methodology

The methodology integrates specific software tools and manual testing to provide a comprehensive evaluation of the One-Click Deployment system:

- *User Experience Testing:* Conducted informally with colleagues, this involves direct interaction with the system’s UI to complete specific deployment tasks, capturing real-time feedback and usability data.
- *Performance Testing:*
  - *Frontend Performance:* Using Google Lighthouse #footnote[https://developer.chrome.com/docs/lighthouse/overview] to systematically assess and document the frontend's performance under typical usage conditions.
  - *Code Quality Assessment:* CodeFactor #footnote[https://codefactor.io/] is employed to analyze the entire codebase, providing a detailed report on code health, identifying areas for improvement, and ensuring adherence to best coding practices.
  - *Scalability Testing:* Load tests are performed manually to simulate multiple concurrent deployments, monitoring the system's response time and resource utilization under varying loads.

== Test Results

The results from the testing phase are critical in highlighting the system’s operational strengths and areas for improvement:

- *User Experience Results:*
  - *Task Completion:* Most participants successfully completed the tasks with minimal guidance, indicating a generally intuitive user interface. However, some noted minor confusion with more complex functionalities.
  - *Lighthouse Scores:* (Appendix: @lighthouse) The frontend achieved the following Lighthouse scores:
    - Performance: 80
    - Accessibility: 92
    - Best Practices: 96
    - SEO: 91
    - First Contentful Paint: 1.7s
    - Largest Contentful Paint: 2.2s
    - Total Blocking Time: 0ms
    - Cumulative Layout Shift: 0
    - Speed Index: 1.9s

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- *Performance and Reliability:*
  - *Code Quality:* CodeFactor analysis revealed an overall "A" grade for the system's codebase with specific suggestions for reducing complexity in certain modules of the Kubernetes operator. The scan will be used to refine the codebase further. The current score is always available in the repository README's.
  - *Scalability:* Load tests demonstrated that the system could handle up to 100 concurrent deployments without significant performance degradation, showcasing its scalability and reliability.

== Recommendations

Based on the test results, several actionable recommendations are proposed:

- *UI Enhancements:* Refine the UI design to improve clarity and ease of use, especially for complex deployment configurations, based on user feedback and Lighthouse results. This includes enhancing error messages and providing more intuitive guidance for users using the advanced editing mode.
- *Optimize Frontend Resources:* Implement the changes suggested by Lighthouse to enhance load times and interactivity, such as optimizing images and reducing the impact of third-party scripts.
- *Code Refinement:* Address the issues highlighted by CodeFactor by refactoring complex code segments in the Kubernetes operator, improving maintainability and potentially enhancing performance.

These recommendations are designed to bolster the One-Click Deployment system's robustness, enhance user satisfaction, and ensure the system can efficiently meet anticipated demands. By implementing these suggestions, the system will not only perform better but also offer a more streamlined and user-friendly experience.
