Feature Request: Introducing NLP Features for Improved Test Summaries and Analysis in Fossil Test

[dreamer-coding]

Is your feature request related to a problem? Please describe.

The current test summaries in Fossil Test are functional but lack in-depth analysis and contextual understanding of the results. I often find it difficult to quickly grasp the essence of test failures or successes without manually analyzing each output. This results in additional effort when reviewing long test reports or large test suites.

Describe the solution you’d like

I would like Fossil Test to integrate Natural Language Processing (NLP)-like features to enhance the summary and analysis of test outputs. Specifically, the features could include:
• Intelligent Test Summaries: Generate more detailed, readable summaries of test results that include human-like explanations for failures or successes. For example, instead of just stating “Test Failed,” the summary might provide a reason such as “Test failed due to timeout” or “Test failed because the expected output did not match the actual output.”
• Contextual Error Analysis: Use NLP to analyze error messages and provide contextual insights, such as suggestions for troubleshooting or common causes of the error.
• Auto Categorization: Automatically categorize tests into groups such as “performance,” “security,” “functional,” and “edge cases,” improving test management and prioritization.
• Sentiment Analysis for Logs: Implement sentiment analysis to identify areas of concern or potential issues by detecting overly negative or alarming patterns in the test logs.
• Test Optimization Suggestions: Suggest optimizations for test cases based on analysis of patterns in successful or failed tests (e.g., recommending parallelization for slow tests).

Describe alternatives you’ve considered

•	Manually reviewing test outputs and categorizing them for analysis, but this process is time-consuming and inconsistent.
•	Using external log analysis tools that use NLP, but these aren’t integrated into the testing framework and require extra setup.

Additional context

Integrating NLP into Fossil Test would drastically improve the usability and efficiency of interpreting test results. It would save developers significant time by providing clear, actionable insights and reducing the need for manual interpretation of logs.