# Test Optimization Savings Breakdown

Test Optimization Savings Breakdown provides a comprehensive overview of test execution performance and savings for a specific app and test stage. 

## Timeline

The page includes a timeline with:

* Build events, with a summary of the test savings (or potential savings) out of the total tests reported 
* System events (e.g. scheduled full test run) 
* User action events (e.g. TIA turned off/on, full run policy change). 

## Test Execution Data & Insights 

Users can view test execution data and detailed insights into each individual build, including:

* **Test Execution Summary and List:** The total number of tests passed / failed, executed / skipped, along with the skipping reason. And a detailed list of all reported tests.
* **Impacted Tests:** Detailed list of code changes and their corresponding tests for each build.
* **AUT (Application Under Test):** Available for apps that combine a few components (apps) for advanced testing (cross app testing), displays the list of apps with the specific branch and build. There is an access to the build monitor (for Admin / DevOps) to explore more technical details. 

## Charts & Graphs

Users can open an additional view with charts describing the savings (in compute time or in number of tests) per build, with a clear visualization of the trends over time and the ability to analyze the potential savings before turning on the TIA.

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By combining these elements, the Savings Breakdown empowers users to understand the factors driving test efficiency, pinpoint areas for improvement, and make data-driven decisions to optimize testing processes.

SeaLights Test Optimization simplifies your testing process by analyzing code changes and recommending which tests are directly impacted. Here's how it works:

1. **Automated Test Reporting:** SeaLights automatically collects data from your tests through integrations with various testing frameworks or using its APIs.
2. **Test Optimization Engine (TIA):** Starting from the second build, TIA analyzes code changes and historical data to identify tests impacted by modifications.
3. **Recommendations and Execution:** TIA recommends skipping or prioritizing tests based on their relevance and according to a pre set [Test Selection Policy](/knowledgebase/test-optimization/test-optimization-strategy/test-selection-policies.md). These recommendations are automatically applied and executed through integrations or by using the APIs.

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