ByteDance QA Engineer System Design Questions

In the context of ByteDance's backend performance testing, design a class LoadTestOrchestrator that can schedule and execute load tests across multiple services. The orchestrator must manage test execution and gather metrics.
Class Signature:
- class LoadTestOrchestrator:
- def __init__(self): - Initializes the orchestrator.
- def schedule_load_test(self, service_name: str, duration: int): - Schedules a load test for a given service.
- def execute_tests(self) -> None: - Executes all scheduled tests concurrently.
- def get_test_results(self) -> Dict[str, Any]: - Returns a dictionary of test results for each service.
Example 1:
- Input: orchestrator = LoadTestOrchestrator(), orchestrator.schedule_load_test('serviceA', 60)
- Output: After calling execute_tests() the results can be accessed via get_test_results().
Constraints:
- 1 <= service_name.length <= 100
- 0 <= duration <= 3600

In testing environments common to ByteDance, it's essential to identify flaky tests to improve the reliability of the automation pipelines. Design a class FlakyTestDetector to help identify tests that fail intermittently and should be reviewed or fixed.
Class Signature:
- class FlakyTestDetector:
- def __init__(self): - Initializes the detector.
- def report_test_result(self, test_id: str, success: bool): - Reports the result of a test execution.
- def get_flaky_tests(self) -> List[str]: - Returns a list of flaky test ids.
Example 1:
- Input: detector = FlakyTestDetector(), detector.report_test_result('test1', True), detector.report_test_result('test1', False)
- Output: detector.get_flaky_tests()
- Returns: ['test1']
Constraints:
- 1 <= test_id <= 100000