LinkedIn QA Engineer Interview Questions

As LinkedIn scales, it becomes crucial to identify and reduce flaky tests that intermittently fail. Your task is to implement a FlakyTestDetector that monitors test execution results and flags tests that exhibit flakiness.
- reportResult(testName: str, result: bool) -> None: Records the result of a test.
- isFlaky(testName: str) -> bool: Checks if a test is marked as flaky based on the number of reported results.Example 1:
Input: reportResult('FeedTest', True)
Output: None
Explanation: Records a passing result for 'FeedTest'.Example 2:
Input: isFlaky('FeedTest')
Output: False
Explanation: 'FeedTest' is not flaky since no failures recorded yet.Constraints:
- 1 <= testName.length <= 50
- Each test can be reported multiple times.

LinkedIn needs to efficiently track and manage test results for its extensive automation suite. This involves navigating through a complex system of test cases and results.
You are tasked to implement a TestResultTracker class that can record and manage test outcomes efficiently.
- addResult(testName: str, result: bool) -> None: Records the result of a test case. If the test already exists, it updates the result.
- getResult(testName: str) -> bool: Retrieves the result of a test case, returning false if it doesn't exist.Example 1:
Input: addResult('LoginTest', True)
Output: None
Explanation: Adds a test result for 'LoginTest'.Example 2:
Input: getResult('LoginTest')
Output: True
Explanation: Returns the result for 'LoginTest'.Constraints:
- 1 <= testName.length <= 100
- result is a boolean value (True or False).

As LinkedIn's infrastructure scales, it's essential to ensure the platform supports heavy loads. Your task is to create a LoadTestOrchestrator that manages various load test scenarios.
- addTestCase(testName: str, load: int) -> None: Adds a load test case with a specific load.
- runLoadTests() -> Dict[str, str]: Runs all added tests and returns their results.Example 1:
Input: addTestCase('ProfilePage', 1000)
Output: None
Explanation: Adds a load test case for the Profile Page with a load of 1000 users.Example 2:
Input: runLoadTests()
Output: {'ProfilePage': 'Passed'}
Explanation: Executes added load tests and returns their results.Constraints:
- 1 <= testName.length <= 100
- Each test can handle 0 < load <= 10000.

In the context of LinkedIn's growing automation suite, you are tasked with creating a TestResultAggregator that encapsulates the management and reporting of test results across different suites.
- addTestResult(suiteName: str, testName: str, result: bool) -> None: Adds a result for a test under a specified suite.
- getSuiteResult(suiteName: str) -> float: Calculates and returns the pass rate of all tests in a given suite, as a percentage.Example 1:
Input: addTestResult('UI', 'LoginTest', True)
Output: None
Explanation: Adds a passing result for the 'LoginTest' in the 'UI' suite.Example 2:
Input: getSuiteResult('UI')
Output: 100.0
Explanation: The pass rate is 100% for the 'UI' suite since there’s one passing test.Constraints:
- 1 <= suiteName.length <= 50
- Each suite can contain up to 1000 tests.