Learn Automating Test Execution | System Interaction and Test Automation

Automated test execution is a cornerstone of modern engineering practices, ensuring that systems maintain reliability as they evolve. By automating tests, you can rapidly verify that new changes do not break existing functionality—this is known as regression testing. Automation also makes it possible to validate large or complex systems quickly, consistently, and with minimal manual intervention. This is especially important when you need to run tests repeatedly, such as after every code update or configuration change, to maintain quality and reduce the risk of human error.


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import random

# Simulate running a set of tests
test_names = ["test_login", "test_logout", "test_file_upload", "test_file_download"]
results = {}

for test in test_names:
    # Randomly assign pass or fail for demonstration
    outcome = random.choice(["pass", "fail"])
    results[test] = outcome
    print(f"{test}: {outcome}")

When you automate tests, organizing your test cases and collecting their outcomes becomes essential for effective reporting and analysis. Storing results in a structured format—such as dictionaries or lists—makes it easy to summarize which tests passed or failed, generate reports, and identify trends over time. This structure helps you quickly communicate system status to your team or stakeholders and supports automated alerting or dashboard updates.


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# Summarize test outcomes using a dictionary
test_results = {
    "test_login": "pass",
    "test_logout": "pass",
    "test_file_upload": "fail",
    "test_file_download": "pass"
}

# Count passes and fails
summary = {"pass": 0, "fail": 0}
for outcome in test_results.values():
    summary[outcome] += 1

print("Test summary:", summary)

1. Why is automated test execution valuable?

2. What data structure is useful for storing test results?

3. Fill in the blank: 'results = {"test1": "pass", "test2": ___}'

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Section 3. Chapter 4

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