Risk analysis for testing in Testing Fundamentals - Practice Problems & Coding Challenges

Challenge - 5 Problems

🧠 Conceptual

intermediate

Identifying High-Risk Areas

In risk analysis for testing, which factor most directly increases the priority of testing a feature?

A The feature has extensive automated tests already.

B The feature is rarely used and has simple logic.

C The feature was recently added but has no known bugs.

D The feature has a complex design and affects many users.

💡 Hint

Think about what makes a feature more likely to cause problems if it fails.

Features that are complex and impact many users have higher risk and need more testing focus.

❓ Predict Output

intermediate

Output of Risk Score Calculation

What is the output of the following Python code that calculates a risk score?

Testing Fundamentals

def risk_score(probability, impact):
    return probability * impact

score = risk_score(0.7, 8)
print(score)

A 15

B 5.6

C 0.875

D SyntaxError

💡 Hint

Multiply the two numbers given as arguments.

The function multiplies probability (0.7) by impact (8), resulting in 5.6.

❓ assertion

advanced

Validating Risk Priority Order

You have a list of features with risk scores. Which assertion correctly checks that the list is sorted from highest to lowest risk?

Testing Fundamentals

risk_scores = [9.5, 7.2, 5.6, 3.1]

A assert risk_scores == sorted(risk_scores)

B assert all(risk_scores[i] <= risk_scores[i+1] for i in range(len(risk_scores)-1))

C assert all(risk_scores[i] >= risk_scores[i+1] for i in range(len(risk_scores)-1))

D assert risk_scores == sorted(risk_scores, reverse=False)

💡 Hint

Check that each score is greater than or equal to the next.

Option C verifies the list is sorted descending by comparing each element to the next.

🔧 Debug

advanced

Debugging Risk Impact Calculation

Find the error in this code that calculates risk impact but returns wrong results:

Testing Fundamentals

def calculate_impact(severity, frequency):
    impact = severity + frequency
    return impact

result = calculate_impact(5, 3)
print(result)

A The impact should be multiplied, not added, so use severity * frequency.

B The function is missing a return statement.

C The variables severity and frequency are not defined.

D The print statement is outside the function and causes an error.

💡 Hint

Risk impact is usually calculated by multiplying severity and frequency.

Adding severity and frequency underestimates impact; multiplication reflects combined effect better.

❓ framework

expert

Designing a Risk-Based Test Selection Framework

Which approach best fits a risk-based test selection framework to optimize testing effort?

A Select tests that cover features with the highest risk scores first, then proceed to lower risk features.

B Run all tests equally regardless of risk to ensure full coverage.

C Select tests randomly to avoid bias in testing.

D Only test features that have failed before, ignoring new or changed features.

💡 Hint

Focus testing on areas where failure impact and likelihood are highest.

Prioritizing tests by risk ensures critical areas are tested first, optimizing resources and reducing risk.