Quality metrics and measurement in Software Engineering - Practice Problems & Coding Challenges

Challenge - 5 Problems

🧠 Conceptual

intermediate

Understanding Defect Density

What does the metric defect density measure in software quality?

A The total number of defects found during the entire project lifecycle

B The number of defects found per size of the software, such as per thousand lines of code

C The average time taken to fix a defect after it is reported

D The percentage of test cases passed during testing

💡 Hint

Think about how defects relate to the size of the software.

Defect density measures how many defects exist relative to the size of the software, often per thousand lines of code. It helps compare quality across projects of different sizes.

📋 Factual

intermediate

Purpose of Code Coverage Metric

Which of the following best describes what the code coverage metric measures?

A The percentage of code executed during testing

B The number of defects found in the code

C The time taken to write the code

D The number of lines of code written by each developer

💡 Hint

Think about what testing aims to do with the code.

Code coverage measures how much of the code is actually run when tests are executed. Higher coverage means more code has been tested.

🔍 Analysis

advanced

Interpreting Mean Time to Failure (MTTF)

A software system has a Mean Time to Failure (MTTF) of 500 hours. What does this indicate about the system?

A The system is guaranteed to fail exactly every 500 hours

B The system takes 500 hours to recover after a failure

C The system has 500 known defects

D On average, the system operates for 500 hours before experiencing a failure

💡 Hint

Consider what 'mean time to failure' means in terms of operation time.

MTTF is the average time the system runs before a failure occurs. It does not guarantee exact failure times but gives an average expectation.

❓ Comparison

advanced

Difference Between Reliability and Availability

Which statement correctly distinguishes reliability from availability in software quality metrics?

A Reliability and availability are the same and can be used interchangeably

B Reliability measures user satisfaction, while availability measures code complexity

C Reliability measures how often software fails, while availability measures the proportion of time software is operational and accessible

D Reliability measures the number of defects, while availability measures the number of test cases

💡 Hint

Think about uptime versus failure frequency.

Reliability focuses on how often failures occur, while availability focuses on the time the system is ready for use, including downtime and repair time.

❓ Reasoning

expert

Choosing the Best Metric for Early Defect Detection

You want to measure how effective your testing process is at finding defects early in the development cycle. Which metric would best help you assess this?

A Defect Removal Efficiency (DRE)

B Code Complexity

C Mean Time to Repair (MTTR)

D Customer Satisfaction Score

💡 Hint

Consider a metric that compares defects found before release to total defects.

Defect Removal Efficiency measures the percentage of defects found and fixed before the software is released, indicating early defect detection effectiveness.

Practice

1. What is the main purpose of quality metrics in software engineering?

easy

A. To manage project budgets

B. To write code faster

C. To measure and improve software quality

D. To design user interfaces

Solution

1. Step 1: Understand what quality metrics measure

   Quality metrics provide numbers that show how good or bad software quality is.

2. Step 2: Identify the main goal of using these metrics

   They help find problems and track improvements in software quality.

3. Final Answer:

   To measure and improve software quality -> Option C

4. Quick Check:

   Quality metrics = measure and improve quality [OK]

Hint: Quality metrics measure software quality, not speed or cost [OK]

Common Mistakes:

• Confusing quality metrics with project management tools
• Thinking metrics speed up coding directly
• Mixing quality metrics with design tasks

2. Which of the following is a correct example of a software quality metric?

easy

A. user interface color

B. number of developers

C. programming language used

D. defect density

Solution

1. Step 1: Identify what counts as a quality metric

   Quality metrics are measurable numbers related to software quality, like defects per size.

2. Step 2: Check each option

   Defect density counts defects per size, so it is a quality metric. Others are not numeric quality measures.

3. Final Answer:

   defect density -> Option D

4. Quick Check:

   Defect density = quality metric [OK]

Hint: Look for measurable numbers related to software quality [OK]

Common Mistakes:

• Choosing non-numeric attributes like color or language
• Confusing team size with quality metric
• Ignoring the need for measurement

3. Given a software module with 50 defects found in 10,000 lines of code, what is the defect density?

medium

A. 0.005 defects per line

B. 0.5 defects per line

C. 5 defects per line

D. 0.05 defects per line

Solution

1. Step 1: Understand defect density formula

   Defect density = Number of defects / Lines of code.

2. Step 2: Calculate defect density

   50 defects / 10,000 lines = 0.005 defects per line. This equals 0.005, which is 0.005 defects per line.

3. Final Answer:

   0.005 defects per line -> Option A

4. Quick Check:

   50 ÷ 10,000 = 0.005 [OK]

Hint: Divide defects by lines of code for defect density [OK]

Common Mistakes:

• Multiplying instead of dividing
• Mixing decimal places
• Confusing defect density with total defects

4. A team tracks test coverage but reports it as 150%. What is the likely error?

medium

A. Test coverage calculation is incorrect or data is wrong

B. Test coverage can exceed 100% if tests overlap

C. Test coverage is not a valid quality metric

D. Test coverage measures defects, not code tested

Solution

1. Step 1: Understand test coverage limits

   Test coverage measures percentage of code tested, max 100%.

2. Step 2: Analyze reported value

   150% is impossible, so calculation or data must be wrong.

3. Final Answer:

   Test coverage calculation is incorrect or data is wrong -> Option A

4. Quick Check:

   Test coverage ≤ 100% [OK]

Hint: Test coverage cannot be more than 100% [OK]

Common Mistakes:

• Believing coverage can exceed 100%
• Confusing coverage with defect count
• Ignoring data errors

5. A project has these metrics: defect density = 0.02, average repair time = 5 hours, test coverage = 80%. Which action best improves overall software quality?

hard

A. Ignore defect density and focus on coding speed

B. Increase test coverage to find more defects early

C. Reduce repair time without changing testing

D. Decrease test coverage to save time

Solution

1. Step 1: Understand the impact of each metric

   Higher test coverage helps find defects early, reducing defect density over time.

2. Step 2: Evaluate options for improving quality

   Increasing test coverage is the best way to improve quality by catching defects early.

3. Final Answer:

   Increase test coverage to find more defects early -> Option B

4. Quick Check:

   More test coverage = better defect detection [OK]

Hint: More test coverage usually improves quality by catching defects early [OK]

Common Mistakes:

• Focusing only on repair time
• Ignoring defect density
• Reducing test coverage to save time