Defect metrics in Testing Fundamentals - Practice Problems & Coding Challenges

Challenge - 5 Problems

🧠 Conceptual

intermediate

Understanding Defect Density

Which formula correctly calculates defect density in a software project?

A Number of defects fixed divided by the total number of defects reported

B Total number of test cases executed divided by the number of defects found

C Number of defects found divided by the size of the software (e.g., lines of code or function points)

D Total number of defects found divided by the number of testers involved

💡 Hint

Think about how many defects appear relative to the size of the software.

Defect density measures how many defects exist per unit size of software, helping to understand quality relative to software size.

🧠 Conceptual

intermediate

Interpreting Defect Leakage

What does defect leakage indicate in software testing?

A Defects that remain undetected and are found by users after release

B Defects found by the testing team during test execution

C Defects fixed but reintroduced in later versions

D Defects reported but rejected as invalid

💡 Hint

Consider defects that escape the testing process and reach the users.

Defect leakage measures the number of defects missed during testing but found by users, indicating gaps in testing.

❓ Predict Output

advanced

Calculate Defect Removal Efficiency (DRE)

Given the following data, what is the Defect Removal Efficiency (DRE)?

DRE = (Defects found before release) / (Defects found before release + Defects found after release)

Defects found before release = 120
Defects found after release = 30

A 0.80

B 0.85

C 0.75

D 0.70

💡 Hint

Calculate the ratio of defects found before release to total defects found.

DRE = 120 / (120 + 30) = 120 / 150 = 0.80.

❓ assertion

advanced

Assertion on Defect Arrival Rate

Which assertion correctly describes the defect arrival rate during testing?

A It is the ratio of defects reopened to defects closed

B It is the number of defects found per unit time during testing

C It is the number of defects fixed per day after release

D It is the total number of defects found divided by total test cases executed

💡 Hint

Think about how quickly defects are discovered over time.

Defect arrival rate measures how many defects are found in a given time period during testing.

🔧 Debug

expert

Identify the Incorrect Defect Metric Calculation

Which option shows an incorrect calculation of a defect metric?

A Defect Arrival Rate = Defects found per day during testing

B Defect Leakage = Defects found after release / Total Defects found

C Defect Density = Total Defects / Total Lines of Code

D Defect Removal Efficiency = Defects found after release / Total Defects found

💡 Hint

Review the formula for Defect Removal Efficiency carefully.

Defect Removal Efficiency is the ratio of defects found before release to total defects found, not defects found after release.

Practice

1. What does defect density measure in software testing?

easy

A. Time taken to fix a defect

B. Total number of test cases executed

C. Number of defects per size of the software

D. Number of users reporting defects

Solution

1. Step 1: Understand defect density meaning

   Defect density is a metric that counts defects relative to software size, like per thousand lines of code.

2. Step 2: Compare options with definition

   Only Number of defects per size of the software matches this definition; others relate to different metrics.

3. Final Answer:

   Number of defects per size of the software -> Option C

4. Quick Check:

   Defect density = defects / software size [OK]

Hint: Defect density = defects divided by software size [OK]

Common Mistakes:

• Confusing defect density with total defects
• Mixing defect density with test execution count
• Thinking defect density measures fix time

2. Which of the following is the correct formula for calculating defect density?

easy

A. Defect Density = Total Defects / Software Size

B. Defect Density = Software Size / Total Defects

C. Defect Density = Total Defects x Software Size

D. Defect Density = Total Defects + Software Size

Solution

1. Step 1: Recall defect density formula

   Defect density is calculated by dividing total defects by software size.

2. Step 2: Match formula with options

   Defect Density = Total Defects / Software Size correctly shows division of defects by size; others use incorrect operations.

3. Final Answer:

   Defect Density = Total Defects / Software Size -> Option A

4. Quick Check:

   Defect density = defects ÷ size [OK]

Hint: Defect density divides defects by size, not multiply [OK]

Common Mistakes:

• Multiplying defects by size instead of dividing
• Reversing numerator and denominator
• Adding defects and size instead of dividing

3. A software module has 1200 lines of code and 24 reported defects. What is the defect density?

medium

A. 20 defects per 1000 lines

B. 50 defects per 1000 lines

C. 0.02 defects per line

D. 0.02 defects per 1000 lines

Solution

1. Step 1: Calculate defects per 1000 lines

   Defect density = (24 defects / 1200 lines) x 1000 = 20 defects per 1000 lines.

2. Step 2: Compare with options

   20 defects per 1000 lines matches 20 defects per 1000 lines; others are incorrect calculations or units.

3. Final Answer:

   20 defects per 1000 lines -> Option A

4. Quick Check:

   (24/1200)*1000 = 20 [OK]

Hint: Multiply defects/lines by 1000 for defect density [OK]

Common Mistakes:

• Not scaling defects per 1000 lines
• Confusing defects per line with per 1000 lines
• Incorrect division order

4. A defect report shows severity as 'High' but the status is marked 'Closed' without fixing. What is the likely issue?

medium

A. Defect density calculation error

B. Defect was fixed but not retested

C. Test cases are incomplete

D. Defect severity and status are inconsistent

Solution

1. Step 1: Analyze severity and status meaning

   High severity means serious defect; status 'Closed' usually means fixed or resolved.

2. Step 2: Identify inconsistency

   Closing a high severity defect without fixing is inconsistent and indicates a reporting or process error.

3. Final Answer:

   Defect severity and status are inconsistent -> Option D

4. Quick Check:

   High severity + Closed without fix = inconsistency [OK]

Hint: High severity defects should not be closed without fix [OK]

Common Mistakes:

• Assuming defect density relates to status
• Confusing test case completeness with defect status
• Thinking defect was fixed without evidence

5. You have two modules: Module A with 2000 lines and 40 defects, Module B with 1000 lines and 30 defects. Which module has better quality based on defect density?

hard

A. Module A has better quality because it has fewer defects

B. Module A has better quality because its defect density is lower

C. Both modules have the same quality

D. Module B has better quality because it has fewer lines of code

Solution

1. Step 1: Calculate defect density for Module A

   Module A defect density = 40 / 2000 = 0.02 defects per line.

2. Step 2: Calculate defect density for Module B

   Module B defect density = 30 / 1000 = 0.03 defects per line.

3. Step 3: Compare defect densities

   Lower defect density means better quality; Module A's 0.02 is less than Module B's 0.03.

4. Final Answer:

   Module A has better quality because its defect density is lower -> Option B

5. Quick Check:

   0.02 < 0.03 means Module A better [OK]

Hint: Lower defect density means better quality [OK]

Common Mistakes:

• Comparing only defect counts without size
• Assuming fewer lines means better quality
• Saying both have same quality without calculation