Defect metrics in Testing Fundamentals - Cheat Sheet & Quick Revision

Recall & Review

beginner

What are defect metrics in software testing?

Defect metrics are measurements used to track and analyze defects found in software. They help understand the quality and stability of the software by counting and categorizing bugs.

beginner

Explain the term 'Defect Density'.

Defect Density is the number of defects found divided by the size of the software (like lines of code or function points). It shows how many bugs exist per unit size, helping to find problem areas.

intermediate

What does 'Defect Leakage' mean?

Defect Leakage is when defects are missed during testing and found later by users or in production. It shows how many bugs escaped the testing process.

intermediate

How is 'Defect Removal Efficiency (DRE)' calculated?

DRE = (Defects found during testing) / (Defects found during testing + Defects found after release) × 100%. It measures how effective testing was at catching bugs before release.

beginner

Why is tracking 'Defect Age' important?

Defect Age is the time between when a defect is reported and when it is fixed. Tracking it helps teams understand how quickly they respond to and resolve issues.

What does Defect Density measure?

A Percentage of defects found after release

B Number of defects per size of software

C Time taken to fix a defect

D Total number of test cases executed

Defect Density measures how many defects exist per unit size of the software, like per thousand lines of code.

Defect Leakage refers to:

A Defects missed in testing but found later

B Defects found during testing

C Defects fixed before release

D Defects reported by developers

Defect Leakage means bugs that were not caught during testing but were found after release.

How do you calculate Defect Removal Efficiency (DRE)?

A (Defects found during testing) / (Total defects) × 100%

B (Defects found after release) / (Total defects) × 100%

C (Total defects) / (Defects found during testing) × 100%

D (Defects fixed) / (Defects reported) × 100%

DRE is the percentage of defects found during testing out of all defects found before and after release.

Why is Defect Age tracked?

A To count defects found in production

B To measure how many defects exist

C To know how long defects remain open before fixing

D To calculate defect density

Defect Age tracks the time between defect reporting and fixing to monitor response speed.

Which metric helps understand testing effectiveness?

A Defect Density

B Defect Leakage

C Defect Age

D Defect Removal Efficiency

Defect Removal Efficiency shows how well testing caught defects before release.

Describe the key defect metrics used to measure software quality.

Think about metrics that count defects, measure testing success, and track fix times.

Explain how Defect Removal Efficiency helps improve the testing process.

Consider how catching more defects before release benefits the team.

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