Quality metrics and measurement in Software Engineering - Step-by-Step Execution

Concept Flow - Quality metrics and measurement

Define Quality Goals

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Select Metrics to Measure

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Collect Data

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Analyze Metrics

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Make Decisions / Improvements

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Repeat Measurement Cycle

This flow shows how quality goals lead to selecting metrics, collecting data, analyzing results, and making improvements in a cycle.

Execution Sample

Software Engineering

Metric: Defect Density = Number of Defects / Size of Software
Collect defects found in testing
Calculate defect density
Analyze if defect density meets quality target

This example calculates defect density to measure software quality by counting defects per size unit.

Analysis Table

Step	Action	Data Collected	Calculation	Result/Decision
1	Define quality goal	Goal: Reduce defects	N/A	Focus on defect metrics
2	Select metric	Defect Density	Defect Density = Defects / KLOC	Metric chosen
3	Collect data	Defects found: 50, Size: 10 KLOC	N/A	Ready for calculation
4	Calculate metric	N/A	50 / 10 = 5 defects/KLOC	Defect density = 5
5	Analyze result	Defect density = 5	Compare to target < 3	Quality below target
6	Make decision	Quality below target	Plan improvements	Schedule code review and testing
7	Repeat cycle	After improvements	Measure again	Expect defect density to decrease

💡 Cycle repeats until quality goals are met or adjusted

State Tracker

Variable	Start	After Step 3	After Step 4	After Step 5	Final
Defects	0	50	50	50	50
Size (KLOC)	0	10	10	10	10
Defect Density	N/A	N/A	5	5	Expected to decrease

Key Insights - 3 Insights

Why do we calculate defect density instead of just counting defects?

Because defect density relates defects to software size, giving a fair quality measure regardless of project size, as shown in step 4 of the execution_table.

What happens if defect density is higher than the target?

The analysis step (step 5) shows quality is below target, so decisions are made to improve quality, like extra testing or code reviews (step 6).

Why repeat the measurement cycle?

Quality measurement is ongoing; after improvements, metrics are collected again to check progress, as shown in step 7.

Visual Quiz - 3 Questions

Look at the execution_table, what is the defect density calculated at step 4?

A 5 defects per KLOC

B 50 defects total

C 10 KLOC size

D 3 defects per KLOC

💡 Hint

Check the 'Calculation' and 'Result/Decision' columns at step 4 in the execution_table.

At which step does the team decide to plan improvements due to quality issues?

A Step 3

B Step 5

C Step 6

D Step 7

💡 Hint

Look for the step where 'Make decision' action is taken in the execution_table.

If the number of defects was 20 instead of 50, how would the defect density at step 4 change?

A It would stay the same

B It would decrease

C It would increase

D It would be zero

💡 Hint

Refer to the variable_tracker and formula in execution_sample: Defect Density = Defects / Size.

Concept Snapshot

Quality metrics measure software attributes to track quality.
Common metric: Defect Density = Defects / Size.
Measure data, analyze results, then improve.
Repeat cycle to ensure quality goals are met.
Metrics help make objective decisions.

Full Transcript

Quality metrics and measurement involve defining quality goals, selecting appropriate metrics like defect density, collecting data such as number of defects and software size, calculating the metric, analyzing if it meets targets, making improvement decisions, and repeating the cycle. This process helps teams objectively track and improve software quality over time.