Importance of Software Testing Metrics and 8 Ways to Measure It

16 / Dec / 2016 by Mohit Tyagi 1 comments

What is Software Testing Metrics?

Software testing metrics provide quantitative approach to measure the quality and effectiveness of the software development and testing process. It helps the team to keep a track on the software quality at every stage in the software development cycle and also provides information to control and reduce the number of errors. It allows the stakeholders to measure the efficiency of the team and accelerates application delivery.

For example: A test manager must measure the effectiveness of a test process to identify the areas of improvement.

While working on various testing projects at TO THE NEW we make sure to follow the software testing metrics for our clients to release a high-quality software.

Following snapshots below highlights the progress on text execution and the defects identification for one of our client

Why to Measure Software Quality?

  • To evaluate the quality of the current product or process
  • To improve quality of a product /process by continuous monitoring
  • Take decisions based on analysis

Test Execution Progress1

2

Types of Metrics

It is imperative to understand the different types of metrics to measure the quality of the software. A manual testing metrics comprises of two other metrics – Base Metrics and Calculated Metrics.

Base Metrics: It comprises the raw data captured by the test engineer during the testing process.

Few examples of Base Metrics are:

– No. of test cases
– No. of test cases executed

Calculated Metrics: It is obtained by converting the data that is gathered in Base Metrics into useful information.

Few examples of Calculated Metrics are:

– Test coverage
– Test efficiency

Importance of Metrics

• Metrics is used to improve the quality of products and services thus helps in achieving customer satisfaction.
• Different metrics helps the teams to monitor the efficiency of the process and control them
• It provides the scope of improvement for current process.

Metrics Lifecycle

1. Analysis
– Identify and define the metrics
– Define parameters for evaluating the metrics

2. Communicate
– Explain the need and significance of metrics to stakeholders and testing team
– Educate the testing team about the data points need to be captured for processing the metric

3. Evaluation
– Capture the required data
– Verify validity of the data captured
– Calculate the metrics value

4. Reports 
– Develop the report with effective conclusion
– Distribute the reports to the stakeholders, developer and the testing team
– Take feedback for further improvements

8 Useful Software Testing Metrics

Here is a list of 8 useful and effective software metrics the team must leverage

1. Test Case Productive Prepration

= Total test steps / effort (hours)

e.g TPP = 60/8 = 7.5
8 test cases / hour

2. Test Execution Summary

Summarize your reports with the following parameters such as

  • Test Case Passed
  • Test Case Failed
  • Test Case Executed
  • Test Case Not Executed
  • Test Case Blocked

3. Test Case Coverage

= [Executed Test cases / total no. of test cases] * 100

4. Defect Acceptance
= [Number of valid defects / total no. of defects] * 100

5. Defect Rejection
= [Number of invalid defects / total no. of defects] * 100

6. Test Efficiency
= [DT / (DT + DU)] * 100

DT = Defect by Testing team & Development team

DU = Defect by customer

7. Effort Variance

= [(Actual effort – estimated effort) / estimated effort] * 100

From the above formula, we can conclude that:
• If Effort Variance is positive, this means we took extra time (effort) to complete the planned work.
• If Effort Variance is negative, this means we took less time (effort) to complete the planned work.
• If Effort Variance is zero, this means you are on the estimated effort.

8. Schedule Variance
= [(Actual no. of days – estimated no. of days) / estimated no. of days)] * 100

From the above formula, we can conclude that:
• If Schedule Variance is positive, this means you are ahead of the schedule.
• If Schedule Variance is negative, this means you are behind the schedule.
• If Schedule Variance is zero, this means you are on the schedule.

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