Understanding the Importance & Classification of Test Metrics in Software Engineering, Lecture notes of Software Engineering

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Software Verification and Validation

Lecture No. 18

Module 120:

Software Test Metrics

Software Test Metrics  (^) The aim of collecting test metrics is to use the data for improving the test process, rather than to just show fancy reports.  (^) This includes finding tangible answers to the questions:  (^) How long will it take to test?  (^) How much money will it take to test?  (^) How bad are the bugs?  (^) How many bugs found were fixed? reopened? closed? deferred?

Software Test Metrics

 How many bugs did the

test team did not find?

 How much of the software

was tested?

 Will testing be done on

time? Can the software be

shipped on time?

 How good were the tests?

Are we using low-value test

cases?

 What is the cost of testing?

 Was the test effort

adequate? Could we have

fit more testing in this

release?

Software Metrics

Processes, Products, Services

Engineering information

Management information

Applied to To improve (^) To supply

Module 121:

Importance of Test Metrics

Software Test Metrics  (^) We need test metrics to:  (^) Track and control phases of testing and fixing  (^) Find out if the system is ready for release  (^) Improve our inhouse process  (^) Find out if our testing process is efficient  (^) Find out when to stop testing  (^) Do trend analysis  (^) Meet client expectations and customer needs

Software Test Metrics

 We also need to classify the

Test metric with respect to:

 Quality

 Productivity

 Cost

 Defect

 Coverage

 Effort

 Stability

 Effectiveness

END

Module 122:

Test Metrics Lifecyle

Test Metrics Lifecycle

Analysis Stage:

Identify Metrics to use

Define Metrics and parameters

Evaluation Stage:

Capture and Verify Data

Calculate metrics values using data

Reporting Stage:

Share report with stakeholders

Collect feedback

END

Module 123:

Test Metrics Classification

Test Metrics Classification

 (^) Performance Testing Metrics  (^) Performance scripting productivity  (^) Performance execution summary  (^) Performance Efficiency  (^) Performance severity Index  (^) Automation Testing Metrics  (^) Automation scripting productivity  (^) Automation test execution productivity  (^) Automation coverage  (^) Cost comparison

Test Metrics Classification

 General / Common metrics

 Effort variance

 Schedule variance

 Scope change

END

Defect Related Metrics

 Defect Acceptance helps determines number of valid defects that

testing team identified during execution.  (^) Value of this metric is compared with previous releases for a clearer picture

Number of Valid Defects

Defect Acceptance = * 100 %

Total Number of Defects

Defect Related Metrics

 Defect Rejection

 This metric determine the number of defects rejected during

execution.

 It gives the percentage of the invalid defect the testing team

has opened and one can control, whenever required.

Number of Defect(s) Rejected

Defect Rejection = * 100 %

Total Number of Defects