Answer / chennamsubbaraidu

Metric Means Measurement .It Plays a Important role in
Testing.It Helps Monitoring the Health of the
Project/application.
It will Define Scale upto What level of Testing can Achevied
by doing Particular Testing on Application in the Scale of 100%

Answer / a.raji

Metrics are the unit of measurement which are used for
validating the efficiency of the Process

Answer / vijaya

Metric is an entity to measure particular effort or activity

Answer / sachin vaidya (blue star infot

Metric Means Measurement .Matic used for to find the
coverage of requirement and up to what level we reach the
requirement. It's nothinig but the mapping of requirement
and test cases.It Plays a Important role in
Testing.It Helps Monitoring the Health of the
Project/application

Answer / neeraj

Test matrics is way of requirement mapping thus means all
requriment is properly covered or not.......

Answer / ravi

prepare the table like Number of testcases Vs Functional,
Number of testcases exectued, Number of test cases are
passed and failed, Number of bugs found, Number of bugs are
closed on certain period.... to meet requiremnt of our
project

Answer / helen cathrine

Metrics used to measure the quality of the application
being tested. Through different formulas metrics can be
derived.

Answer / prasad

Important Software Test Metrics and Measurements – Explained with Examples and Graphs
Posted In | Bug Defect tracking, Testing Concepts | Last Updated: "June 26, 2015"
In software projects, it is most important to measure the quality, cost and effectiveness of the project and the processes. Without measuring these, project can’t be completed successfully.
In today’s article we will learn with examples and graphs – Software test metrics and measurements and how to use these in software testing process.
There is a famous statement: “We can’t control things which we can’t measure”.
Here controlling the projects means, how a project manager/lead can identify the deviations from the test plan ASAP in order to react in the perfect time. Generation of test metrics based on the project needs is very much important to achieve the quality of the software being tested.

What are Software Testing Metrics?
A Metric is a quantitative measure of the degree to which a system, system component, or process possesses a given attribute.
Metrics can be defined as “STANDARDS OF MEASUREMENT”.
Software Metrics are used to measure the quality of the project. Simply, Metric is a unit used for describing an attribute. Metric is a scale for measurement.
Suppose, in general, “Kilogram” is a metric for measuring the attribute “Weight”. Similarly, in software, “How many issues are found in thousand lines of code?”, here No. of issues is one measurement & No. of lines of code is another measurement. Metric is defined from these two measurements.
Test metrics example:
• How many defects are existed within the module?
• How many test cases are executed per person?
• What is the Test coverage %?
What is Software Test Measurement?
Measurement is the quantitative indication of extent, amount, dimension, capacity, or size of some attribute of a product or process.
Test measurement example: Total number of defects.
Please refer below diagram for clear understanding of the difference between Measurement & Metrics.

Why Test Metrics?
Generation of Software Test Metrics is the most important responsibility of the Software Test Lead/Manager.
Test Metrics are used to,
1. Take the decision for next phase of activities such as, estimate the cost & schedule of future projects.
2. Understand the kind of improvement required to success the project
3. Take decision on process or technology to be modified etc.
Importance of Software Testing Metrics:
As explained above, Test Metrics are the most important to measure the quality of the software.
Now, how can we measure the quality of the software by using Metrics?
Suppose, if a project does not have any metrics, then how the quality of the work done by a Test analyst will be measured?
For Example: A Test Analyst has to,
1. Design the test cases for 5 requirements
2. Execute the designed test cases
3. Log the defects & need to fail the related test cases
4. After the defect is resolved, need to re-test the defect & re-execute the corresponding failed test case.
In above scenario, if metrics are not followed, then the work completed by the test analyst will be subjective i.e. the test reportwill not have the proper information to know the status of his work/project.
If Metrics are involved in the project, then the exact status of his/her work with proper numbers/data can be published.
I.e. in the Test report, we can publish:
1. How many test cases have been designed per requirement?
2. How many test cases are yet to design?
3. How many test cases are executed?
4. How many test cases are passed/failed/blocked?
5. How many test cases are not yet executed?
6. How many defects are identified & what is the severity of those defects?
7. How many test cases are failed due to one particular defect? etc.
Based on the project needs we can have more metrics than above mentioned list, to know the status of the project in detail.
Based on the above metrics, test lead/manager will get the understanding of the below mentioned key points.
a) %ge of work completed
b) %ge of work yet to be completed
c) Time to complete the remaining work
d) Whether the project is going as per the schedule or lagging? etc.
Based on the metrics, if the project is not going to complete as per the schedule, then the manager will raise the alarm to the client and other stake holders by providing the reasons for lagging to avoid the last minute surprises.
Metrics Life Cycle:

Types of Manual Test Metrics:
Testing Metrics are mainly divided into 2 categories.
1. Base Metrics
2. Calculated Metrics
Base Metrics:
Base Metrics are the Metrics which are derived from the data gathered by the Test Analyst during the test case development and execution.
This data will be tracked throughout the Test Life cycle. I.e. collecting the data like, Total no. of test cases developed for a project (or) no. of test cases need to be executed (or) no. of test cases passed/failed/blocked etc.
Calculated Metrics:
Calculated Metrics are derived from the data gathered in Base Metrics. These Metrics are generally tracked by the test lead/manager for Test Reporting purpose.
Examples of Software Testing Metrics:
Let’s take an example to calculate various test metrics used in software test reports:
Below is the table format for the data retrieved from the test analyst who is actually involved in testing:

Definitions and Formulas for Calculating Metrics:
#1) %ge Test cases Executed: This metric is used to obtain the execution status of the test cases in terms of %ge.
%ge Test cases Executed = (No. of Test cases executed / Total no. of Test cases written) * 100.
So, from the above data,
%ge Test cases Executed = (65 / 100) * 100 = 65%
#2) %ge Test cases not executed: This metric is used to obtain the pending execution status of the test cases in terms of %ge.
%ge Test cases not executed = (No. of Test cases not executed / Total no. of Test cases written) * 100.
So, from the above data,
%ge Test cases Blocked = (35 / 100) * 100 = 35%
------------



#3) %ge Test cases Passed: This metric is used to obtain the Pass %ge of the executed test cases.
%ge Test cases Passed = (No. of Test cases Passed / Total no. of Test cases Executed) * 100.
So, from the above data,
%ge Test cases Passed = (30 / 65) * 100 = 46%
#4) %ge Test cases Failed: This metric is used to obtain the Fail %ge of the executed test cases.
%ge Test cases Failed = (No. of Test cases Failed / Total no. of Test cases Executed) * 100.
So, from the above data,
%ge Test cases Passed = (26 / 65) * 100 = 40%
#5) %ge Test cases Blocked: This metric is used to obtain the blocked %ge of the executed test cases. A detailed report can be submitted by specifying the actual reason of blocking the test cases.
%ge Test cases Blocked = (No. of Test cases Blocked / Total no. of Test cases Executed) * 100.
So, from the above data,
%ge Test cases Blocked = (9 / 65) * 100 = 14%


#6) Defect Density = No. of Defects identified / size
(Here “Size” is considered as requirement. Hence here the Defect Density is calculated as number of defects identified per requirement. Similarly, Defect Density can be calculated as number of Defects identified per 100 lines of code [OR] No. of defects identified per module etc.)
So, from the above data,
Defect Density = (30 / 5) = 6
#7) Defect Removal Efficiency (DRE) = (No. of Defects found during QA testing / (No. of Defects found during QA testing +No. of Defects found by End user)) * 100
DRE is used to identify the test effectiveness of the system.
Suppose, During Development & QA testing, we have identified 100 defects.
After the QA testing, during Alpha & Beta testing, end user / client identified 40 defects, which could have been identified during QA testing phase.
Now, The DRE will be calculated as,
DRE = [100 / (100 + 40)] * 100 = [100 /140] * 100 = 71%
$8) Defect Leakage: Defect Leakage is the Metric which is used to identify the efficiency of the QA testing i.e., how many defects are missed / slipped during the QA testing.
Defect Leakage = (No. of Defects found in UAT / No. of Defects found in QA testing.) * 100
Suppose, During Development & QA testing, we have identified 100 defects.
After the QA testing, during Alpha & Beta testing, end user / client identified 40 defects, which could have been identified during QA testing phase.
Defect Leakage = (40 /100) * 100 = 40%
#9) Defects by Priority: This metric is used to identify the no. of defects identified based on the Severity / Priority of the defect which is used to decide the quality of the software.
%ge Critical Defects = No. of Critical Defects identified / Total no. of Defects identified * 100
From the data available in the above table,
%ge Critical Defects = 6/ 30 * 100 = 20%
%ge High Defects = No. of High Defects identified / Total no. of Defects identified * 100
From the data available in the above table,
%ge High Defects = 10/ 30 * 100 = 33.33%
%ge Medium Defects = No. of Medium Defects identified / Total no. of Defects identified * 100
From the data available in the above table,
%ge Medium Defects = 6/ 30 * 100 = 20%
%ge Low Defects = No. of Low Defects identified / Total no. of Defects identified * 100
From the data available in the above table,
%ge Low Defects = 8/ 30 * 100 = 27%

Recommended reading => How to Write an Effective Test Summary Report
Conclusion:
The metrics provided in this article are majorly used for generating the daily/weekly status report with accurate data during test case development/execution phase & this is also useful for tracking the project status & Quality of the software.
About the author: This is a guest post by Anuradha K. She is having 7+ years of software testing experience and currently working as a consultant for a MNC. She is also having good knowledge of mobile automation testing.

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