Do you know “Most of the bugs in software are due to incomplete or inaccurate functional requirements?” The software code, doesn’t matter how well it’s written, can’t do anything if there are ambiguities in requirements.
It’s better to catch the requirement ambiguities and fix them in early development life cycle. Cost of fixing the bug after completion of development or product release is too high. So it’s important to have requirement analysis and catch these incorrect requirements before design specifications and project implementation phases of SDLC.
How to measure functional software requirement specification (SRS) documents?
Well, we need to define some standard tests to measure the requirements. Once each requirement is passed through these tests you can evaluate and freeze the functional requirements.
Let’s take an example. You are working on a web based application. Requirement is as follows:
“Web application should be able to serve the user queries as early as possible”
How will you freeze the requirement in this case?
What will be your requirement satisfaction criteria? To get the answer, ask this question to stakeholders: How much response time is ok for you?
If they say, we will accept the response if it’s within 2 seconds, then this is your requirement measure. Freeze this requirement and carry the same procedure for next requirement.
We just learned how to measure the requirements and freeze those in design, implementation and testing phases.
Now let’s take other example. I was working on a web based project. Client (stakeholders) specified the project requirements for initial phase of the project development. My manager circulated all the requirements in the team for review. When we started discussion on these requirements, we were just shocked! Everyone was having his or her own conception about the requirements. We found lot of ambiguities in the ‘terms’ specified in requirement documents, which later on sent to client for review/clarification.
Client used many ambiguous terms, which were having many different meanings, making it difficult to analyze the exact meaning. The next version of the requirement doc from client was clear enough to freeze for design phase.
From this example we learned “Requirements should be clear and consistent”
Next criteria for testing the requirements specification is “Discover missing requirements”
Many times project designers don’t get clear idea about specific modules and they simply assume some requirements while design phase. Any requirement should not be based on assumptions. Requirements should be complete, covering each and every aspect of the system under development.
Specifications should state both type of requirements i.e. what system should do and what should not.
Generally I use my own method to uncover the unspecified requirements. When I read the software requirements specification document (SRS), I note down my own understanding of the requirements that are specified, plus other requirements SRS document should supposed to cover. This helps me to ask the questions about unspecified requirements making it clearer.
For checking the requirements completeness, divide requirements in three sections, ‘Must implement’ requirements, requirements those are not specified but are ‘assumed’ and third type is ‘imagination’ type of requirements. Check if all type of requirements are addressed before software design phase.
Check if the requirements are related to the project goal.
Some times stakeholders have their own expertise, which they expect to come in system under development. They don’t think if that requirement is relevant to project in hand. Make sure to identify such requirements. Try to avoid the irrelevant requirements in first phase of the project development cycle. If not possible ask the questions to stakeholders: why you want to implement this specific requirement? This will describe the particular requirement in detail making it easier for designing the system considering the future scope.
But how to decide the requirements are relevant or not?Simple answer: Set the project goal and ask this question: If not implementing this requirement will cause any problem achieving our specified goal? If not, then this is irrelevant requirement. Ask the stakeholders if they really want to implement these types of requirements.
In short requirements specification (SRS) doc should address following:
Project functionality (What should be done and what should not)
Software, Hardware interfaces and user interface
System Correctness, Security and performance criteria
Implementation issues (risks) if any
Conclusion:
I have covered all aspects of requirement measurement. To be specific about requirements, I will summarize requirement testing in one sentence:
“Requirements should be clear and specific with no uncertainty, requirements should be measurable in terms of specific values, requirements should be testable having some evaluation criteria for each requirement, and requirements should be complete, without any contradictions”
Testing should start at requirement phase to avoid further requirement related bugs. Communicate more and more with your stakeholder to clarify all the requirements before starting project design and implementation.
Do you have any experience testing software requirements?
Tuesday, November 9, 2010
Tuesday, November 2, 2010
Test Case Point Analysis
1. INTRODUCTION
Effective software project estimation is one of the most challenging and important activity in software project life-cycle. On time project delivery cannot be achieved without an accurate and reliable estimate. Estimates play a vital role in all phases of the software development life-cycle.
There are many popular models for estimation in vogue today. But none of the models determine the efforts needed for separate phases of the SDLC. Organizations specializing in niche areas such as providing only testing services need an estimation model that can accurately determine the size of the Application Under Test (AUT) and in turn the efforts needed to execute it. Today’s e-business applications impose new challenges for software testing. Some of the commonly known challenges are complex application scenarios, extensive third party integration, crunched testing life cycles and increased security concerns. These factors inherently make testing of e-business application far more complex and critical than conventional software testing. In no other projects is performance testing more critical than in web-based projects. Underestimating a testing project leads to under-staffing it (resulting in staff burnout), under-scoping the
quality assurance effort (running the risk of low quality deliverables), and setting too short a schedule (resulting in loss of credibility as deadlines are missed). Traditionally, estimation of efforts for testing has been more of a ballpark percentage of the rest of the development life cycle phases. This approach to estimation is more prone to errors and carries a bigger risk of delaying the launch deadlines.
TCP analysis is an approach for doing an accurate estimation of functional testing projects. This approach emphasizes on key testing factors that determine the complexity of the entire testing
cycle and gives us a way of translating test creation efforts to test execution efforts, which is very useful for regression testing estimation. In other words Test Case Points is a way of representing the efforts involved in testing projects.
2. TCP METHODOLOGY
As stated above, TCP analysis generates test efforts for separate testing activities. This is essential because testing projects fall under four different models. Though in practice, most testing projects are a combination of the four execution models stated below.
Model I – Test Case Generation
This includes designing well-defined test cases. The deliverables here are only the test cases.
Model II – Automated Script Generation
This execution model includes only automating the test cases using an automated test tool. The
deliverables include the tool generated scripts
Model III – Manual Test Execution
This execution model only involves executing the test cases already designed and reporting the
defects.
Model IV – Automated Test Execution
This phase includes the execution of the automated scripts and reporting the defects.
TCP Analysis uses a 7-step process consisting of the following stages:
1. Identify Use Cases
2. Identify Test Cases
3. Determine TCP for Test Case Generation
4. Determine TCP for Automation
5. Determine TCP for Manual Execution
6. Determine TCP for Automated Execution
7. Determine Total TCP
Given below is an overview of different phases as applied to the four project execution models.Each phase is explained in detail in subsequent sections. Determine TCP for Test Case Generation To determine the TCP for Test Case Generation, first determine the complexity of the Test Cases. Some test cases may be more complex due to the inherent functionality being tested. The complexity will be an indicator of the number of TCPs for the test case.
Calculate test case generation complexity based on the factors given below.
Sl.No Test Case Generation Complexity Factors Weights
1 The number of steps in the case –
Assuming that test cases are atomic and that they test only one
condition, the number of steps will be an indicator of the complexity. 2
2 Interface with other Test Cases
This usually involves calling other test cases from this use case. Ex.
Address Book lookup from Compose Mail 1
3 Establishing a baseline result
e.g. Testing an EMI Calculator would involve validating the formulae
used.
This would typically be complex 3
Note: The above given weights are just sample weights and should not be mistaken for
benchmarks.
– Determine the complexity based on the following table:
Number of Steps Weight
<5 1
5-10 2
>10 3
* The standard weights range from 0 to 3.
0 —-> Not Applicable
1 —-> Simple
2 —-> Average
3 —-> Complex
Calculate the sum of the above weights and determine the complexity of each test case.
Calculate the Rough Test Case Points for test generation by using the table below.
Test Case Type Complexity Weights Test Case Points
Simple < 9 6
Average < 10-16 8
Complex >16 12
Calculate Test Case Points by using the below formulae
Rough TCP-G = ( # of Simple Test Cases X 6 ) + ( # of Average Test Cases X 8 ) + ( # of
Complex Test Cases X 12 )
The TCP estimates above might be affected by certain application level parameters. For
example, if the AUT is a vertical portal (e.g. Insurance), then creating test cases would involve an
understanding of the insurance business. This might increase the effort required. To factor the
impact of such parameters, we will increase the TCP by an Adjustment Factor. Some of the
Application level parameters that might have an influence on the TCP are listed in the table
below:
Sl. No. Factors Adjusted Weight
1 Design Complexity 0.1
2 Integration with other
devices such as WAP
enabled devices, etc. 0.1
1 Multi-lingual Support 0.05
4 Total Factor 0.25
The weights in the table are only indicative and will be subject to the application for which
estimation is being carried out.
Adjustment Factor = 1 + Total Factor = 1 + 0.25 = 1.25
Each of these factors is scored based on their influence on the system being counted. The
resulting score will increase the Unadjusted Test Case Point count. This calculation provides us
with the Test Case Point Generation count.
TCP-G = Rough TCP -Generation X Adjustment Factor
2.1 Determine TCP for Automation
From the list of Test Cases derived from Section 2.2, identify the test cases that are good
candidates for automation. Some test cases save a lot of effort if done manually and is not worth
automating. On the other hand, some test cases cannot be automated because the test tool does
not support the feature being tested.
Certain cases are straightforward and are quite easy to automate whereas certain cases involving
dynamic data are difficult to automate. Next, determine the test case automation complexity
based on the factors given below.
Sl.No Test Case Automation Complexity Factors Weights
1 Interface with other Test Cases
This usually involves calling other test cases from this use case. Ex.
Address Book lookup from Compose Mail 2
2 Interface with external application
This is interaction with an application that is outside the system boundary.
Ex. Credit Card validations through an independent gateway 0
3 External Application Validation
This involves testing of third party applications to validate the use case.
Ex. Checking Word, PDF reports generated by the system 0
4 Data Driven
This is usually helpful for testing the use case with positive and negative
data. Ex. User Registration 2
5 Links
# of links to be tested for broken/orphaned links. Typically, dynamic lists
like catalog items are rated as complex. 1
6 Numerical Computations
This involves validation of arithmetical calculations.
e.g. Testing an EMI Calculator would involve validating the formulae used.
This would typically be complex. 1
7 Check Points
This involves modifying the test scripts to check for validations.
Ex. Page titles, buttons, labels, null values, max char, numeric etc 1
8 Database Check Points
This involves cross checking the database values for integrity.
Ex. Check database after user registration for proper values. 0
9 UI ComponentsThese are usually Applets, ActiveX etc 0
Note: The above given weights are just sample weights and should not be mistaken for
benchmarks.
* The standard weights range from 0 to 3.
0 —-> Not Applicable
1 —-> Simple
2 —-> Average
3 —-> Complex
Calculate the sum of the above weights and determine the complexity of each test case.
From the complexity, calculate the Test Case Points for test automation by using the table below.
Test Case Type Complexity Weights Test Case Points
Simple < 9 6
Average < 10-16 8
Complex >16 12
TCP-A (Single Scenario) = ( # of Simple Test Cases X 6 ) + ( # of Average Test Cases X 8 ) + (
# of Complex Test Cases X 12 )
e-biz applications need to be tested on various configurations because they can be accessed
from anywhere and from an uncontrolled environment. A scenario is basically a combination of a
browser, operating system and hardware.
Sometimes, the application by its nature of usage might demand testing on different scenarios.
The TCPs identified above need to be modified to factor the impact of multiple scenarios.
The extra effort needed can be obtained by answering the following two questions:
Ø Can the scripts generated for a single scenario be run on multiple scenarios?
Ø Do the scripts generated for a single scenario need to be re-generated because the
automation tool does not support a scenario?
To arrive at the additional Test Case Points, we will identify the test cases (from section 3.2) that
need to be re-generated for every additional scenario.
The TCP-A (single scenario) will be added for every scenario for which regeneration is required.
For example, assume that the test case checks for an applet condition in Internet Explorer 5.0
and Windows NT and the TCP -A comes out to be 6. Further, the test tool does not support the
same script for Netscape Navigator 4.7 and Solaris. So the script needs to be regenerated. In
this case, the Total TCP -A comes out to be 12 for the 2 different scripts.
2.2 Determine TCP for Manual Execution
To determine the TCPs for Manual Execution, first calculate the manual test case execution complexity based on the factors given below.
Sl.No Manual Execution Complexity Factors Weights
1 Pre-conditions
This usually involves setting up the test data. It also includes
the steps needed before starting the execution. E.g. to test
whether the printing facility is working fine, the pre-conditions
would include opening the application, inserting a record into
the database, generating a report and then checking the
printing facility. 2
2 Steps in the Test Case
If the steps themselves are complex, the manual execution
effort will increase. Please refer to the legend below to
determine the complexity factor. 1
3 Verification
The verification itself might be complex. For example,
checking the actual result might itself involve many steps.
Let’s say in a test case, we need to check the server logs, it
might need opening up the log analyzer and verifying the
statistics. 2
Note: The above given weights are just sample weights and should not be mistaken for benchmarks.
Number of Steps Weight
<5 1
5-10 2
>10 3
The standard weights range from 0 to 3.
0 —-> Not Applicable
1 —-> Simple
2 —-> Average
3 —-> Complex
Calculate the sum of the above weights and determine the complexity of each test case.
Calculate the Test Case Points for manual execution by using the table below.
Test Case Type Complexity Weights Test Case Points
Simple < 9 6
Average < 10-16 8
Complex >16 12
TCP-ME = ( # of Simple Test Cases X 6 ) + ( # of Average Test Cases X 8 ) + ( # of Complex
Test Cases X 12 )
Test Cases need to be manually executed in all the scenarios. To arrive at the additional Test
Case Points, the TCP -ME (single scenario) will be added for every scenario for which manual
execution is required.
2.3 Determine TCP for Automated Execution
To determine the TCP for Automated Execution, calculate the automation test case execution complexity based on the factors given below.
Note: The above given weights are just sample weights and should not be mistaken for
benchmarks.
The standard weights range from 0 to 3.
0 —-> Not Applicable
1 —-> Simple
2 —-> Average
3 —-> Complex
Calculate the sum of the above weights and determine the complexity of each test case.
Calculate the Test Case Points for automated execution by using the table below.
Sl.No Test Case Complexity Factors Weights
1 Pre-conditions
This usually involves setting up the test data. It also includes
the steps needed before starting the execution. E.g. to test
whether the printing facility is working fine, the pre-conditions
would include opening the application, inserting a record into
the database, generating a report and then checking the
printing facility. 2
Test Case Type Complexity Weights Test Case Points
Simple < 9 6
Average < 10-16 8
Complex >16 12
TCP-AE = ( # of Simple Test Cases X 6 ) + ( # of Average Test Cases X 8 ) + ( # of Complex Test
Cases X 12 )
2.4 Calculate Total TCP
The Total TCP is computed by summing up the individual TCPs for Test Case Generation, Test Automation and Test Execution.
TCP-T = TCP-G + TCP-A + TCP-ME + TCP-AE
The total TCP is indicative of the size of the testing project.
3. EFFORT CALCULATION
To translate the Test Case Points into the total person months involved, based on your prior experience estimate the number of test case points per person month.
Effective software project estimation is one of the most challenging and important activity in software project life-cycle. On time project delivery cannot be achieved without an accurate and reliable estimate. Estimates play a vital role in all phases of the software development life-cycle.
There are many popular models for estimation in vogue today. But none of the models determine the efforts needed for separate phases of the SDLC. Organizations specializing in niche areas such as providing only testing services need an estimation model that can accurately determine the size of the Application Under Test (AUT) and in turn the efforts needed to execute it. Today’s e-business applications impose new challenges for software testing. Some of the commonly known challenges are complex application scenarios, extensive third party integration, crunched testing life cycles and increased security concerns. These factors inherently make testing of e-business application far more complex and critical than conventional software testing. In no other projects is performance testing more critical than in web-based projects. Underestimating a testing project leads to under-staffing it (resulting in staff burnout), under-scoping the
quality assurance effort (running the risk of low quality deliverables), and setting too short a schedule (resulting in loss of credibility as deadlines are missed). Traditionally, estimation of efforts for testing has been more of a ballpark percentage of the rest of the development life cycle phases. This approach to estimation is more prone to errors and carries a bigger risk of delaying the launch deadlines.
TCP analysis is an approach for doing an accurate estimation of functional testing projects. This approach emphasizes on key testing factors that determine the complexity of the entire testing
cycle and gives us a way of translating test creation efforts to test execution efforts, which is very useful for regression testing estimation. In other words Test Case Points is a way of representing the efforts involved in testing projects.
2. TCP METHODOLOGY
As stated above, TCP analysis generates test efforts for separate testing activities. This is essential because testing projects fall under four different models. Though in practice, most testing projects are a combination of the four execution models stated below.
Model I – Test Case Generation
This includes designing well-defined test cases. The deliverables here are only the test cases.
Model II – Automated Script Generation
This execution model includes only automating the test cases using an automated test tool. The
deliverables include the tool generated scripts
Model III – Manual Test Execution
This execution model only involves executing the test cases already designed and reporting the
defects.
Model IV – Automated Test Execution
This phase includes the execution of the automated scripts and reporting the defects.
TCP Analysis uses a 7-step process consisting of the following stages:
1. Identify Use Cases
2. Identify Test Cases
3. Determine TCP for Test Case Generation
4. Determine TCP for Automation
5. Determine TCP for Manual Execution
6. Determine TCP for Automated Execution
7. Determine Total TCP
Given below is an overview of different phases as applied to the four project execution models.Each phase is explained in detail in subsequent sections. Determine TCP for Test Case Generation To determine the TCP for Test Case Generation, first determine the complexity of the Test Cases. Some test cases may be more complex due to the inherent functionality being tested. The complexity will be an indicator of the number of TCPs for the test case.
Calculate test case generation complexity based on the factors given below.
Sl.No Test Case Generation Complexity Factors Weights
1 The number of steps in the case –
Assuming that test cases are atomic and that they test only one
condition, the number of steps will be an indicator of the complexity. 2
2 Interface with other Test Cases
This usually involves calling other test cases from this use case. Ex.
Address Book lookup from Compose Mail 1
3 Establishing a baseline result
e.g. Testing an EMI Calculator would involve validating the formulae
used.
This would typically be complex 3
Note: The above given weights are just sample weights and should not be mistaken for
benchmarks.
– Determine the complexity based on the following table:
Number of Steps Weight
<5 1
5-10 2
>10 3
* The standard weights range from 0 to 3.
0 —-> Not Applicable
1 —-> Simple
2 —-> Average
3 —-> Complex
Calculate the sum of the above weights and determine the complexity of each test case.
Calculate the Rough Test Case Points for test generation by using the table below.
Test Case Type Complexity Weights Test Case Points
Simple < 9 6
Average < 10-16 8
Complex >16 12
Calculate Test Case Points by using the below formulae
Rough TCP-G = ( # of Simple Test Cases X 6 ) + ( # of Average Test Cases X 8 ) + ( # of
Complex Test Cases X 12 )
The TCP estimates above might be affected by certain application level parameters. For
example, if the AUT is a vertical portal (e.g. Insurance), then creating test cases would involve an
understanding of the insurance business. This might increase the effort required. To factor the
impact of such parameters, we will increase the TCP by an Adjustment Factor. Some of the
Application level parameters that might have an influence on the TCP are listed in the table
below:
Sl. No. Factors Adjusted Weight
1 Design Complexity 0.1
2 Integration with other
devices such as WAP
enabled devices, etc. 0.1
1 Multi-lingual Support 0.05
4 Total Factor 0.25
The weights in the table are only indicative and will be subject to the application for which
estimation is being carried out.
Adjustment Factor = 1 + Total Factor = 1 + 0.25 = 1.25
Each of these factors is scored based on their influence on the system being counted. The
resulting score will increase the Unadjusted Test Case Point count. This calculation provides us
with the Test Case Point Generation count.
TCP-G = Rough TCP -Generation X Adjustment Factor
2.1 Determine TCP for Automation
From the list of Test Cases derived from Section 2.2, identify the test cases that are good
candidates for automation. Some test cases save a lot of effort if done manually and is not worth
automating. On the other hand, some test cases cannot be automated because the test tool does
not support the feature being tested.
Certain cases are straightforward and are quite easy to automate whereas certain cases involving
dynamic data are difficult to automate. Next, determine the test case automation complexity
based on the factors given below.
Sl.No Test Case Automation Complexity Factors Weights
1 Interface with other Test Cases
This usually involves calling other test cases from this use case. Ex.
Address Book lookup from Compose Mail 2
2 Interface with external application
This is interaction with an application that is outside the system boundary.
Ex. Credit Card validations through an independent gateway 0
3 External Application Validation
This involves testing of third party applications to validate the use case.
Ex. Checking Word, PDF reports generated by the system 0
4 Data Driven
This is usually helpful for testing the use case with positive and negative
data. Ex. User Registration 2
5 Links
# of links to be tested for broken/orphaned links. Typically, dynamic lists
like catalog items are rated as complex. 1
6 Numerical Computations
This involves validation of arithmetical calculations.
e.g. Testing an EMI Calculator would involve validating the formulae used.
This would typically be complex. 1
7 Check Points
This involves modifying the test scripts to check for validations.
Ex. Page titles, buttons, labels, null values, max char, numeric etc 1
8 Database Check Points
This involves cross checking the database values for integrity.
Ex. Check database after user registration for proper values. 0
9 UI ComponentsThese are usually Applets, ActiveX etc 0
Note: The above given weights are just sample weights and should not be mistaken for
benchmarks.
* The standard weights range from 0 to 3.
0 —-> Not Applicable
1 —-> Simple
2 —-> Average
3 —-> Complex
Calculate the sum of the above weights and determine the complexity of each test case.
From the complexity, calculate the Test Case Points for test automation by using the table below.
Test Case Type Complexity Weights Test Case Points
Simple < 9 6
Average < 10-16 8
Complex >16 12
TCP-A (Single Scenario) = ( # of Simple Test Cases X 6 ) + ( # of Average Test Cases X 8 ) + (
# of Complex Test Cases X 12 )
e-biz applications need to be tested on various configurations because they can be accessed
from anywhere and from an uncontrolled environment. A scenario is basically a combination of a
browser, operating system and hardware.
Sometimes, the application by its nature of usage might demand testing on different scenarios.
The TCPs identified above need to be modified to factor the impact of multiple scenarios.
The extra effort needed can be obtained by answering the following two questions:
Ø Can the scripts generated for a single scenario be run on multiple scenarios?
Ø Do the scripts generated for a single scenario need to be re-generated because the
automation tool does not support a scenario?
To arrive at the additional Test Case Points, we will identify the test cases (from section 3.2) that
need to be re-generated for every additional scenario.
The TCP-A (single scenario) will be added for every scenario for which regeneration is required.
For example, assume that the test case checks for an applet condition in Internet Explorer 5.0
and Windows NT and the TCP -A comes out to be 6. Further, the test tool does not support the
same script for Netscape Navigator 4.7 and Solaris. So the script needs to be regenerated. In
this case, the Total TCP -A comes out to be 12 for the 2 different scripts.
2.2 Determine TCP for Manual Execution
To determine the TCPs for Manual Execution, first calculate the manual test case execution complexity based on the factors given below.
Sl.No Manual Execution Complexity Factors Weights
1 Pre-conditions
This usually involves setting up the test data. It also includes
the steps needed before starting the execution. E.g. to test
whether the printing facility is working fine, the pre-conditions
would include opening the application, inserting a record into
the database, generating a report and then checking the
printing facility. 2
2 Steps in the Test Case
If the steps themselves are complex, the manual execution
effort will increase. Please refer to the legend below to
determine the complexity factor. 1
3 Verification
The verification itself might be complex. For example,
checking the actual result might itself involve many steps.
Let’s say in a test case, we need to check the server logs, it
might need opening up the log analyzer and verifying the
statistics. 2
Note: The above given weights are just sample weights and should not be mistaken for benchmarks.
Number of Steps Weight
<5 1
5-10 2
>10 3
The standard weights range from 0 to 3.
0 —-> Not Applicable
1 —-> Simple
2 —-> Average
3 —-> Complex
Calculate the sum of the above weights and determine the complexity of each test case.
Calculate the Test Case Points for manual execution by using the table below.
Test Case Type Complexity Weights Test Case Points
Simple < 9 6
Average < 10-16 8
Complex >16 12
TCP-ME = ( # of Simple Test Cases X 6 ) + ( # of Average Test Cases X 8 ) + ( # of Complex
Test Cases X 12 )
Test Cases need to be manually executed in all the scenarios. To arrive at the additional Test
Case Points, the TCP -ME (single scenario) will be added for every scenario for which manual
execution is required.
2.3 Determine TCP for Automated Execution
To determine the TCP for Automated Execution, calculate the automation test case execution complexity based on the factors given below.
Note: The above given weights are just sample weights and should not be mistaken for
benchmarks.
The standard weights range from 0 to 3.
0 —-> Not Applicable
1 —-> Simple
2 —-> Average
3 —-> Complex
Calculate the sum of the above weights and determine the complexity of each test case.
Calculate the Test Case Points for automated execution by using the table below.
Sl.No Test Case Complexity Factors Weights
1 Pre-conditions
This usually involves setting up the test data. It also includes
the steps needed before starting the execution. E.g. to test
whether the printing facility is working fine, the pre-conditions
would include opening the application, inserting a record into
the database, generating a report and then checking the
printing facility. 2
Test Case Type Complexity Weights Test Case Points
Simple < 9 6
Average < 10-16 8
Complex >16 12
TCP-AE = ( # of Simple Test Cases X 6 ) + ( # of Average Test Cases X 8 ) + ( # of Complex Test
Cases X 12 )
2.4 Calculate Total TCP
The Total TCP is computed by summing up the individual TCPs for Test Case Generation, Test Automation and Test Execution.
TCP-T = TCP-G + TCP-A + TCP-ME + TCP-AE
The total TCP is indicative of the size of the testing project.
3. EFFORT CALCULATION
To translate the Test Case Points into the total person months involved, based on your prior experience estimate the number of test case points per person month.
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