The document discusses a method called qsize analysis for estimating the size and effort of software testing activities, addressing current challenges in reliable estimation methods. It introduces a toolkit and principles based on test case complexity, effort estimation methods, and calibration to improve the accuracy of test planning and execution. The conclusion emphasizes qsize analysis as an agile approach, while highlighting its advantages and the need for further empirical validation.

2. Agenda
• Background and Motivation
• qSize Analysis
– Test Size Estimation (Test Case Point Analysis)
– Test Effort Estimation
• Conclusion
2

3. Background
• Software estimation
– process of determining the cost, time, staff, and
other related attributes of software projects
• It is important for the success or failure of
software projects
• Methods and Metrics
– Source Lines of Code (SLOC)
– Function Points
– COCOMO
– Expert Judgment
3

4. Motivation
• Testing accounts for up to 50% of project
effort [1]
• Current problems
– lack of reliable methods designed for estimating
size and effort of software testing
– vague definitions of testing productivity
• Our aim is to introduce
– a method for estimating the size and effort of
testing activities
– a simple toolkit for this estimation process
4

5. Agenda
• Background and Motivation
• qSize Analysis
– Test Size Estimation (Test Case Point Analysis)
– Test Effort Estimation
• Conclusion
5

6. qSize Analysis’ Principles
• Size measures the mass and complexity of each
test cycle of a testing project
• Test case’s complexity is based on
– Number of checkpoints
– Complexity of test setup or precondition
– Complexity of test data
• Test Case Point (TCP) is used as size unit
• Calibration or model refinement is key to
estimating effort
– calibration based on feedback from previous
testing cycles
• Focusing on independent testing (V & V)
6

7. qSize Analysis’ Process
[Test Cycle i]
Count TCPs Estimate
Test Case Counted Estimated
of all Test Testing
Test Case Size
Effort
Effort
Cases
Update
Parameters Historical
Data
Calibrate
Estimation Historical Data of this Project
Model
Test Cycle Size Actual Effort by
Effort Activity
…. …. …. ….
Test cycle i …. …. ….
…. …. …. ….
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8. Count Size of Test Cycle
• Size of a test cycle is the total of TCPs of all test
cases to be executed in that test cycle
• Steps:
Count
Checkpoints
Adjust based
Test Case Determine Set Unadjusted
on Test Type TCPs
Up Complexity TCPs
(optional)
Determine Test
Data
Complexity
8

9. Count Size of Test Cycle (cont’d)
• Checkpoints
– Checkpoint is the condition in which the tester
verifies whether the result produced by the
target function matches the expected criterion
– One test case consists of one or many
checkpoints
One checkpoint is counted as one TCP
9

10. Count Size of Test Cycle (cont’d)
• Test Setup or Precondition
– Test setup specifies the condition to execute the
test case
– Four levels of Test Setup complexity
• Each is assigned a number of TCPs
Number Complexity Description
of TCP(*) Level
0 None • The set up is not applicable or important to execute the test case
• Or, the set up is just reused from the previous test case to continue the current test case
1 Low • The condition for executing the test case is available with some simple modifications required
• Or, some simple set-up steps are needed
3 Medium • Some explicit preparation is needed to execute the test case
• Or, The condition for executing is available with some additional modifications required
• Or, some additional set-up steps are needed
5 High • Heavy hardware and/or software configurations are needed to execute the test case
10

11. Count Size of Test Cycle (cont’d)
• Test Data
– Test Data is used to execute the test case
– Four levels of Test Data complexity
• Each is assigned a number of TCPs
Number Complexity Description
of TCP (*) Level
0 None • No test data preparation is needed
1 Low • Simple test data is needed and can be created during the test case execution time
• Or, the test case uses a slightly modified version of existing test data and requires little
or no effort to modify the test data
3 Medium • Test data is deliberately prepared in advance with extra effort to ensure its
completeness, comprehensiveness, and consistency
6 High • Test data is prepared in advance with considerable effort to ensure its completeness,
comprehensiveness, and consistency
• This could include using support tools to generate data and a database to store and
manage test data
• Scripts may be required to generate test data
(*) based on our survey of 18 senior QA engineers. You can adjust according to your project’s experience.

12. Count Size of Test Cycle (cont’d)
• Adjust TCPs based on Type of Test
– This is an OPTIONAL step
– Adjustment is based on types of test cases
• Each type of test case is assigned a weight
• Adjusted TCP = Counted TCP x Weight(*)
12

13. Estimate Effort of Test Cycle
• Overview
– Two estimation methods
• Based on Test Velocity
• Regression analysis of Size and Effort of
completed test cycles
– Effort distributed by activity
• Test Planning Each may be
• Test Analysis and Design performed
• Test Execution multiple
• Test Tracking and Reporting times
13

14. Estimate Effort of Test Cycle (cont’d)
• Estimate Effort based on Test Velocity
Effort = Size / Test Velocity
– Test Velocity is measured as TCP/person-hour
• dependent on project
• calculated based on data from completed test
cycles of the same project
14

15. Estimate Effort of Test Cycle (cont’d)
• Estimate effort using Linear Regression Analysis
– Find out the equation of effort and size using
similar completed test cycles of a project
100
90
80 Equation of
70
y = 0.072x + 1.640
Size and
Effort (PM)
60
Effort
50
40
30
20
10
0
0 100 200 300 400 500 600 700 800 900 1000
Adjusted TCP
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16. Calibrate the qSize Estimation Model
• Calibration: a process adjusting parameters for a
model using historical data or experiences
• With qSize Estimation model, you can calibrate:
(1) TCP for to each complexity level of Test Setup
(2) TCP for to each complexity level of Test Data
(3) Test Velocity
(4) Effort distribution
(5) Weights of test case types
• Process can be done with the help of tools
Tool Demo
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17. Conclusion
• qSize Analysis is an agile approach to estimating
size and effort of test cycle
– Estimate Size in TCP
– Estimate Effort using Test Velocity or Regression
– An Excel toolkit to simplify the approach
• Advantages and experiences learned
– Easy to implement
– Independent with the level of details of test cases
– Found useful
• Limitations and future improvements
– A new approach
– Need more empirical validations
17

18. Thank You

19. References
• [1] Y. Yang, Q. Li, M. Li, Q. Wang, An empirical analysis on distribution patterns of software
maintenance effort, International Conference on Software Maintenance, 2008, pp. 456-459
• [2] N. Patel, M. Govindrajan, S. Maharana, S. Ramdas, “Test Case Point Analysis”, Cognizant
Technology Solutions, White Paper, 2001
• [3] QASymphony: www.qasymphony.com