[Vu Van Nguyen] Test Estimation in Practice

1. Test Estimation in Practice STC JULY 2014 VU NGUYEN Faculty of Information Technology University of Science, VNU-HCMC

2. Agenda • Background and Motivation • qEstimation Process – Test Size Estimation – Test Effort Estimation • Conclusion 2

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

4. Motivation • Testing accounts for up to 50% of project effort [1] • Current problems – estimates done for the whole project rather than testing specific – lack of reliable methods designed for estimating software testing • Our aim – Introducing qEstimation for estimating size and effort of testing projects 4

6. Test Case qEstimation Process 6 Test Case Count TCPs of all Test Cases Estimate Testing Effort Parameters Counted Size Estimated Effort [Test Cycle i] Test Cycle Size Actual Effort Effort by Activity …. …. …. …. Test cycle i …. …. …. …. …. …. …. Historical Data of this Project Update Historical Data Calibrate Estimation Model Estimate size and effort of different test cycles of a same project:

7. qEstimation Principles • Size measures complexity of each test cycle • 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 • Model refinement (calibration) is key to estimating effort – based on previous cycles of the current project or similar projects 7

8. Count Size of Test Cycle • Size of a test cycle: total TCPs of all test cases to be executed in that test cycle • Steps: 8 Test Case Count Checkpoints Determine Set Up Complexity Determine Test Data Complexity Adjust based on Test Type (optional) Unadjusted TCPs TCPs

9. Count Size of Test Cycle - 2 • 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 9 One checkpoint is counted as one TCP

10. Count Size of Test Cycle - 3 • Test Setup or Precondition – Test setup specifies the condition to execute the test case • Include setup steps to prepare environment for testing – Four levels of Test Setup complexity • Each is assigned a number of TCPs 10 Number of TCP(*) Complexity Level Description 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

11. Count Size of Test Cycle - 4 • Test Data – Test Data is used to execute the test case • It can be generated at the test case execution time, sourced from previous tests, or generated by test scripts – Four levels of Test Data complexity • Each is assigned a number of TCPs Number of TCP (*) Complexity Level Description 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

12. Count Size of Test Cycle - 5 • 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 of the test case = Counted TCP x Weight(*) 12

14. 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 • Test Analysis and Design • Test Execution • Test Tracking and Reporting 14 Each of these activities may be performed multiple times

15. Estimate Effort of Test Cycle - 2 • Estimate Effort based on Test Velocity Effort(person-hour) = Size(TCP) / Test Velocity(TCP per person-hour) – Test Velocity is measured as TCP/person-hour • Test Velocity is dependent on project • It should be calculated based on data from completed test cycles of the same project. 15

16. Estimate Effort of Test Cycle - 3 • Estimate effort using Linear Regression Analysis – Find out the equation of effort and size using similar completed test cycles of a project 16 y = 0.0729x + 1.6408 0 10 20 30 40 50 60 70 80 90 100 0 100 200 300 400 500 600 700 800 900 1000 Effort(PM) Adjusted TCP Equation of Size and Effort The data analysis tool like Excel can be used to find out the equation

17. Calibrate qEstimation • Calibration: a process adjusting parameters for a model using historical data or experiences • With qEstimation, you can calibrate: (1) TCP assigned to each complexity level of Test Setup (2) TCP assigned 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 17

18. 18 Tool Demo

19. Conclusion • qEstimation is an agile approach to estimating tests – Estimate Size in TCP by measuring the complexity of test cases – Estimate Effort using Test Velocity or Regression – An Excel toolkit to simplify the approach • Advantages – Easy to implement – Reflecting real complexity of test cases – Independent with the level of details of test cases – Useful for estimating testing effort 19

20. 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 • [4] Vu Nguyen, Vu Pham, and Vu Lam. “qEstimation: a process for estimating size and effort of software testing.” Proceedings of the 2013 International Conference on Software and System Process. ACM, 2013