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Applying QPM Techniques for effective Test Management of ERP Systems

Applying QPM Techniques for effective Test Management of ERP Systems. Balamurali L Senior SQA Manager balamurali.l@nestgroup.net Diana Ambrose Senior Lead SQA diana.ambrose@nestgroup.net Arun Kumar V Senior Engineer QA arunkumar.v@nestgroup.net Geethu K Nair Engineer QA

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Applying QPM Techniques for effective Test Management of ERP Systems

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  1. Applying QPM Techniques for effective Test Management of ERP Systems Balamurali L Senior SQA Manager balamurali.l@nestgroup.net Diana Ambrose Senior Lead SQA diana.ambrose@nestgroup.net Arun Kumar V Senior Engineer QA arunkumar.v@nestgroup.net Geethu K Nair Engineer QA geethu.nair@nestgroup.net

  2. Software Systems – A Part of Daily Life Banking applications Cars and other vehicles Home appliances Software is now omnipresent Communicati-on Media Educational applications

  3. Role of Testing • Reduction of errors • Increasing confidence of end users • Ensuring safe operations • Contributes to quality • Reduces cost of defect fixing

  4. Testing: Perspective shift… • Establish confidence that a program does what it is supposed to do (Hetzel, 1973)

  5. Testing: Perspective shift… • The process of executing a program or system with the intent of finding errors (Myers, 1979)

  6. Testing: Perspective shift… • Verifying that a system satisfies its specified requirements and identifying the differences between expected and actual results

  7. The Planned Requirement Design Code Testing The Actual Requirement Design Code Testing The Lacuna

  8. Where we stand now… You can define, what you understand. You can measure, what you can define You can manage, what you can measure

  9. bug prediction and tracking

  10. Introduction • Uses baseline data of the organization and size of the current project • Predicts the expected number of bugs and the testing schedule for the current project • Cumulative bug trend curve resembles the curve of a first order response system • The actual cumulative bug trend is tracked against the estimated • Any notable deviation from the bug prediction curve, analysis will be triggered and corrective actions taken accordingly.

  11. Cumulative Bug Trend Curve • A curve with: • The days of testing marked on X-Axis • The cumulative number of bugs caught on Y-Axis • The slope of the curve gives the rate of bug capture

  12. Process In Testing - Monitoring No. Testing Days Schedule • Monitoring • Bug Prediction Curve • Weekly Status Report • % Schedule Completed • Resource Utilization ODB Defect Density Expected Defects & Schedule Project Team Size Defect Prevention measures

  13. Cumulative number of bugs Number of days Bug Prediction Curve Helps in tracking the test execution

  14. Bug Prediction Curve

  15. Possible Outcomes • The actual curve - within expected trend • The actual curve - outside expected trend • The number of bugs in the initial quarters is much less than estimated • The number of bugs in the initial quarters is much more than estimated

  16. The Scenario Diagram Situations Bugs in initial stage : Less than what is estimated Bugs in initial stage : More than what is estimated Unstable Product Stable Product Inadequate Testing

  17. Inadequate Testing

  18. Unstable Product

  19. Challenges in ERP Testing • Wide range of stakeholders that use the system • Impact of changes across various modules and higher risk of issues to be found at integration • Inherent slippages that is accumulated over various phases of the development lifecycle • Tracking and Managing multiple test iterations in parallel • High pressure to ensure delivery dates as well as the quality of delivery

  20. In the ERP context • Bug trend curve can be calculated for different iterations • Specification limits can be defined for each iterations • Actual bug trend curve can be plotted and monitored for each iterations

  21. Bug Trend Curve for multiple iterations

  22. Test Status Indicator

  23. Test Status Indicator • Root mean square of the variation between the estimated and actual bug trend curve • The variation between the planned and actual value of the bugs can be calculated on a daily basis. • The overall TSI values of the total projects in an organization can be plotted in a control chart for monitoring. • The specification limits can be defined and from the control chart, the points which fall outside the limits can be analyzed by the top management.

  24. SPC for TSI

  25. SPC for TSI in different iterations

  26. Advantages

  27. Case Study • Reduction in % effort for testing • Implementation of Bug Prediction and Tracking method ensures quantitative monitoring and control • Critical phases tracked in an efficiently and effectively

  28. Questions

  29. Thank you

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