Adopting Six Sigma Approach in Predicting Functional Defects for System Testing
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This document discusses adopting a Six Sigma approach to predict functional defects in system testing using predictors from earlier phases. It defines the research focus as using Six Sigma to predict test defects via phases prior to testing. An overview explains that Six Sigma is a data-driven approach to reducing defects in any process. The findings sections explain applying the Six Sigma define, measure, analyze, design, and verify phases to software development. A proposed regression model and verification plan are presented to conclude.
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Adopting Six Sigma Approach in Predicting Functional Defects for System Testing
- 1. ADOPTING SIX SIGMA APPROACH IN PREDICTING FUNCTIONAL DEFECTS FOR SYSTEM TESTING Muhammad Dhiauddin bin Mohamed Suffian Faculty of Computer Science & Information System mdhiauddin2@live.utm.my AP Dr. Suhaimi Ibrahim Advanced Informatics School suhaimiibrahim@utm.my INSPIRING CREATIVE AND INNOVATIVE MINDS
- 2. CONTENT • • • • • • • • RESEARCH FOCUS & BACKGROUND OVERVIEW OF SIX SIGMA FINDINGS - DEFINE FINDINGS - MEASURE FINDINGS - ANALYZE FINDINGS - DESIGN FINDINGS - VERIFY CONCLUSION & RECOMMENDATION INSPIRING CREATIVE AND INNOVATIVE MINDS
- 3. RESEARCH FOCUS & BACKGROUND How to predict functional test defects in system testing phase using predictors in phases prior to testing phase via Six Sigma approach? INSPIRING CREATIVE AND INNOVATIVE MINDS
- 4. OVERVIEW OF SIX SIGMA A disciplined, data-driven approach and methodology for eliminating defects (driving toward six standard deviations between the mean and the nearest specification limit) in any process -- from manufacturing to transactional and from product to service (www.isixsigma.com) INSPIRING CREATIVE AND INNOVATIVE MINDS
- 5. FINDINGS - DEFINE Software Development Life Cycle INSPIRING CREATIVE AND INNOVATIVE MINDS
- 6. FINDINGS - DEFINE Y-X Tree
- 7. FINDINGS - MEASURE Measurement System Analysis INSPIRING CREATIVE AND INNOVATIVE MINDS
- 8. FINDINGS - ANALYZE Initial data set used Initial prediction model in a form of regression INSPIRING CREATIVE AND INNOVATIVE MINDS
- 9. FINDINGS - DESIGN Revised data set used Revised regression equation INSPIRING CREATIVE AND INNOVATIVE MINDS
- 10. FINDINGS - VERIFY PROPOSED MODEL Functional Defects (Y) = 4.00 - 0.204 Req. Error - 0.631 CUT Error + 1.90 KLOC 0.140 Req. Page + 0.125 Design Page - 0.169 Total Test Cases + 0.221 Effort Days Verify with new/fresh projects Control plan INSPIRING CREATIVE AND INNOVATIVE MINDS
- 12. THANK YOU