1. Effective Usage of Predictions modeling makes you Great!
Raja Balusamy, Senior Chief Engineer
Samsung R&D Institute India - Bangalore

2. Abstract
Predictive modeling is a latest process that helps test organization or software test team to predict the outcome of future results. Data can be collected from various sources like Google Analytics, Cloud and Previous Reports. There has been a shift in Software testing over the time towards prediction modeling to strengthen user space which helps to improve the business or service quality. Preventive actions and focus can be changed for Software testing based on predictions. This presentation outlines how we can predict the future results from various sources and explain about important parameters.

3. Why Predictive modeling?
Problem
Increase costs in SW Testing
Production Delays
Experience Operational risks
Customer Satisfaction on Quality
Advantages
Helps to making right decisions
Helps to improve the productivity
Helps to predict the Outcomes

4. What is Predictive modeling ?
Predictive modeling uses statistics to predict outcomes (Data Driven).
Current
Future
Past
Review Predictions
Reports / Records
Predict Results
Action

5. Predictions in Software Testing
How to Predict?
Data Sources
VOC
User Data
Past Records
A. SW Test Predictions
B. User Expectations
C. Action on VOCs
Productivity
Predictions in Software Testing
Test Plan
Defects
Most Used Features by Users
Most VOCs

6. A: SW Test Predictions Mobile Testing Defects Trend
New Model Total Defects Prediction: 1075
Average Defects Prediction
Defects Per New Feature: 90 (25%)
Defects Per Major/Minor Enhancement: 25 (10%)
Side Effect: 66.6% A B C D E
New Model
Mobile Models

7. B. Predictions: User Expectations from Google Analytics
Mobile Testing
Google Analytics is a web analytics service that tracks and reports website traffic.
Most widely used web analytics service on the Internet.
We can get details like:
No. of Users
Mostly used feature
Issues.
Time Spent, etc..
Important to know the Users pattern to plan better!

8. Highly important to know the feedback from actual Users!
C. Resolving VOCs
Mobile Testing
VOCs Sources :Google Analytics, Play Store or Market Team
Update our test strategy and plan based on Sources.
VOCs should be categorized like
VOCs which most number of users reported
(Pareto Rule)
Enhancements or Issues
Highly important to know the feedback from actual Users!

9. Productivity A. SW Test Predictions +
Productivity : B. User Expectations
C. Action on VOCs
Makes to
feel great!
Help us to improve:
Test Effectiveness, Test Satisfaction, Test Productivity and Test Coverage.

10. Mostly Used in? Limitations
History cannot always predict 100% future accurate.
The issue of unknown unknowns.
Self-defeat of an algorithm.

11. References & Appendix

12. Author Biography
Raja Balusamy works as a Senior Chief Engineer at Samsung R&D Institute India, Bangalore and have 13+ years of experience in Software Testing, Test Management and Leadership. He holds a Bachelor's Degree. He is a certified PMP Holder, ISTQB certified, Six-Sigma Green Belt certified and Black belt trained professional.
PMP® #

13. Thank You!!!