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Predictive Analytics in Software Testing
- 2. The common problem most of the companies today face sudden increase in costs, production delays and operational risks. Introduction Organizations which perform testing using its in-house testing environment and team. Organizations simply outsourcing its entire testing activities to preferred vendors.
- 3. Challenges with in-house Testing • Managing testing for multiple releases of different types of applications • Managing multiple testing tools and required infrastructure usage and productivity • Measuring Testing team Productivity • Identify Right Tester for particular task • Unable to identify issues which can lead to challenges in future • Unable to provide different stake-holders reports in preferred view • Measuring Test coverage and quality of work • Timely alerts and notifications
- 4. Challenges with Outsourced Testing • Identifying the right vendor who have the required competency to deliver the output as per expectations and vendor who is flexible enough to adapt to changes • Managing and communication with multiple testing vendors is a challenge • Difficulty in Identifying the root cause at a right time • KPI reports and SLA adherence • Measuring Test coverage and quality of work • Difficulty in identifying the root cause of an issue • Implementing quick changes is a challenge
- 5. Common Challenges and Expectations • Every stakeholder have different expectation in terms of KPI reports , test results, Audit reports, Test management reports, Other metrics, etc.. • There are no standard expectation on reports. Demand of reports might change based on that situation and Stakeholder requirements. • Not able to produce desired analytical reports and its time taking process to generate OnDemand Analytical reports • Is project going in right track ? • Who is the right tester for this assignment? • In my testing practice where exactly I am incurring more cost ? • With the current pace of the project will I be able to meet the deadline ? • Project got deviated ! What measure I should take to accomplish the project with in the set Deadline? • Not able to generate expected report because data is residing in different sources. • Many more challenges..…
- 6. Predictive Analytics in Software Testing Predictive Analytics is a data driven technology which can be leveraged to predict failure points in testing activities and determine the future. It has the power to help optimize project data and make proactive decisions. Predictive analytics helps in predicting the present and taking proactive measures for future. There are 3 major techniques which can be used in Predictive Analytics – • Predictive model • Descriptive model • Decision model Based on the KPI requirements or expectations of the clients applicable model can be applied and expected report can be generated. Predictive Analytical solution will helps answering many such questions which we might not derive from existing testing tool based reports • How will it affect my Testing project? • How do we do things better? • What is the best decision for a complex problem? Predictive analytics helps in reducing the testing costs and deriving to better ROI early in the testing life cycle.
- 7. Advantages of Predictive Analytics in Software Testing • Predictive Analytics helps in identifying right tester for particular task • Predictive Analytics helps in monitoring overall project status • Predictive Analytics helps in identifying issues impacting various areas of project • Predictive Analytics helps in proactively identifying the risks and mitigating the risks at the earliest stage • Predictive Analytics helps in identifying where is the delay and what is the issue • Predictive Analytics helps in monitoring tester and testing team productivity • Predictive Analytics helps in right vendor for the particular project • Predictive Analytics helps in Improve Planning, Quality and Delivery • Predictive Analytics helps in making right decisions at right time.
- 8. Predictive Analytics in Integrated Approach In a testing practice multiple testing activities performed and multiple testing tools are leveraged to fulfill the requirements and each testing tool works in silos and respective testing data and logs storing in silos. To optimize the cost, time and effort, it’s suggested to go with new techniques and technology and integrate predictive analytical tool into the integration framework.
- 9. Conclusion Predictive Analytics helps in increasing the efficiency and improves the effectiveness of the testing operations Predictive Analytics helps in Improve Planning, Quality and Delivery
- 10. Thank you for attending our webinar. - K.Pavan Kumar
Editor's Notes
- #4: Typically, testing companies follow a lengthy process for any testing project in an effort to reduce operational issues and costs. However, these companies still need to encounter many issues with every new project. Lets look at some of the challenges involved with in-house testing.
- #5: The development companies that outsources all the testing activities would look forward to focus more on core business while avoiding ever increasing costs associated with testing. However, these companies still face a lot of delays for deliverables and exceeding costs. Lets look at some of the challenges involved with outsourcing testing.