SANJAN BORA (LEAD QA ENGINEER) ENVISIONING DEFECT FREE SOFTWARE THROUGH INNOVATIVE PROCESS OPTIMIZATION PAVAN KULKARNI (LEAD QA ENGINEER) SANJAN BORA (LEAD QA ENGINEER) NANTHINI SUKUMARAN (SENIOR QA SPECIALIST) Software AG Bangalore Technologies Pvt. Ltd

ABSTRACT Delivering a Product Suite without defects is a myth, especially in a complex Middleware Customer environment where the platform can be customized to suit business requirements in numerous ways. However, with the adoption of innovative process methodologies and cutting-edge technologies available now, the vision of achieving ‘Defect Free’ applications and products is closer than ever before. OVERVIEW ON MIDDLEWARE & TESTING CHALLENGES FIX RELEASE PROCESS DEFECT TRIAGING PROCESS INTELLIGENT ROOT CAUSE ANALYSIS TEST ADEQUACY ENHANCEMENTS & CONCLUSION

MIDDLEWARE ARCHITECTURE

COMMON MIDDLEWARE TESTING CHALLENGES DIFFICULTY IN IDENTIFYING USE CASES RAPID CHANGES IN SYSTEMS TESTING COMBINES INTERNAL AS WELL AS THIRD PARTY PRODUCTS DIFFICULT TO SIMULATE TESTING ENVIRONMENTS IMPOSSIBLE TO USE BLACK BOX TECHNIQUES

Requirement Traceability ROADMAP TO DEFECT FREE SOFTWARE(?) Requirement Traceability Fault based models Reviews Test Adequacy

RECURRING DEFECTS IN CUSTOMER SITE IS A BIG INCONVENIENCE CUSTOMER SPECIFIC CHALLENGES CUSTOMERS A DEV TEAM-A RECURRING DEFECTS IN CUSTOMER SITE IS A BIG INCONVENIENCE FIX A DEV TEAM-B B FIX B A SAME DEFECT REPORTED AGAINST DIFFERENT VERSIONS FOR DIFFERENT CUSTOMERS CUSTOMER-A USING VERSION 1 CUSTOMER-B USING VERSION 2 CUSTOMER-C USING VERSION 3

SIMPLIFIED LIFE-CYCLE OF RELEASED FIXES PRODUCT LEVEL TESTING IS DONE HERE Entry Level Repositories INTEGRATION TESTING IS DONE HERE FIX AVAILABLE TO CUSTOMERS TESTING Repositories CUSTOMERS GA Repositories

CONTINUOUS CUSTOMER DEFECT TRIAGING Automated Triaging of Customer Defect FIX Integration Matrix Customer Defects README Integration Issues Intelligent Review of Triaged Defects Intelligent Test Case Comparator Matched Test cases Test Case Addition to the Automation Suite v1 v2 TEST CASES v3 Automate

CONTINUOUS TRIAGING IMPLEMENTATION 3 ReadMe Validator 1 Releases Fixes 4 Defect Extractor Automatic Tests JQL JSON 5 Integration Filter Dev Team 2 Request Tests 6 Intelligent Test case Comparator Refactor Rebuild 7 Automate CNL 8 Enhance Test Suite

Input Parsing Tokenizing RCA Feature Vector Preprocessing INTELLIGENT ROOT CAUSE ANALYSIS Input Parsing Tokenizing NEURAL NETWORKS RCA Feature Vector Preprocessing

TEST DESIGN PHASE ENHANCE TEST ADEQUACY TEST CHECKLIST TEST ENGINEER TEST CASES

INCREASING TREND IN REGRESSION TEST COUNT DECREASING TREND IN CUSTOMER DEFECTS

Automatic generation of test cases from defect details using NLP FUTURE ENHANCEMENTS Build a framework to analyse various probable root causes using Intelligent Root Cause Analysis technique. Automatic generation of test cases from defect details using NLP

References & Appendix www.degdigital.com   azure.microsoft.com www.bobemiliani.com en.wikipedia.org

Author Biography Pavan Kulkarni is a Lead QA Engineer in the Suite Integration team at Software AG. He has a total experience of 11 years and has worked in multiple domains like Telecom, Networking and now Middleware. Having been exposed to different testing methodologies in his career, he is passionate about optimizing and improving Automation and QA processes in the organization. Sanjan Bora is working as a Lead QA Engineer in Software AG having more than 13 years of total experience. He has worked on financial domain in the early period of his career and is currently into middleware testing where he contributed widely in different areas like automation, platform testing, SOA testing, fix release testing (to name a few).   Nanthini Sukumaran is a Senior QA Specialist in Software AG, with 9 years of experience in multiple domains. Being an automation specialist, she has worked on organization level unified frameworks for mobile as well as web automation. She was also instrumental in coming up new utilities and process changes resulting in more efficient QA processes. Her current interests include Machine Learning and Data science.

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