Overcome a Frontier with Quality, ML and Agility
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Usually we hear a lot about “great success” however we learn a lot more from mistakes which help to gain experience and skills. In this talk I'm going to share challenges team faced with on a project which started with simple requirement to implement a replacement for an old core business system in a like-for-like fashion with new technologies. That led to explosion of different issues and challenges during implementation and eventually to stabilization and to a long awaited chance to go-live.
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Overcome a Frontier with Quality, ML and Agility
- 2. ● proud father ● SA in EPAM Systems ● Java is my primary programming language ● infected by AI disrupting power ● passionate about agile, clean code and devops
- 3. Agenda ● All we need is Quality ● Helpful ML ● Takeaways ● Q&A
- 4. What..? ● Team ● Sorry, no code ● Surprise..? ● Takeaways
- 5. Legacy ● Business critical 30+ years old application ● Based on IBM AS/400 and DB2 ● Hundreds of stores with customizations ● Most of requirements were reverse engineered from ~6M LoC
- 6. What’s New ● Main requirement is like-for-like UI/UX ● Custom UI Framework to render “Green Screen” in browser ● New Platform based on Java and Spring Framework ● MariaDB for storage ● Lots of talents, time, hard work
- 7. All we need is Quality
- 8. Gentleman’s Kit ● CI/CD ○ GitLab ○ Jenkins ○ SonarQube ○ Artifactory ○ Ansible ● Automated Testing ● Peer Code Review
- 9. S2S ● Designed to verify like-for-like requirement ● Executes testing scenarios in legacy and new apps one-by-one ● Compares screens ● Compares text reports Legacy Stories Definition New New Runner Legacy Runner Legacy Screen New Screen Artifactory Comparator Report Portal Screen 2 Screen Report
- 10. ● Designed for long-running and full-of-heavy-calculation logic jobs ● Compares data after scenario execution DB2DB
- 11. DB2DB Legacy Scenarios New ExecuteDump Dump Snapshot 0 Snapshot 0` ETL Execute Snapshot 0`` Dump Compare
- 12. ● Day ● Week ● Month ● Quarter ● Year X in a Life
- 13. fbinfer.com ● A static analyzer for Java, C, C++, and Objective-C ● Kills NPEs and many other issues
- 14. Mutation Testing ● State-of-the-art mutation testing tool ● Helps to assess automated tests quality
- 15. DB Validator ● Post ETL ● Data validation from JPA Enum fields perspective ● Data Referential Integrity validation ○ From JPA Mapping perspective ○ From domain model DDL perspective ● Data validation from domain model attributes perspective
- 16. Spider ● Single step Serenity ● Navigation-driven ● Exploratory New Report Portal Spider
- 17. Helpful ML
- 18. Bugs Clusterization ● ML Clustering ● JIRA issues export ● Improves assignment process
- 19. Regression Shrink ● ML Clustering ● Execution extract from Report Portal ● Improves tests deduplication process
- 20. SpAIder ● PoC ● Reinforcement Learning ● OpenAI Gym environment ● AI agent is based on Soft Actor-Critic Algorithm Mocked App Report Portal SpAIder AI Agent Spider Runner Gym Env
- 21. References ● PIT Mutation Testing ● FB Infer ● Soft Actor-Critic paper ● Affinity Propagation
- 22. Takeaways ● Don’t believe in “like-for-like“ ● There is no constraints of what is possible ● Think out-of-the-box ● Act as a team