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Science behind Staging
- 1. The Science Behind Staging How Graph Theory Helps the Development of Liferay’s Publication Tools Máté Thurzó, Staging Lead, Senior Software Engineer
- 2. Budapest
- 4. Pörkölt
- 6. 1. Advanced publication tool Content can be assembled and reviewed on a staging site and can be published to live
- 7. A staging publication process replicates data between sites and performs extra operations – such as validation 2. replication
- 10. Entity Staging is operating on a graph of entities, discovering and processing the relationships between them
- 11. wy si wy g beh avi or In order to ensure a smooth experience we might need to pull other contents too r ef er en ce val i d at i on Certain business rules needs to be validated and reported back
- 12. n o gr aph st or ed There is no information before the execution of the graph gr aph mai n t en an ce On edit approach vs processing every time X M L f or mat Performance considerations – especially on the memory side
- 13. gr aph n ot h omogen ous The graph vertices are not the same – graph operations not possible st at i c cal l i n g Pre-defined entry points combined with a static controlling setup
- 15. Science kicks in – Enter graph theory
- 20. Directed Direction is important to tell what comes after what – This is defined in the business logic Graph Duh! Acyclical In a cycle everything has a predecessor and a successor
- 21. Coffman- graham
- 26. It’s a graph!
- 27. × Discovering relationships, behavior, interests × Providing suggestions on products
- 28. × Probability distribution over graphs × Complex network modeling × Erdos-Rényi model
- 29. Pál erdos
- 30. × Finding insurance fraudulant activity × Risk assessement
- 31. × News site – content with links to other content × Panama papers
- 32. × Static code analysis – Codecheck, Liferay Source Formatter × Abstract Syntax Tree (AST) × Abstract Semantic Graph (ASG)
- 33. × Statistics gathering in a graph form and analysing the produced result
- 34. × Parkinson’s disease × Protein struture prediction × Cancer research
- 35. László babai university of chicago graph isomorphism can be solved in quasi polinomial time
- 36. Why graphs
- 37. Graphs are easyEasy to understand Whiteboard friendly Easy to work with Graph algorithms
- 45. Questions?
- 46. @matethurzo