1. Wrapper-Based Evolution of Legacy Information System Philippe Thiran et al Fcculties University Notre-Dame de la Paix

2. Outline Why Data Wrappers? Building R/W Data Wrappers R/W Wrapper Architecture Generating Data Wrapper

3. Why Data Wrappers? Architectural shifts: from centralized to distributed and cooperative paradigm Data consistency in legacy architecture  Explicit constraints: guaranteed legacy system  Implicit constraints: data consistency is guaranteed by client application code  Example: PR field of record type ORDER refer a definite PRODUCT record Implicit constraints: to create or modify an ORDER, the referred PRODUCT should be first checked ORDER … PR … Product …

4. Why Data Wrappers? Plug a new application component into such a legacy architecture How to validate the implicit data property? Forward Wrappers:  Translate data and queries from the legacy data model  Take charge of the validation logic

5. Why Data Wrappers? Reuse a legacy component in a modern system Semantic mismatch: many important constraints and structures are ignored by data management system Backward Wrappers:  Query and update the new data  Data integrity is ensured by both the new and legacy app

6. What is a Data Wrapper? Component inserted between the legacy database and the application component to  Extend the lifetime of existing system  Address the heterogeneity by providing a standard and common interface  Allows to transparently incorporate new capabilities  Provides a smooth path to a step-by-step modernization of a complex legacy system Interface of a Data Wrapper  A wrapper schema  A common query language

7. Outline Why Data Wrappers? Building R/W Data Wrappers R/W Wrapper Architecture Generating Data Wrapper

8. Bridge the Semantic Gap Data Wrapper: a new application component that query and update the contents of a legacy database  Physical schema: explicit structures and constraints  Logical schema: explicit and implicit structures, accessed by the wrapper  By accessing the logical schema, data wrappers address the implicit constraints Reject the updates that violate the implicit constraints

9. Building R/W Wrapper Wrapper Schema Definition  Recover explicit constraints  Enriched with implicit constraints by reverse engineering techniques Program analysis Data analysis

10. Building R/W Wrapper Mapping definition  Transform structures  Transform constraints Example of update statement

11. Outline Why Data Wrappers? Building R/W Data Wrappers R/W Wrapper Architecture Generating Data Wrapper

12. R/W Wrapper Architecture Query/update analysis Error reporting Query/update and data translation Implicit constraint control Security Concurrency and transaction management

13. Specification of a Wrapper GER: a wide spectrum entity-relationship model Generate sub-models  Retain necessary parts in the sub-model  Rename the constructs  Assemble the valid parts Advantage:  All inter-model transformations equal to intra-model process  A limit set of primitive operators is sufficient to model most database engineering processes Enriched Model:  Encompass the physical, logical and conceptual models  Define a set of constructs comprising the structures and constraints

14. Model and Schema Specification Constructs: entity types, attribute, relationship types Built-in Constraints

15. Transformational Mapping Spec Transform a schema from one model to another, requiring specific operators  Inverse transformation T2(T1(C))=C  Transformation sequence S1-to-S2=(T1 T2... Tn): S2=T2(T1(S1)) S2-to-S1=(Tn -1 T2 -1 T1 -1 ): S1=S2-to-S1(S2)  Transformation categories T+: augment the semantics of the schema T=: Preserve the semantics of the schema T-: Reduce the semantics of the schema  Implicit constraints and schema Interpretation

16. Outline Why Data Wrappers? Building R/W Data Wrappers R/W Wrapper Architecture Generating Data Wrapper

17. Generating Wrapper Database reverse engineering  Yield all the necessary information to specify and develop a wrapper Semi-hardcoded wrapper  A model layer and a database layer Schema transformation-based wrapper generation  T+ is used to specify the implicit constraint assertions instead of T= Operational CASE support  Schema processing, mapping processing, and wrapper generation

18. Database Reverse Engineering Results:  Wrapper schema  Schema transformation sequence Process  Physical extraction  Logical extraction  Wrapper schema derivation  Mapping definition

19. Wrapper Generation

20. The results from DBRE:  Legacy physical schema  Legacy logical schema  Wrapper schema LS-to-PS mapping is formally defined, used to code the implicit constraint control component Structural part of WS-to-LS is used to code the query/update translator Instance part of ls-to-ws define the data translator

21. Reference Thiran, P. et al, Wrapper-Based Evoluation of Legacy Information System, ACM Tran Software Engineering and Methodology Vol.15 No.4, October 2006 Brodie, M. et al. 1995. Migrating Legacy Systems, Morgan Kaufmann Haninaut, J. et al, 2005, Transformation-Based Database Engineering, IDEA Group

22. Thanks Questions?