AspectJ Paradigm Model A Basis for Multi-Paradigm Design for AspectJ

1. GCSE 2001 AspectJ Paradigm ModelA Basis for Multi-Paradigm Design for AspectJ Valentino Vranić vranic@elf.stuba.sk Department of Computer Science and Engineering Faculty of Electrical Engineering and Information Technology Slovak University of Technology in Bratislava

2. Presentation Overview • Multi-paradigm design • Feature modeling • Multi-paradigm design with feature modeling • AspectJ paradigm model • Transformational analysis • An example: Text editing buffers • Conclusions

3. Multi-Paradigm Design (MPD) • MPD for C++ (J. O. Coplien) • Programming paradigms: • Large-scale paradigms • Small-scale paradigms • Scope, commonality, variability, and relationship (SCVR) analysis • Transformational analysis

4. Transformational Analysis in MPD Variability tables (from application domain SCVR analysis) Domain D1 (main commonality of D1) Parameters of Variation Meaning Domain Binding Default P1 Generalization of P1 (values P1 can take) (default value for P1) … Family table (from solution domain SCVR analysis) Commonality Variability Binding Instantiation Language Mechanism …

5. Feature Modeling • A conceptual modeling technique Feature diagrams • directed trees with edge decorations • root = concept,other nodes = features • common and variable features • variation points Other information • Semantic description • Rationale • Constraints • Default dependency rules • Binding mode • Instantiation

6. MPD with Feature Modeling • Feature models instead of tables and informal description • Both feature modeling and SCVR analysis are based on commonalities and variabilities • SCVR analysis and feature modeling: • scope  concept • commonality  common feature • variability  variable feature • relationship  feature diagrams hierarchy

7. MPDandMPD with Feature Modeling Parameters of Variation Meaning Domain Binding Default variation point semantic description, rationale alternative features binding mode default dependency rules Commonality Variability Binding Instantiation Language Mechanism common feature variable feature binding mode additional information concept Variability table Domain D1 (main commonality of D1 concept) Family table

8. AspectJ Paradigm Model

9. AspectJ Paradigm Model: Class Paradigm

10. AspectJ Paradigm Model: Aspect Paradigm

11. Transformational Analysis • Prerequisites: • Solution domain feature model • Application domain feature model • Matching of application domain feature model nodes with the solution domain feature model nodes • Points to the paradigms to be used for application domain structures • Two nodes match if they conceptually represent the same thing

12. Matching the Nodes 1. Select a node F from the application domain feature model 2. Try to match F’s children with the children of some node P that represents a paradigm in the solution domain feature model 3. If a match has been found for all of the F’s children, then F matches with P 4. A paradigm that represented by P should be used to implement feature F

13. The Process of Transformational Analysis • Find the matching for all of the nodes in the application domain feature model • Try to match the application domain nodes with the paradigms of “higher order” — the paradigms based on other paradigms (inheritance and overloading in AspectJ) • Translate the results of the transformational analysis into the code: • directly • through a specific design method pointed to by MPD

14. An Example: Text Editing Buffers • Represent a state of a file being edited • Employ different working set management schemes • Use different character sets • Load and save the contents into a file • Maintain a record of the number of lines and characters, cursor position, etc.

17. File read write name name status status contents contents

25. Working Set Management DC … whole file whole page LRU fixed

27. Feature diagrams alone do not fully determine the code skeleton • What other sources are there? • Variability dependency graphs • Other information in feature model

28. Variability Dependency Graph File Character Set Text Editing Buffer Debugging Code Working Set Management

29. class TextBuffer { public: yield(...) {...}; replace(...) {...}; loadFile(...) {...}; saveFile(...) {...}; private: int numLines, numChars, curPosition; . . . } class WholeFileTextBuffer extends TextBuffer { public: WholeFileTextBuffer(File f, CharacterSet c) {...}; yield(...) {...}; replace(...) {...}; . . . } . . .

30. class File { public: Status readFile(String name, TextBuffer buff) {...} Status writeFile(String name, TextBuffer buff) {...} . . . } class UnixFile extends File { . . . } . . . aspect DebuggingCode { . . . } aspect WorkingSetDebug extends DebuggingCode { . . . } aspect WholeFileDebug extends WorkingSetDebug { . . . } . . .

31. Conclusions • A new representation for the solution and application domain in MPD • Based on feature modeling • Involves a new transformational analysis • AspectJ paradigm model • Further research: • Noting of the transformational analysis results • Incorporating the MPD’s negative variability tables and variability dependency graphs • Relationship between the MPD and generative programming