The project is about testing of various automated web service composition algorithms and the corresponding web serviece challenge generation problems. Its datasets were used in serveral publications. We are extending this project with contraints and effects from the recent research, a working service respository, and making the generator a service itself.
Originally, the project came as a fruit from multiple organization solving web service composition challenges (WSC) implementing planning graph web services composition algorithms for comparative studies. That included studies and comparison of the performance of existing/contributed algorithms with planning graph and served as an experimental reference implementatio framework to improve planning graph algorithms.
- Clone and import it to
Eclipseand useExisting Projects into Workspaceand then configure the build path and add required jars to the class path.de.vs.unikassel.genrator.gui.GeneratorGUIis the Java class that instantiates the GUI forWSC-Gen.
- Active Branches
- [
temp] -- this branch currently provides a manual hardcoded extension to theWSC-Generatorin terms of extending the SLA's to include web service contraints and their effects for the recent work of Touraj Laleh. - [
Datasets] -- this branch extends theWSC-Genby providing updates to bring it up to recent JDK version, GUI modifications (not significant), additional toggle for the web services to be Context-Aware and related classes for a GIPSY Service by SOEN487 students.
- Issues
- Pull requests
- References to theses and papers of Ludeng and Touraj and co-authors
- References to the relevant GIPSY publications, at ICSOC and elsewhere
- Ongoing project work on the service repository
- Open an issue in the Issue Tracker
- Please send an to the current maintainers: 📧
gipsy AT encs.concordia.ca
The project was originally about implementing planning graph web services composition algorithm on the platform provided by Web Service Challenge 09. Also, the project aim to study and compare the performence of existing algorithms with planning graph and serve as an experiment basis to improve planning graph algorithm.