Watch what I do: programming by demonstration
Watch what I do: programming by demonstration
Making mashups with marmite: towards end-user programming for the web
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Using assertions to help end-user programmers create dependable web macros
Proceedings of the 16th ACM SIGSOFT International Symposium on Foundations of software engineering
End-user programming in the wild: A field study of CoScripter scripts
VLHCC '08 Proceedings of the 2008 IEEE Symposium on Visual Languages and Human-Centric Computing
Proceedings of the VLDB Endowment
Semantic-Based Mashup of Composite Applications
IEEE Transactions on Services Computing
The state of the art in end-user software engineering
ACM Computing Surveys (CSUR)
How end-user development will save composition technologies from their continuing failures
IS-EUD'11 Proceedings of the Third international conference on End-user development
End-user requirements for wisdom-aware EUD
IS-EUD'11 Proceedings of the Third international conference on End-user development
Efficient, interactive recommendation of mashup composition knowledge
ICSOC'11 Proceedings of the 9th international conference on Service-Oriented Computing
Baya: assisted mashup development as a service
Proceedings of the 21st international conference companion on World Wide Web
An efficient and scalable ranking technique for mashups involving RSS data sources
Journal of Network and Computer Applications
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Despite the recent progresses in end-user development and particularly in mashup application development, developing even simple mashups is still non-trivial and requires intimate knowledge about the functionality of web APIs and services, their interfaces, parameter settings, data mappings, and so on. We aim to assist less skilled developers in composing own mashups by interactively recommending composition knowledge in the form of modeling patterns and fostering knowledge reuse. Our prototype system demonstrates our idea of interactive recommendation and automated pattern weaving, which involves recommending relevant composition patterns to the users during development, and once selected, applying automatically the changes as suggested in the selected pattern to the mashup model under development. The experimental evaluation of our prototype implementation demonstrates that even complex composition patterns can be efficiently stored, queried and weaved into the model under development in browser-based mashup tools.