Discovery and reuse of composition knowledge for assisted mashup development

Florian Daniel, Carlos Rodríguez, Soudip Roy Chowdhury, Hamid R Motahari Nezhad, Fabio Casati

Результат исследований: Материалы для книги/типы отчетовМатериалы для конференции

12 Цитирования (Scopus)

Выдержка

Despite the emergence of mashup tools like Yahoo! Pipes or JackBe Presto Wires, developing 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 the mashup process and to turn it into an interactive co-creation process, in which one part of the solution comes from the developer and the other part from reusable composition knowledge that has proven successful in the past. We harvest composition knowledge from a repository of existing mashup models by mining a set of reusable composition patterns, whichwe then use to interactively provide composition recommendations to developers while they model their own mashup. Upon acceptance of a recommendation, the purposeful design of the respective pattern types allows us to automatically weave the chosen pattern into a partial mashup model, in practice performing a set of modeling actions on behalf of the developer. The experimental evaluation of our prototype implementation demonstrates that it is indeed possible to harvest meaningful, reusable knowledge from existing mashups, and that even complex recommendations can be efficiently queried and weaved also inside the client browser. Copyright is held by the author/owner(s).

Язык оригиналаАнглийский
Название основной публикацииWWW'12 - Proceedings of the 21st Annual Conference on World Wide Web Companion
Страницы493-494
Число страниц2
DOI
СостояниеОпубликовано - 2012
Опубликовано для внешнего пользованияДа
Событие21st Annual Conference on World Wide Web, WWW'12 - Lyon, Франция
Продолжительность: 16 апр 201220 апр 2012

Конференция

Конференция21st Annual Conference on World Wide Web, WWW'12
СтранаФранция
ГородLyon
Период16.4.1220.4.12

Отпечаток

Chemical analysis
Application programming interfaces (API)
Interfaces (computer)
Pipe
Wire

ASJC Scopus subject areas

  • Computer Networks and Communications

Цитировать

Daniel, F., Rodríguez, C., Chowdhury, S. R., Nezhad, H. R. M., & Casati, F. (2012). Discovery and reuse of composition knowledge for assisted mashup development. В WWW'12 - Proceedings of the 21st Annual Conference on World Wide Web Companion (стр. 493-494) https://doi.org/10.1145/2187980.2188093

Discovery and reuse of composition knowledge for assisted mashup development. / Daniel, Florian; Rodríguez, Carlos; Chowdhury, Soudip Roy; Nezhad, Hamid R Motahari; Casati, Fabio.

WWW'12 - Proceedings of the 21st Annual Conference on World Wide Web Companion. 2012. стр. 493-494.

Результат исследований: Материалы для книги/типы отчетовМатериалы для конференции

Daniel, F, Rodríguez, C, Chowdhury, SR, Nezhad, HRM & Casati, F 2012, Discovery and reuse of composition knowledge for assisted mashup development. в WWW'12 - Proceedings of the 21st Annual Conference on World Wide Web Companion. стр. 493-494, 21st Annual Conference on World Wide Web, WWW'12, Lyon, Франция, 16.4.12. https://doi.org/10.1145/2187980.2188093
Daniel F, Rodríguez C, Chowdhury SR, Nezhad HRM, Casati F. Discovery and reuse of composition knowledge for assisted mashup development. В WWW'12 - Proceedings of the 21st Annual Conference on World Wide Web Companion. 2012. стр. 493-494 https://doi.org/10.1145/2187980.2188093
Daniel, Florian ; Rodríguez, Carlos ; Chowdhury, Soudip Roy ; Nezhad, Hamid R Motahari ; Casati, Fabio. / Discovery and reuse of composition knowledge for assisted mashup development. WWW'12 - Proceedings of the 21st Annual Conference on World Wide Web Companion. 2012. стр. 493-494
@inproceedings{ab621acacab34113a527e7d70729fd68,
title = "Discovery and reuse of composition knowledge for assisted mashup development",
abstract = "Despite the emergence of mashup tools like Yahoo! Pipes or JackBe Presto Wires, developing 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 the mashup process and to turn it into an interactive co-creation process, in which one part of the solution comes from the developer and the other part from reusable composition knowledge that has proven successful in the past. We harvest composition knowledge from a repository of existing mashup models by mining a set of reusable composition patterns, whichwe then use to interactively provide composition recommendations to developers while they model their own mashup. Upon acceptance of a recommendation, the purposeful design of the respective pattern types allows us to automatically weave the chosen pattern into a partial mashup model, in practice performing a set of modeling actions on behalf of the developer. The experimental evaluation of our prototype implementation demonstrates that it is indeed possible to harvest meaningful, reusable knowledge from existing mashups, and that even complex recommendations can be efficiently queried and weaved also inside the client browser. Copyright is held by the author/owner(s).",
keywords = "Assisted mashup development, Composition patterns, End user development, Pattern recommendation, Weaving",
author = "Florian Daniel and Carlos Rodr{\'i}guez and Chowdhury, {Soudip Roy} and Nezhad, {Hamid R Motahari} and Fabio Casati",
year = "2012",
doi = "10.1145/2187980.2188093",
language = "English",
isbn = "9781450312301",
pages = "493--494",
booktitle = "WWW'12 - Proceedings of the 21st Annual Conference on World Wide Web Companion",

}

TY - GEN

T1 - Discovery and reuse of composition knowledge for assisted mashup development

AU - Daniel, Florian

AU - Rodríguez, Carlos

AU - Chowdhury, Soudip Roy

AU - Nezhad, Hamid R Motahari

AU - Casati, Fabio

PY - 2012

Y1 - 2012

N2 - Despite the emergence of mashup tools like Yahoo! Pipes or JackBe Presto Wires, developing 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 the mashup process and to turn it into an interactive co-creation process, in which one part of the solution comes from the developer and the other part from reusable composition knowledge that has proven successful in the past. We harvest composition knowledge from a repository of existing mashup models by mining a set of reusable composition patterns, whichwe then use to interactively provide composition recommendations to developers while they model their own mashup. Upon acceptance of a recommendation, the purposeful design of the respective pattern types allows us to automatically weave the chosen pattern into a partial mashup model, in practice performing a set of modeling actions on behalf of the developer. The experimental evaluation of our prototype implementation demonstrates that it is indeed possible to harvest meaningful, reusable knowledge from existing mashups, and that even complex recommendations can be efficiently queried and weaved also inside the client browser. Copyright is held by the author/owner(s).

AB - Despite the emergence of mashup tools like Yahoo! Pipes or JackBe Presto Wires, developing 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 the mashup process and to turn it into an interactive co-creation process, in which one part of the solution comes from the developer and the other part from reusable composition knowledge that has proven successful in the past. We harvest composition knowledge from a repository of existing mashup models by mining a set of reusable composition patterns, whichwe then use to interactively provide composition recommendations to developers while they model their own mashup. Upon acceptance of a recommendation, the purposeful design of the respective pattern types allows us to automatically weave the chosen pattern into a partial mashup model, in practice performing a set of modeling actions on behalf of the developer. The experimental evaluation of our prototype implementation demonstrates that it is indeed possible to harvest meaningful, reusable knowledge from existing mashups, and that even complex recommendations can be efficiently queried and weaved also inside the client browser. Copyright is held by the author/owner(s).

KW - Assisted mashup development

KW - Composition patterns

KW - End user development

KW - Pattern recommendation

KW - Weaving

UR - http://www.scopus.com/inward/record.url?scp=84861041075&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84861041075&partnerID=8YFLogxK

U2 - 10.1145/2187980.2188093

DO - 10.1145/2187980.2188093

M3 - Conference contribution

AN - SCOPUS:84861041075

SN - 9781450312301

SP - 493

EP - 494

BT - WWW'12 - Proceedings of the 21st Annual Conference on World Wide Web Companion

ER -