Assisted mashup development: On the discovery and recommendation of mashup composition knowledge

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

Research output: Chapter in Book/Report/Conference proceedingChapter

4 Citations (Scopus)

Abstract

Over the past few years, mashup development has been made more accessible with tools such as Yahoo! Pipes that help in making the development task simpler through simplifying technologies. However, mashup development is still a difficult task that requires knowledge about the functionality of web APIs, parameter settings, data mappings, among other development efforts. In this work, we aim at assisting users in the mashup process by recommending development knowledge that comes in the form of reusable composition knowledge. This composition knowledge is harvested from a repository of existing mashup models by mining a set of composition patterns, which are then used for interactively providing composition recommendations while developing the mashup. When the user accepts a recommendation, it is automatically woven into the partial mashup model by applying modeling actions as if they were performed by the user. In order to demonstrate our approach we have implemented Baya, a Firefox plugin for Yahoo! Pipes that shows that it is indeed possible to harvest useful composition patterns from existing mashups, and that we are able to provide complex recommendations that can be automatically woven inside Yahoo! Pipes' web-based mashup editor.

Original languageEnglish
Title of host publicationWeb Services Foundations
PublisherSpringer New York
Pages683-708
Number of pages26
Volume9781461475187
ISBN (Electronic)9781461475187
ISBN (Print)1461475171, 9781461475170
DOIs
Publication statusPublished - 1 Oct 2014
Externally publishedYes

Fingerprint

Chemical analysis
Pipe
Application programming interfaces (API)

ASJC Scopus subject areas

  • Computer Science(all)

Cite this

Rodríguez, C., Chowdhury, S. R., Daniel, F., Nezhad, H. R. M., & Casati, F. (2014). Assisted mashup development: On the discovery and recommendation of mashup composition knowledge. In Web Services Foundations (Vol. 9781461475187, pp. 683-708). Springer New York. https://doi.org/10.1007/978-1-4614-7518-7_27

Assisted mashup development : On the discovery and recommendation of mashup composition knowledge. / Rodríguez, Carlos; Chowdhury, Soudip Roy; Daniel, Florian; Nezhad, Hamid R Motahari; Casati, Fabio.

Web Services Foundations. Vol. 9781461475187 Springer New York, 2014. p. 683-708.

Research output: Chapter in Book/Report/Conference proceedingChapter

Rodríguez, C, Chowdhury, SR, Daniel, F, Nezhad, HRM & Casati, F 2014, Assisted mashup development: On the discovery and recommendation of mashup composition knowledge. in Web Services Foundations. vol. 9781461475187, Springer New York, pp. 683-708. https://doi.org/10.1007/978-1-4614-7518-7_27
Rodríguez C, Chowdhury SR, Daniel F, Nezhad HRM, Casati F. Assisted mashup development: On the discovery and recommendation of mashup composition knowledge. In Web Services Foundations. Vol. 9781461475187. Springer New York. 2014. p. 683-708 https://doi.org/10.1007/978-1-4614-7518-7_27
Rodríguez, Carlos ; Chowdhury, Soudip Roy ; Daniel, Florian ; Nezhad, Hamid R Motahari ; Casati, Fabio. / Assisted mashup development : On the discovery and recommendation of mashup composition knowledge. Web Services Foundations. Vol. 9781461475187 Springer New York, 2014. pp. 683-708
@inbook{7d34d3d241484648a6c2c6738ee90c87,
title = "Assisted mashup development: On the discovery and recommendation of mashup composition knowledge",
abstract = "Over the past few years, mashup development has been made more accessible with tools such as Yahoo! Pipes that help in making the development task simpler through simplifying technologies. However, mashup development is still a difficult task that requires knowledge about the functionality of web APIs, parameter settings, data mappings, among other development efforts. In this work, we aim at assisting users in the mashup process by recommending development knowledge that comes in the form of reusable composition knowledge. This composition knowledge is harvested from a repository of existing mashup models by mining a set of composition patterns, which are then used for interactively providing composition recommendations while developing the mashup. When the user accepts a recommendation, it is automatically woven into the partial mashup model by applying modeling actions as if they were performed by the user. In order to demonstrate our approach we have implemented Baya, a Firefox plugin for Yahoo! Pipes that shows that it is indeed possible to harvest useful composition patterns from existing mashups, and that we are able to provide complex recommendations that can be automatically woven inside Yahoo! Pipes' web-based mashup editor.",
author = "Carlos Rodr{\'i}guez and Chowdhury, {Soudip Roy} and Florian Daniel and Nezhad, {Hamid R Motahari} and Fabio Casati",
year = "2014",
month = "10",
day = "1",
doi = "10.1007/978-1-4614-7518-7_27",
language = "English",
isbn = "1461475171",
volume = "9781461475187",
pages = "683--708",
booktitle = "Web Services Foundations",
publisher = "Springer New York",
address = "United States",

}

TY - CHAP

T1 - Assisted mashup development

T2 - On the discovery and recommendation of mashup composition knowledge

AU - Rodríguez, Carlos

AU - Chowdhury, Soudip Roy

AU - Daniel, Florian

AU - Nezhad, Hamid R Motahari

AU - Casati, Fabio

PY - 2014/10/1

Y1 - 2014/10/1

N2 - Over the past few years, mashup development has been made more accessible with tools such as Yahoo! Pipes that help in making the development task simpler through simplifying technologies. However, mashup development is still a difficult task that requires knowledge about the functionality of web APIs, parameter settings, data mappings, among other development efforts. In this work, we aim at assisting users in the mashup process by recommending development knowledge that comes in the form of reusable composition knowledge. This composition knowledge is harvested from a repository of existing mashup models by mining a set of composition patterns, which are then used for interactively providing composition recommendations while developing the mashup. When the user accepts a recommendation, it is automatically woven into the partial mashup model by applying modeling actions as if they were performed by the user. In order to demonstrate our approach we have implemented Baya, a Firefox plugin for Yahoo! Pipes that shows that it is indeed possible to harvest useful composition patterns from existing mashups, and that we are able to provide complex recommendations that can be automatically woven inside Yahoo! Pipes' web-based mashup editor.

AB - Over the past few years, mashup development has been made more accessible with tools such as Yahoo! Pipes that help in making the development task simpler through simplifying technologies. However, mashup development is still a difficult task that requires knowledge about the functionality of web APIs, parameter settings, data mappings, among other development efforts. In this work, we aim at assisting users in the mashup process by recommending development knowledge that comes in the form of reusable composition knowledge. This composition knowledge is harvested from a repository of existing mashup models by mining a set of composition patterns, which are then used for interactively providing composition recommendations while developing the mashup. When the user accepts a recommendation, it is automatically woven into the partial mashup model by applying modeling actions as if they were performed by the user. In order to demonstrate our approach we have implemented Baya, a Firefox plugin for Yahoo! Pipes that shows that it is indeed possible to harvest useful composition patterns from existing mashups, and that we are able to provide complex recommendations that can be automatically woven inside Yahoo! Pipes' web-based mashup editor.

UR - http://www.scopus.com/inward/record.url?scp=84906746581&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84906746581&partnerID=8YFLogxK

U2 - 10.1007/978-1-4614-7518-7_27

DO - 10.1007/978-1-4614-7518-7_27

M3 - Chapter

AN - SCOPUS:84906746581

SN - 1461475171

SN - 9781461475170

VL - 9781461475187

SP - 683

EP - 708

BT - Web Services Foundations

PB - Springer New York

ER -