short-paper

Automatic generation of IFTTT mashup infrastructures

Authors:

Wei-Peng ChenAuthors Info & Claims

ASE '20: Proceedings of the 35th IEEE/ACM International Conference on Automated Software Engineering

Pages 1179 - 1183

https://doi.org/10.1145/3324884.3421837

Published: 27 January 2021 Publication History

Abstract

In recent years, IF-This-Then-That (IFTTT) services are becoming more and more popular. Many platforms such as Zapier, IFTTT.com, and Workato provide such services, which allow users to create workflows with "triggers" and "actions" by using Web Application Programming Interfaces (APIs). However, the number of IFTTT recipes in the above platforms increases much slower than the growth of Web APIs. This is because human efforts are still largely required to build and deploy IFTTT recipes in the above platforms. To address this problem, in this paper, we present an automation tool to automatically generate the IFTTT mashup infrastructure. The proposed tool provides 5 REST APIs, which can automatically generate triggers, rules, and actions in AWS, and create a workflow XML to describe an IFTTT mashup by connecting the triggers, rules, and actions. This workflow XML is automatically sent to Fujitsu RunMyProcess (RMP) to set up and execute IFTTT mashup. The proposed tool, together with its associated method and procedure, enables an end-to-end solution for automatically creating, deploying, and executing IFTTT mashups in a few seconds, which can greatly reduce the development cycle and cost for new IFTTT mashups.

References

[1]

Mehdi Bahrami, Junhee Park, Lei Liu, and Wei-Peng Chen. 2018. Api learning: Applying machine learning to manage the rise of API economy. In Companion Proceedings of The Web Conference 2018. 151--154.

Digital Library

[2]

Iulia Bastys, Musard Balliu, and Andrei Sabelfeld. 2018. If this then what? Controlling flows in IoT apps. In Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications Security. 1102--1119.

Digital Library

[3]

Buqing Cao, Jianxun Liu, Mingdong Tang, Zibin Zheng, and Guangrong Wang. 2013. Mashup service recommendation based on user interest and social network. In 2013 IEEE 20th International Conference on Web Services. IEEE, 99--106.

Digital Library

[4]

Wei Gao, Liang Chen, Jian Wu, and Honghao Gao. 2015. Manifold-learning based api recommendation for mashup creation. In 2015 IEEE International Conference on Web Services. IEEE, 432--439.

Digital Library

[5]

Ting-Hao Kenneth Huang, Amos Azaria, and Jeffrey P Bigham. 2016. Instructablecrowd: Creating if-then rules via conversations with the crowd. In Proceedings of the 2016 CHI Conference Extended Abstracts on Human Factors in Computing Systems. 1555--1562.

Digital Library

[6]

IFTTT.com. accessed May 28, 2020. https://ifttt.com/

[7]

Chune Li, Richong Zhang, Jinpeng Huai, and Hailong Sun. 2014. A novel approach for API recommendation in mashup development. In 2014 IEEE International Conference on Web Services. IEEE, 289--296.

[8]

Michele Melchiori. 2011. Hybrid techniques for Web APIs recommendation. In Proceedings of the 1st International Workshop on Linked Web Data Management (LWDM 2011). Uppsala, Sweden.

Digital Library

[9]

Steven Ovadia. 2014. Automate the internet with "if this then that"(IFTTT). Behavioral & Social Sciences Librarian 33, 4 (2014), 208--211.

[10]

Charlie Pinder, Jo Vermeulen, Adhi Wicaksono, Russell Beale, and Robert J Hendley. 2016. If this, then habit: exploring context-aware implementation intentions on smartphones. In Proceedings of the 18th International Conference on Human-Computer Interaction with Mobile Devices and Services Adjunct. 690--697.

Digital Library

[11]

ProgrammableWeb. accessed May 28, 2020. https://www.programmableweb.com/

[12]

Chris Quirk, Raymond Mooney, and Michel Galley. 2015. Language to code: Learning semantic parsers for if-this-then-that recipes. In Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), Vol. 1. 878--888.

[13]

Leonard Richardson and Sam Ruby. 2008. RESTful web services. " O'Reilly Media, Inc.".

[14]

Fujitsu RunMyProcess. accessed May 28, 2020. https://www.runmyprocess.com/

[15]

Amazon Web Services (AWS) Cloud Computing Services. accessed May 28, 2020. https://aws.amazon.com/

[16]

OpenAPI Specification. accessed May 28, 2020. https://swagger.io/specification/

[17]

StackStorm. accessed May 28, 2020. https://docs.stackstorm.com/rules.html#critera-comparisons

[18]

Romina Torres, Boris Tapia, et al. 2011. Improving web api discovery by leveraging social information. In 2011 IEEE International Conference on Web Services. IEEE, 744--745.

Digital Library

[19]

Blase Ur, Melwyn Pak Yong Ho, Stephen Brawner, Jiyun Lee, Sarah Mennicken, Noah Picard, Diane Schulze, and Michael L Littman. 2016. Trigger-action programming in the wild: An analysis of 200,000 ifttt recipes. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems. 3227--3231.

Digital Library

[20]

Workato. accessed May 28, 2020. https://www.workato.com/

[21]

Qinghan Xue, Lei Liu, Weipeng Chen, and Mooi Choo Chuah. 2017. Automatic generation and recommendation for API mashups. In 2017 16th IEEE International Conference on Machine Learning and Applications (ICMLA). IEEE, 119--124.

[22]

Yilong Yang, Peng Liu, Lianchao Ding, Bingqing Shen, and Weiru Wang. 2018. ServeNet: A Deep Neural Network for Web Service Classification. arXiv preprint arXiv:1806.05437 (2018).

[23]

Zapier. accessed May 28, 2020. https://zapier.com/

Cited By

Bran ENadoleanu GPopovici D(2022)Towards an Accessible Platform for Multimodal Extended Reality Smart EnvironmentsInformation10.3390/info1309043913:9(439)Online publication date: 18-Sep-2022
https://doi.org/10.3390/info13090439
Yusuf IJiang LLo DRastogi ATufano RBavota GArnaoudova VHaiduc S(2022)Accurate generation of trigger-action programs with domain-adapted sequence-to-sequence learningProceedings of the 30th IEEE/ACM International Conference on Program Comprehension10.1145/3524610.3527922(99-110)Online publication date: 16-May-2022
https://dl.acm.org/doi/10.1145/3524610.3527922
Pham QVo TTran P(2021)On the Implementation of a Low-Cost Mind-Voice-and-Gesture-Controlled Humanoid Robotic Arm Using Leap Motion and Neurosky SensorJournal of Electrical Engineering & Technology10.1007/s42835-021-00903-517:1(665-683)Online publication date: 13-Sep-2021
https://doi.org/10.1007/s42835-021-00903-5

Index Terms

Automatic generation of IFTTT mashup infrastructures
1. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing
2. Information systems
  1. Information retrieval
  2. World Wide Web
    1. Web applications

Recommendations

An empirical characterization of IFTTT: ecosystem, usage, and performance
IMC '17: Proceedings of the 2017 Internet Measurement Conference

IFTTT is a popular trigger-action programming platform whose applets can automate more than 400 services of IoT devices and web applications. We conduct an empirical study of IFTTT using a combined approach of analyzing data collected for 6 months and ...
Evolution of the mashup ecosystem by copying
Mashups '09/'10: Proceedings of the 3rd and 4th International Workshop on Web APIs and Services Mashups

Previous work has explored the structure of the mashup ecosystem, which can be modeled as a network of mashups and APIs. However, it did not offer an explanation for its growth. In this paper, we seek an answer to the question how mashup developers ...
On Simplifying Mobile Mashup Application Development
COMPSAC '13: Proceedings of the 2013 IEEE 37th Annual Computer Software and Applications Conference

In this paper, we propose a novel integrated API service system as well as a Web API script to enable mobile mashup application developers to invoke Web APIs in a consistent way, and provide a consistent format for the responses of Web APIs, thereby ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Conferences

ASE '20: Proceedings of the 35th IEEE/ACM International Conference on Automated Software Engineering

December 2020

1449 pages

ISBN:9781450367684

DOI:10.1145/3324884

General Chair:
John Grundy,
Program Chairs:
Claire Le Goues,
David Lo

Copyright © 2020 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

In-Cooperation

IEEE CS

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 27 January 2021

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Short-paper

Conference

ASE '20

Sponsor:

ASE '20: 35th IEEE/ACM International Conference on Automated Software Engineering

December 21 - 25, 2020

Virtual Event, Australia

Acceptance Rates

Overall Acceptance Rate 82 of 337 submissions, 24%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

3
Total Citations
View Citations
96
Total Downloads

Downloads (Last 12 months)19
Downloads (Last 6 weeks)3

Reflects downloads up to 16 Nov 2024

Other Metrics

View Author Metrics

Citations

Cited By

Bran ENadoleanu GPopovici D(2022)Towards an Accessible Platform for Multimodal Extended Reality Smart EnvironmentsInformation10.3390/info1309043913:9(439)Online publication date: 18-Sep-2022
https://doi.org/10.3390/info13090439
Yusuf IJiang LLo DRastogi ATufano RBavota GArnaoudova VHaiduc S(2022)Accurate generation of trigger-action programs with domain-adapted sequence-to-sequence learningProceedings of the 30th IEEE/ACM International Conference on Program Comprehension10.1145/3524610.3527922(99-110)Online publication date: 16-May-2022
https://dl.acm.org/doi/10.1145/3524610.3527922
Pham QVo TTran P(2021)On the Implementation of a Low-Cost Mind-Voice-and-Gesture-Controlled Humanoid Robotic Arm Using Leap Motion and Neurosky SensorJournal of Electrical Engineering & Technology10.1007/s42835-021-00903-517:1(665-683)Online publication date: 13-Sep-2021
https://doi.org/10.1007/s42835-021-00903-5

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Table of Contents