Xatkit: A Multimodal Low-Code Chatbot Development Framework
Open accessAbstract
Chatbot (and voicebot) applications are increasingly adopted in various domains such as e-commerce or customer services as a direct communication channel between companies and end-users. Multiple frameworks have been developed to ease their definition and deployment. While these frameworks are efficient to design simple chatbot applications, they still require advanced technical knowledge to define complex interactions and are difficult to evolve along with the company needs (e.g. it is typically impossible to change the NL engine provider). In addition, the deployment of a chatbot application usually requires a deep understanding of the targeted platforms, especially back-end connections, increasing the development and maintenance costs. In this paper, we introduce the Xatkit framework. Xatkit tackles these issues by providing a set of Domain Specific Languages to define chatbots (and voicebots and bots in general) in a platform-independent way. Xatkit also comes with a runtime engine that automatically deploys the chatbot application and manages the defined conversation logic over the platforms of choice. Xatkit's modular architecture facilitates the separate evolution of any of its components. Xatkit is open source and fully available online.
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A number of current chatbot platforms are marketed under the promise of supporting chatbot design without need for coding skills.
“A number of current chatbot platforms are marketed under the promise of supporting chatbot design without need for coding skills [26].”
From Future directions for chatbot research: An interdisciplinary research agenda (2021) · cites this paper as [26]
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Cites
ELIZA — a computer program for the study of natural language communication between man and machine
Weizenbaum, J. (1983) · Communications of the ACM · doi:10.1145/357980.357991 · Cited by 2,765 · see citing works
Nardi, B. A., Whittaker, S., & Bradner, E. (2000) · ACM Conference on Computer Supported Cooperative Work (CSCW) · doi:10.1145/358916.358975 · Cited by 1,079 · see citing works
A New Chatbot for Customer Service on Social Media
Xu, A., Liu, Z., Guo, Y., Sinha, V. S., & Akkiraju, R. (2017) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3025453.3025496 · Cited by 589 · see citing works
Model-Driven Software Engineering in Practice
Brambilla, M., Cabot, J., & Wimmer, M. (2012) · Synthesis lectures on software engineering · doi:10.2200/s00441ed1v01y201208swe001 · Cited by 541 · see citing works
Self-citationThe DARPA Twitter Bot Challenge
Subrahmanian, V. S., Azaria, A., Durst, S., Kagan, V., Galstyan, A., Lerman, K., Zhu, L., Ferrara, E., Flammini, A., & Menczer, F. (2016) · Computer · doi:10.1109/mc.2016.183 · Cited by 480 · see citing works
Instant messaging in teen life
Grinter, R. E., & Palen, L. A. (2002) · ACM Conference on Computer Supported Cooperative Work (CSCW) · doi:10.1145/587078.587082 · Cited by 425 · see citing works
Implementing Domain-Specific Languages with Xtext and Xtend
Bettini, L. (2013) · CERN Document Server (European Organization for Nuclear Research) · Cited by 344 · see citing works
Klopfenstein, L. C., Delpriori, S., Malatini, S., & Bogliolo, A. (2017) · Designing Interactive Systems Conference · doi:10.1145/3064663.3064672 · Cited by 257 · see citing works
Empirical software engineering experts on the use of students and professionals in experiments
Falessi, D., Juristo, N., Wohlin, C., Turhan, B., Münch, J., Jedlitschka, A., & Oivo, M. (2017) · Empirical Software Engineering · doi:10.1007/s10664-017-9523-3 · Cited by 257 · see citing works
Bringing chatbots into education: Towards natural language negotiation of open learner models
Kerly, A., Hall, P., & Susan Bull, A. (2006) · Knowledge-Based Systems · doi:10.1016/j.knosys.2006.11.014 · Cited by 239 · see citing works
Software Language Engineering: Creating Domain-Specific Languages Using Metamodels
Kleppe, A. (2008) · Cited by 226 · see citing works
Hutchinson, J., Whittle, J., & Rouncefield, M. (2013) · Science of Computer Programming · doi:10.1016/j.scico.2013.03.017 · Cited by 223 · see citing works
Natural Language Processing for Online Applications
Jackson, P. E., & Moulinier, I. (2007) · Natural language processing · doi:10.1075/nlp.5 · Cited by 123 · see citing works
An e-business chatbot using AIML and LSA
Thomas, N. (2016) · International Conference on Advances in Computing, Communications and Informatics (ICACCI) · doi:10.1109/icacci.2016.7732476 · Cited by 109 · see citing works
Collaborative Modeling and Group Decision Making Using Chatbots in Social Networks
Pérez-Soler, S., Guerra, E., & Lara, J. D. (2018) · IEEE Software · doi:10.1109/ms.2018.290101511 · Cited by 76 · see citing works
A Review of Technologies for Conversational Systems
Masche, J., & Le, N.-T. (2017) · Advances in intelligent systems and computing · doi:10.1007/978-3-319-61911-8_19 · Cited by 71 · see citing works
Concepts and models for typing events for event-based systems
Rozsnyai, S., Schiefer, J., & Schatten, A. (2007) · doi:10.1145/1266894.1266904 · Cited by 47 · see citing works
Dynamic Role Binding in Blockchain-Based Collaborative Business Processes
López‐Pintado, O., Dumas, M., García‐Bañuelos, L., et al. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-21290-2_25 · Cited by 44 · see citing works
Cognifying Model-Driven Software Engineering
Cabot, J., Clarisó, R., Brambilla, M., et al. (2018) · Lecture notes in computer science · doi:10.1007/978-3-319-74730-9_13 · Cited by 39 · see citing works
Self-citationChatbot Dimensions that Matter: Lessons from the Trenches
Pereira, J., & Díaz, Ó. (2018) · Lecture notes in computer science · doi:10.1007/978-3-319-91662-0_9 · Cited by 39 · see citing works
Multi-platform Chatbot Modeling and Deployment with the Jarvis Framework
Daniel, G., Cabot, J., Deruelle, L., et al. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-21290-2_12 · Cited by 39 · see citing works
Self-citationUsability of Chatbots: A Systematic Mapping Study
Ren, R., Castro, J. W., Acuña, S. T., & Lara, J. D. (2019) · Proceedings/Proceedings of the ... International Conference on Software Engineering and Knowledge Engineering · doi:10.18293/seke2019-029 · Cited by 31 · see citing works
Perceived language complexity in GitHub issue discussions and their effect on issue resolution
Kavaler, D., Sirovica, S., Hellendoorn, V. J., Aranovich, R., & Filkov, V. (2017) · IEEE/ACM International Conference on Automated Software Engineering (ASE) · doi:10.1109/ase.2017.8115620 · Cited by 29 · see citing works
From Process Models to Chatbots
López, A., Sànchez-Ferreres, J., Carmona, J., & Padró, L. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-21290-2_24 · Cited by 28 · see citing works
Model-Driven Engineering of Service Orchestrations
Brambilla, M., Dosmi, M., & Fraternali, P. (2009) · doi:10.1109/services-i.2009.94 · Cited by 18 · see citing works
Generating blogs out of product catalogues: An MDE approach
Díaz, Ó., & Villoria, F. M. (2010) · Journal of Systems and Software · doi:10.1016/j.jss.2010.05.075 · Cited by 14 · see citing works
Agent-oriented software engineering
Bežek, A., & Gams, M. (2003) · Adaptive Agents and Multi-Agents Systems · doi:10.1145/860722.860730 · Cited by 8 · see citing works
Flagged first, then by citations
Research works printed but not linked: 4
- B. Nardi, S. Whittaker, and E. Bradner, ''Interaction and outerac- tion: Instant messaging in action,'' in Proc. 3rd CSCW Conf., 2000, pp. 79-88.
- N. Jennings and M. Wooldridge, ''Agent-oriented software engineer- ing,'' Handbook Agent Technology, vol. 18. 2001. [Online]. Available: https://link.springer.com/book/10.1007/978-3-642-54432-3 · DOI
- B. J. Fogg, Persuasive Technology: Using Computers to Change What We Think and Do. New York, NY, USA: Ubiquity, Dec. 2002. [Online]. Available: https://www.amazon.com/Persuasive-Technology-Computers- Interactive-Technologies/dp/1558606432, doi: 10.1145/764008.763957. · DOI · Paper page
- GWENDAL DANIEL received the Ph.D. degree with the AtlanMod Team, Ecole des Mines de Nantes, France, in 2017. He is currently a Postdoc- toral Fellow with the SOM Research Lab, Inter- net Interdisciplinary Institute (IN3), a Research Center, Universitat Oberta de Catalunya (UOC). He also funded by the MegaM@rt2 ECSEL-JU project. His research interests include model driven engineering, model persistence, query, and transformation techniques, domain specific languages, and applying model-based techniques for large-scale data applications. He received the Best Thesis Award from the GDR-GPL and the INFORSID Association, in 2018.
Cited by
Sorted by citations
Future directions for chatbot research: An interdisciplinary research agenda
Følstad, A., Araujo, T., Law, E. L.-C., Brandtzaeg, P. B., Papadopoulos, S., Reis, L., Baez, M., Laban, G., McAllister, P., Ischen, C., et al. (2021) · Computing · doi:10.1007/s00607-021-01016-7 · Cited by 247 · see citing works
Zhang, K., Xie, Y., Chen, D., Ji, Z., & Wang, J. (2025) · BMC Psychology · doi:10.1186/s40359-025-03284-w · Cited by 38 · see citing works
Soni, A., Arora, R., Kumar, A., & Panwar, D. (2024) · 2024 International Conference on Electrical Electronics and Computing Technologies (ICEECT) · doi:10.1109/iceect61758.2024.10738994 · Cited by 3 · see citing works
- Authors
- Daniel, G., Cabot, J., Deruelle, L., & Derras, M.
- Affiliations
- Universitat Oberta de Catalunya (ES)
- Institució Catalana de Recerca i Estudis Avançats (ES)
- Berger-Levrault (France) (FR)
- Venue
- IEEE Access
- Published
- 2020
- Volume
- 8
- Pages
- 15332-15346
- ISSN
- 2169-3536 (ISSN-L)
- OpenAlex
- W3000206684
- Cited by
- 173
- References
- 27
- Citations by year
- 2026: 9 · 2025: 37 · 2024: 38 · 2023: 27 · 2022: 25 · 2021: 28 · 2020: 9
- FWCI
- 8.74
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- IEEE Access (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Spanish Government (TIN2016-75944-R)
- Electronic Component Systems for European Leadership Joint Undertaking (737494)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Speech and dialogue systems
- Physical Sciences › Computer Science › Artificial Intelligence › AI in Service Interactions
- Physical Sciences › Computer Science › Software › Model-Driven Software Engineering Techniques
- Keywords
- voicebots, low-code development, domain-specific languages, open source software, chatbot deployment
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