Cited By
View all- Martins JBranco FMamede H(2023)Combining low-code development with ChatGPT to novel no-code approaches: A focus-group studyIntelligent Systems with Applications10.1016/j.iswa.2023.20028920(200289)Online publication date: Nov-2023
Low-code experimentation on software products
Authors: 
Sebastian Gottschalk, Rakshit Bhat, Nils Weidmann, Jonas Kirchhoff, Gregor EngelsAuthors Info & Claims
Pages 798 - 807
Abstract
The continuous development of software products can be supported by systematically testing different software variants with the users. During this so-called continuous experimentation, different variants are presented to dedicated user groups, and the results are compared to determine the better-performing one. However, the product owner often defines those experiments while the software developers do their implementation. This, in turn, results in additional communication and synchronization effort. To bridge the gap between the definition and implementation of experiments, we provide a solution based on low-code development. Low-code development, in turn, allows the development of software products by non-developers using a graphical user interface (GUI). Within our solution, the product owner can model the experiments, product variants, and user groups within a GUI. Code wrappers are generated from those models, which the software developers can modify. Last, those variants are executed by different users, and the results are visualized for the product owner. This workshop paper shows the technical feasibility based on a streaming application.
References
[1]
Pierre A. Akiki, Arosha K. Bandara, and Yijun Yu. 2014. Adaptive Model-Driven User Interface Development Systems. ACM Computing Surveys 47, 1 (2014), 1--33.
[2]
Sven Apel, Don Batory, Christian Kästner, and Gunter Saake. 2013. Feature-Oriented Software Product Lines. Springer, Heidelberg.
[3]
Florian Auer and Michael Felderer. 2021. An Approach for Platform-Independent Online Controlled Experimentation. In Software Quality: Future Perspectives on Software Engineering Quality. Vol. 404. Springer, Cham, 139--158.
[4]
Lionel Balme, Alexandre Demeure, Nicolas Barralon, Joëlle Coutaz, and Gaëlle Calvary. 2004. CAMELEON-RT: A Software Architecture Reference Model for Distributed, Migratable, and Plastic User Interfaces. In Ambient Intelligence. LNCS, Vol. 3295. Springer, Heidelberg, 291--302.
[5]
Mariana Bexiga, Stoyan Garbatov, and João Costa Seco. 2020. Closing the gap between designers and developers in a low code ecosystem. In Proceedings of the 23rd ACM/IEEE International Conference on Model Driven Engineering Languages and Systems: Companion Proceedings. ACM, New York, 1--10.
[6]
Alexander C. Bock and Ulrich Frank. 2021. Low-Code Platform. Business & Information Systems Engineering 63, 6 (2021), 733--740.
[7]
Marco Brambilla, Jordi Cabot, and Manuel Wimmer. 2017. Model-Driven Software Engineering in Practice: Second Edition. Synthesis Lectures on Software Engineering 3, 1 (2017), 1--207.
[8]
Jordi Cabot. 2020. Positioning of the low-code movement within the field of model-driven engineering. In Proceedings of the 23rd ACM/IEEE International Conference on Model Driven Engineering Languages and Systems: Companion Proceedings. ACM, New York, 1--3.
[9]
Gaëlle Calvary, Joëlle Coutaz, David Thevenin, Quentin Limbourg, Laurent Bouillon, and Jean Vanderdonckt. 2003. A Unifying Reference Framework for multitarget user interfaces. Interacting with Computers 15, 3 (2003), 289--308.
[10]
Javier Cámara, Pedro Correia, Rogério de Lemos, David Garlan, Pedro Gomes, Bradley Schmerl, and Rafael Ventura. 2016. Incorporating architecture-based self-adaptation into an adaptive industrial software system. Journal of Systems and Software 122 (2016), 507--523.
[11]
Javier Cámara and Alfred Kobsa. 2009. Facilitating Controlled Tests of Website Design Changes: A Systematic Approach. In Web Engineering. Vol. 5648. Springer, Heidelberg, 370--378.
[12]
Rafael Capilla, Jan Bosch, Pablo Trinidad, Antonio Ruiz-Cortés, and Mike Hinchey. 2014. An overview of Dynamic Software Product Line architectures and techniques: Observations from research and industry. Journal of Systems and Software 91 (2014), 3--23.
[13]
Aleksander Fabijan, Pavel Dmitriev, Helena Holmstrom Olsson, and Jan Bosch. 2017. The Evolution of Continuous Experimentation in Software Product Development: From Data to a Data-Driven Organization at Scale. In 2017 IEEE/ACM 39th International Conference on Software Engineering (ICSE). IEEE, 770--780.
[14]
Fabian Fagerholm, Alejandro Sanchez Guinea, Hanna Mäenpää, and Jürgen Münch. 2014. Building blocks for continuous experimentation. In Proceedings of the 1st International Workshop on Rapid Continuous Software Engineering - RCoSE 2014. ACM, New York, 26--35.
[15]
Fabian Fagerholm, Alejandro Sanchez Guinea, Hanna Mäenpää, and Jürgen Münch. 2017. The RIGHT model for Continuous Experimentation. J. Syst. Softw. 123 (2017), 292--305.
[16]
Piero Fraternali. 2015. Interaction flow modeling language: Model-driven UI engineering of web and mobile apps with IFML. Elsevier, Amsterdam. http://www.sciencedirect.com/science/book/9780128001080
[17]
Ilias Gerostathopoulos, Frantisek Plasil, Christian Prehofer, Janek Thomas, and Bernd Bischl. 2021. Automated Online Experiment-Driven Adaptation-Mechanics and Cost Aspects. IEEE Access 9 (2021), 58079--58087.
[18]
Carlo Ghezzi and Amir Molzam Sharifloo. 2013. Dealing with Non-Functional Requirements for Adaptive Systems via Dynamic Software Product-Lines. In Software Engineering for Self-Adaptive Systems II. Lecture Notes in Computer Science, Vol. 7475. Springer, Heidelberg, 191--213.
[19]
Sebastian Gottschalk, Enes Yigitbas, and Gregor Engels. 2020. Model-Based Hypothesis Engineering for Supporting Adaptation to Uncertain Customer Needs. In Business Modeling and Software Design. Vol. 391. Springer, Cham, 276--286.
[20]
Sebastian Gottschalk, Enes Yigitbas, and Gregor Engels. 2022. Model-driven Continuous Experimentation on Component-based Software Architectures. In Proceedings of the 19th International Conference on Software Architectures. IEEE.
[21]
Faezeh Khorram, Jean-Marie Mottu, and Gerson Sunyé. 2020. Challenges & opportunities in low-code testing. In Proceedings of the 23rd ACM/IEEE International Conference on Model Driven Engineering Languages and Systems: Companion Proceedings. ACM, New York, 1--10.
[22]
Barbara Lopes, Sergio Amorim, and Carla Ferreira. 2021. Solution Discovery over Feature Toggling with Built-in Abstraction in OutSystems. In 2021 ACM/IEEE International Conference on Model Driven Engineering Languages and Systems Companion (MODELS-C). IEEE, 47--56.
[23]
David Issa Mattos, Jan Bosch, and Helena Holmström Olsson. 2017. More for Less: Automated Experimentation in Software-Intensive Systems. In Product-Focused Software Process Improvement. LNCS, Vol. 10611. Springer, Cham, 146--161.
[24]
Helena Holmström Olsson and Jan Bosch. 2014. The HYPEX Model: From Opinions to Data-Driven Software Development. In Continuous Software Engineering. Vol. 14. Springer, 155--164.
[25]
Helena Holmström Olsson and Jan Bosch. 2015. Towards Continuous Customer Validation: A Conceptual Model for Combining Qualitative Customer Feedback with Quantitative Customer Observation. In Software Business. Vol. 210. Springer, 154--166.
[26]
Md Tajmilur Rahman, Louis-Philippe Querel, Peter C. Rigby, and Bram Adams. 2016. Feature toggles. In Proceedings of the 13th International Conference on Mining Software Repositories. ACM, New York, 201--211.
[27]
Eric Ries. 2014. The Lean Startup: How Today's Entrepreneurs Use Continuous Innovation to Create Radically Successful Businesses. Crown Business, USA.
[28]
Amir Molzam Sharifloo, Andreas Metzger, Clément Quinton, Luciano Baresi, and Klaus Pohl. 2016. Learning and evolution in dynamic software product lines. In Proceedings of the 11th International Symposium on Software Engineering for Adaptive and Self-Managing Systems. ACM, New York, 158--164.
[29]
David J. Teece. 2010. Business Models, Business Strategy and Innovation. Long Range Planning 43, 2-3 (2010), 172--194.
[30]
Jason Wong, Kimihiko Iijima, Adrian Leow, Akash Jain, and Paul Vincent. 2021. Gartner Magic Quadrant for Enterprise Low-Code Application Platforms. https://www.gartner.com/en/documents/4005939
[31]
Enes Yigitbas, Ivan Jovanovikj, Kai Biermeier, Stefan Sauer, and Gregor Engels. 2020. Integrated model-driven development of self-adaptive user interfaces. Software & Systems Modeling 19, 5 (2020), 1057--1081.
Index Terms
- Low-code experimentation on software products
Recommendations
Situational development of low-code applications in manufacturing companies
MODELS '22: Proceedings of the 25th International Conference on Model Driven Engineering Languages and Systems: Companion ProceedingsCompanies show an increasing interest in low-code development platforms to facilitate application development by domain experts without sophisticated software development knowledge. Thus, companies aim for a more efficient development of more effective ...
DevOps Practitioners’ Perceptions of the Low-code Trend
ESEM '22: Proceedings of the 16th ACM / IEEE International Symposium on Empirical Software Engineering and MeasurementBackground: DevOps is currently one of the main trends in software development. Low-Code is also an emerging tendency that, combined with DevOps, may offer significant value to software businesses by improving the process. However, how DevOps practices ...
An initial investigation of test driven development in industry
SAC '03: Proceedings of the 2003 ACM symposium on Applied computingTest Driven Development (TDD) is a software development practice in which unit test cases are incrementally written prior to code implementation. In our research, we ran a set of structured experiments with 24 professional pair programmers. One group ...
Comments
Please enable JavaScript to view thecomments powered by Disqus.Information & Contributors
Information
Published In
October 2022
1003 pages
Copyright © 2022 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
- Univ. of Montreal: University of Montreal
- IEEE CS
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 09 November 2022
Check for updates
Author Tags
Qualifiers
- Research-article
Funding Sources
- German Research Foundation (DFG) within the CRC ?On-The-Fly Computing?
- German Federal Ministry of Education and Research (BMBF) through Software Campus grant ?KOVAS?
- North Rhine Westphalian Ministry of Economic Affairs, Innovation, Digitalisation and Energy (MWIDE) through It's OWL grant
Conference
MODELS '22
Sponsor:
MODELS '22: ACM/IEEE 25th International Conference on Model Driven Engineering Languages and Systems
October 23 - 28, 2022
Quebec, Montreal, Canada
Acceptance Rates
Overall Acceptance Rate 144 of 506 submissions, 28%
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- View Citations1Total Citations
- 280Total Downloads
- Downloads (Last 12 months)87
- Downloads (Last 6 weeks)8
Reflects downloads up to 18 Nov 2024
Other Metrics
Citations
Cited By
View all- Martins JBranco FMamede H(2023)Combining low-code development with ChatGPT to novel no-code approaches: A focus-group studyIntelligent Systems with Applications10.1016/j.iswa.2023.20028920(200289)Online publication date: Nov-2023
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in