Starting June 2022, our book “Model Driven Software Engineering in Practice” (co-authored with Jordi Cabot and Manuel Wimmer) is now also available via Springer . This means the price is actually lower, and if you are affiliated with an academic institution, you may even have free access to the book through your institutional access. Check it here.
Together with the book, we provided free bonus material including: over 500 slides on MDE ready to use for classes; and all the book examples in the book’s github repository.
Modern User Interfaces (UIs) are becoming complex software artifacts themselves, through integration of AI-enhanced software components that enable even more natural interactions, including the possibility to use Natural Language Processing (NLP) via chatbots or voicebots (aka., Conversational User Interfaces or CUIs).
Some times, several types of UIs are combined as part of the same application (e.g. a chatbot in a web page), what it is known as Multiexperience User Interface. These multiexperience UIs may be built together by using a Multiexperience Development Platform (MXDP).
“Multiexperience development involves ensuring a consistent user experience across web, mobile, wearable, conversational and immersive touchpoints”. [Gartner]
A typical scenario of multiexperience user interaction could unroll as follows (see image below too). Suppose that a customer on a Sunday morning wants to buy a new technical product (a cell phone or a home theater system). He first interacts with his home assistant (like Alexa or Google assistant) to ask it to find the best nearby tech store open on Sunday. With this information in mind, he looks at the store web site on his PC and, being satisfied with the kind of store, he asks the web site chatbot to find the type of products he is looking for. After browsing the various alternatives, he finds one item he likes, and sets the place and the product as preferences on his mobile phone. He reads the details of the product on the phone while walking to his car. When he reaches the car, he transfers the information about the place to the car navigation system and drives there. Finally, in the stores he looks around, tries various items, reads the reviews about them on a dedicated mobile app, and finally picks up the product and pays for it.
This kind of dynamic and seamless interaction demands a variety of complex design and implementation mechanisms to be put in place. Clearly, also very critical integration, evolution, and maintenance challenges need to be faced for these CUIs. Developers need to handle the coordination of the cognitive services to build multiexperience UIs, integrate them with external services, and worry about extensibility, scalability, and maintenance.
We believe a model-driven approach for MXDP could be an important first step towards facilitating the specification of rich UIs able to coordinate and collaborate to provide the best experience for end-users. Indeed, most non-trivial systems adhere to some kind of model-based philosophy, where software design models (including GUI models) are transformed into the production code the system executes at run-time. This transformation can be (semi)automated in some cases.
Our recent research tackles the application of model-driven techniques to the development of software applications embedding a multiexperience UI.
The research has been published in our recent paper Towards a Model-Driven Approach for Multiexperience AI-based User Interfaces, co-authored by Elena Planas, Gwendal Daniel, Marco Brambilla and Jordi Cabot, recently published in the International Journal on Software and Systems Modeling (SoSyM) available online here (open access).
The paper contribution is twofold:
we raise the abstraction level used in the definition of this new kind of conversational and smart interfaces.
we show how these CUI models can be used in conjunction with more “traditional” GUI models to combine the benefits of all these different types of interfaces in a multiexperience development project.
In practice, we propose a new Domain Specific Language (DSL), that generalizes the one defined by the Xatkit model to cover all types of CUIs, and we show how this seamlessly integrates with appropriate extensions of the IFML model to design comprehensive multi-experience interfaces.
IFML model integrating traditional navigation of a web interface and a chatbot component.
You can refer to the full paper here for covering the details. The paper reference is:
Planas, E., Daniel, G., Brambilla, M., Cabot, J. Towards a model-driven approach for multiexperience AI-based user interfaces. Software and System Modeling (SoSyM)20, 997–1009 (2021). https://doi.org/10.1007/s10270-021-00904-y
In the context of Domain-Specific Modeling Language (DSML) development, the involvement of end-users is crucial to assure that the resulting language satisfies their needs.
In our paper presented at SLE 2017 in Vancouver, Canada, on October 24th within the SPLASH Conference context, we discuss how crowdsourcing tasks can exploited to assist in domain-specific language definition processes. This is in line with the vision towards cognification of model-driven engineering.
The slides are available on slideshare:
Indeed, crowdsourcing has emerged as a novel paradigm where humans are employed to perform computational and information collection tasks. In language design, by relying on the crowd, it is possible to show an early version of the language to a wider spectrum of users, thus increasing the validation scope and eventually promoting its acceptance and adoption.
Ready to accept improper use of your tools?
We propose a systematic (and automatic) method for creating crowdsourcing campaigns aimed at refining the graphical notation of DSMLs. The method defines a set of steps to identify, create and order the questions for the crowd. As a result, developers are provided with a set of notation choices that best fit end-users’ needs. We also report on an experiment validating the approach.
Improving the quality of the language notation may improve dramatically acceptance and adoption, as well as the way people use your notation and the associated tools.
Essentially, our idea is to spawn to the crowd a bunch of questions regarding the concrete syntax of visual modeling languages, and collect opinions. Based on different strategies, we generate an optimal notation and then we check how good it is.
In the paper we also validate the approach and experiment it in a practical use case, namely studying some variations over the BPMN modeling language.
The full paper can be found here: https://dl.acm.org/citation.cfm?doid=3136014.3136033. The paper is titled: “Better Call the Crowd: Using Crowdsourcing to Shape the Notation of Domain-Specific Languages” and was co-authored by Marco Brambilla, Jordi Cabot, Javier Luis Cánovas Izquierdo, and Andrea Mauri.
You can also access the Web version on Jordi Cabot blog.
The artifacts described in this paper are also referenced on findresearch.org, namely referring to the following materials:
Long time ago, in the past century, the International DB Research Community used to meet for assessing new research directions, starting the meetings with 2-minutes gong showsto tell each one’s opinion and influencing follow-up discussion. Bruce Lindsay from IBM had just been quoted for his message:
There are 3 important things in data management: performance, performance, performance.
Stefano Ceri had a chance to speak out immediately after and to give a syntactically similar but semantically orthogonal message:
There are 3 important things in data management: modeling, modeling, modeling.
Data management is continuously evolving for serving the needs of an increasingly connected society. New challenges apply not only to systems and technology, but also to the models and abstractions for capturing new application requirements.
In our retrospective paper, we describe several models and abstractions which have been progressively designed to capture new forms of data-centered interactions in the last twenty five years – a period of huge changes due to the spreading of web-based applications and the increasingly relevant role of social interactions.
We initially focus on Web-based applications for individuals, then discuss applications among enterprises, and this is all about WebML and IFML; then we discuss how these applications may include rankings which are computed using services or using crowds, and this is related to our work on crowdsourcing (liquid query and crowdsearcher tool); we conclude with hints to a recent research discussing how social sources can be used for capturing emerging knowledge (the social knowledge extractor perspective and tooling).
It’s also true that model-driven engineering is not necessarily the tool of choice for this to happen. Why? As technician, we always tend to blame the customer for not understanding our product. But maybe we should look into ourselves and the kind of tools (conceptual and technical) the MDE community is offering. I’m pretty sure we could find plenty of space for improvement.
This is the summary of a joint contribution with Eric Umuhoza to ICEIS 2017 on Model-driven Development of User Interfaces for IoT via Domain-specific Components & Patterns.
Internet of Things technologies and applications are evolving and continuously gaining traction in all fields and environments, including homes, cities, services, industry and commercial enterprises. However, still many problems need to be addressed.
For instance, the IoT vision is mainly focused on the technological and infrastructure aspect, and on the management and analysis of the huge amount of generated data, while so far the development of front-end and user interfaces for IoT has not played a relevant role in research.
On the contrary, we believe that user interfaces in the IoT ecosystem they can play a key role in the acceptance of solutions by final adopters.
In this paper we present a model-driven approach to the design of IoT interfaces, by defining a specific visual design language and design patterns for IoT applications, and we show them at work. The language we propose is defined as an extension of the OMG standard language called IFML.
The slides of this talk are available online on Slideshare as usual:
This year I’m co-organizing with Davide Rossi and a bunch of experts in Business Process Management and Enterprise Architecture a new event called BPM-EA, which aims at bringing together the broad topics of business processes, modeling, and enterprise architecture.
These disciplines are quickly evolving and intertwining with each other, and are often referred to with the broad term of business modeling.
I believe there is a strong need of exploring new paths of improvement, integration and consolidation of these disciplines.
If you are interested to participate and contribute, we seek contributions in the areas of enterprise and systems architecture and modeling, multilevel models tracing and alignment, models transformation, IT & business alignment (both in terms of modeling and goals), tackling both technical (languages, systems, patterns, tools) and social (collaboration, human-in-the-loop) issues.
The deadline for submitting a paper is September 15, 2016.
You can find the complete call and further details on the event website:
This year we decided to be present at ICWSM 2016 in Cologne, with two contributions that basically blend model driven software engineering and big data analysis, to provide value to users and citizens both in terms of high quality software and added value information provision.
Studying Multicultural Diversity of Cities and Neighborhoods through Social Media Language Detection, presented at the CityLab workshop at ICWSM 2016. The focus of this work is to study cities as melting pots of people with different culture, religion, and language. Through multilingual analysis of Twitter contents shared within a city, we analyze the prevalent language in the different neighborhoods of the city and we compare the results with census data, in order to highlight any parallelisms or discrepancies between the two data sources. We show that the officially identified neighborhoods are actually representing significantly different communities and that the use of the social media as a data source helps to detect those weak signals that are not captured from traditional data. Slides here:
We now continuously look for new dataset and computational challenges. Feel free to ask or to propose ideas!
To keep updated on my activities you can subscribe to the RSS feed of my blog or follow my twitter account (@MarcoBrambi).
As model-driven engineering practitioners, we sometimes encounter weird modelling notations for the languages we use… and this is also definitely true for modelling language adopters!
We always end up wondering who could ever think about such or such terrible syntax for a language, also for very well established notations (including, for instance, some pieces of UML or BPMN). I take it for granted this is a common experience (raise your hand if not).
This lead to the idea that also syntax definition should be a more collaborative task. Therefore, we decided to give it a try and test whether crowdsourcing techniques can be used to create and validate language constructs, in particular, its concrete syntax (i.e. notation).
As part of our research work in this area, together with Jordi Cabot’s group, we have setup as an experiment a crowdsourcing campaign using our tool CrowdSearcher.
This boils down to a very simple case: we are asking anyone on the web to look into a very small subset of BPMN, and to participate into 3 simple tasks, including questions for selecting the best notation for some of the BPMN concepts (it won’t take more than 3 minutes).
We asked people to help us responding these 3 quick questions!
Some disclaimers:
1. we don’t care if you are the world’s expert in BPMN or if you never heard about it. We want you!
2. we ask you to register before taking the task (just click on the Register button once you enter the task), simply to make sure we only have one performance per person. All the analysis will run on anonymous data.
3. The results of the survey will be made publicly available in the following months.
To keep updated on my activities you can subscribe to the RSS feed of my blog or follow my twitter account (@MarcoBrambi).
While this is definitely not a statistically significant benchmark, I think it’s a significant insight on the field and on how ourselves (MDE practitioners and researchers) see the field.
Basically, there is absolutely no agreement and common understanding!!
On the question on whether MDE is a sound engineering discipline, one third of responders said yes, one third said no, and one third is not sure. Perfectly even distribution!
In summary, if you don’t count uncertainty, here is what we collected:
I’m happy the panelists raised several issues I pointed out myself in the introduction to the conference: as software modelling scientists, we are facing big challenges nowadays, as the focus of modelling is shifting, due to the fact that now software is more and more pervasive, in fields like IoT, social network and social media, personal and wearable devices, and so on.
Panel included the keynote speakers of the conference: Manfred Broy, Paola Inverardi and Lionel Briand, three well known names in the Software Engineering and Modeling community.
Manfred Broy highlighted:
there is a different between scientific maturity and practical maturity. Sometimes, the latter in companies is far beyond the former.
a truck company in Germany has been practicing modelling for years, and now has this take on the world: whatever is not in the models, doesn’t exist
The current challenges are about how to model cyber-physical systems
The flow of model must be clarified: traceability, refinement, model integration are crucial. You must grant syntactic and semantic coherence
You also need a coherent infrastructure of tools and artefacts, that grants logic integration. You cannot obtain coherence of models without coherence of tools.
You need a lot of automation, otherwise you won’t get practical maturity. This doesn’t mean to have end-to-end, or round-trip complete model transformations, but you need to push automaton as much as possible
Lionel Briand clarified that:
by definition, engineering underpins deep mathematical background as a foundation and implies application of the scientific method to solving problems
maturity can be evaluated in terms of: how much math underpinning is foundational, how many standards and tools exist and are used, whether the scientific approach is used
Tools, methods, engineers, and scale of MDE are increasing (aka. MDE is increasingly more difficult to avoid)
Paola Inverardi recalled a position by Jean Bezivin:
we need to split Domain Engineering (where the problem is) and Support Engineering (where the solution will be)
MDE is the application of modelling principles and tools to any engineering field
So: is actually SOFTWARE the main field of interest of model-driven engineering?
In the modern interpretation of life, covering from smart cities to embedded, wearable, and cyber-physical systems, is the border between the environment and the system still relevant?
In the future we will need to rely less and less on the “creativity” of engineers when building models, and more and more on the scientific/ quantitative/ empirical methods for building models
The debate obviously stirred around this aspects, starting from Bran Selic who asked a very simple question:
Isn’t it the case that the real problem is about the word “modeling”? In any other fields (architecture, mechanics, physics) modelling is implicit and obvious. Why not in our community? At the end, what we want to achieve is to raise abstraction and increase automation, nothing else.
Other issues have been raised too:
why is there so much difference in attitude towards modelling between Europe and US?
what’s the role of notations and standards in the success / failure of MDE?
What’s your take on this issue?
Feel free to share your thoughts here or on Twitter, mentioning me (@MarcoBrambi).
AND:
Respond to my poll on twitter!
To keep updated on my activities you can subscribe to the RSS feed of my blog or follow my twitter account (@MarcoBrambi).
Marco Brambilla 