Involving External Stakeholders in Project Courses

Problem: The involvement of external stakeholders in capstone projects and project courses is desirable due to its potential positive effects on the students. Capstone projects particularly profit from the inclusion of an industrial partner to make the project relevant and help students acquire professional skills. In addition, an increasing push towards education that is aligned with industry and incorporates industrial partners can be observed. However, the involvement of external stakeholders in teaching moments can create friction and could, in the worst case, lead to frustration of all involved parties. Contribution: We developed a model that allows analysing the involvement of external stakeholders in university courses both in a retrospective fashion, to gain insights from past course instances, and in a constructive fashion, to plan the involvement of external stakeholders. Key Concepts: The conceptual model and the accompanying guideline guide the teachers in their analysis of stakeholder involvement. The model is comprised of several activities (define, execute, and evaluate the collaboration). The guideline provides questions that the teachers should answer for each of these activities. In the constructive use, the model allows teachers to define an action plan based on an analysis of potential stakeholders and the pedagogical objectives. In the retrospective use, the model allows teachers to identify issues that appeared during the project and their underlying causes. Drawing from ideas of the reflective practitioner, the model contains an emphasis on reflection and interpretation of the observations made by the teacher and other groups involved in the courses. Key Lessons: Applying the model retrospectively to a total of eight courses shows that it is possible to reveal hitherto implicit risks and assumptions and to gain a better insight into the interaction...Comment: Abstract shortened since arxiv.org limits length of abstracts. See paper/pdf for full abstract. Paper is forthcoming, accepted August 2017. Arxiv version 2 corrects misspelled author nam

Transitioning from Teaching Canonical Engineering to Sustainable Development

To be published in a special issue of the International Journal of Sustainability in Higher Education</p

Transitioning from Teaching Canonical Engineering to Sustainable Development

To be published in a special issue of the International Journal of Sustainability in Higher Education</p

A Scholarship Approach to Model-Driven Engineering

Model-Driven Engineering is a paradigm for software engineering where software models are the primary artefacts throughout the software life-cycle. The aim is to define suitable representations and processes that enable precise and efficient specification, development and analysis of software. Our contributions to Model-Driven Engineering are structured according to Boyer's four functions of academic activity - the scholarships of teaching, discovery, application and integration. The scholarships share a systematic approach towards seeking new insights and promoting progressive change. Even if the scholarships have their differences they are compatible so that theory, practice and teaching can strengthen each other. Scholarship of Teaching: While teaching Model-Driven Engineering to under-graduate students we introduced two changes to our course. The first change was to introduce a new modelling tool that enabled the execution of software models while the second change was to adapt pair lecturing to encourage the students to actively participate in developing models during lectures. Scholarship of Discovery: By using an existing technology for transforming models into source code we translated class diagrams and high-level action languages into natural language texts. The benefit of our approach is that the translations are applicable to a family of models while the texts are reusable across different low-level representations of the same model. Scholarship of Application: Raising the level of abstraction through models might seem a technical issue but our collaboration with industry details how the success of adopting Model-Driven Engineering depends on organisational and social factors as well as technical. Scholarship of Integration: Building on our insights from the scholarships above and a study at three large companies we show how Model-Driven Engineering empowers new user groups to become software developers but also how engineers can feel isolated due to poor tool support. Our contributions also detail how modelling enables a more agile development process as well as how the validation of models can be facilitated through text generation. The four scholarships allow for different possibilities for insights and explore Model-Driven Engineering from diverse perspectives. As a consequence, we investigate the social, organisational and technological factors of Model-Driven Engineering but also examine the possibilities and challenges of Model-Driven Engineering across disciplines and scholarships

Results from Two Controlled Experiments on the Effect of Using Requirement Diagrams on the Requirements Comprehension

We carried out a controlled experiment and an external replication to investigate whether the use of requirement diagrams of the SysML (System Modeling Language) helps in the comprehensibility of requirements. The original experiment was conducted at the University of Basilicata in Italy with Bachelor students, while its replication was executed at the University of Gothenburg in Sweden with Bachelor and Master students. A total of 87 participants took part in the two experiments. The achieved results indicated that the comprehension of requirements is statistically higher when requirements speci cation documents include requirement diagrams without any impact on the time to accomplish comprehension tasks

Real-life Observations from Full Electric City Buses Utilising the Information Technology for Public Transport Specification

Poster presented at UITP Global Public Transport SummitRIVSILO

Parsing linear context-free rewriting systems

We describe four different parsing algorithms for Linear Context-Free Rewriting Systems (Vijay-Shanker et al., 1987). The algorithms are described as deduction systems, and possible optimizations are discussed. The only parsing algorithms presented for linear contextfree rewriting systems (LCFRS; Vijay-Shanker et al., 1987) and the equivalent formalism multiple context-free grammar (MCFG; Seki et al., 1991) are extensions of the CKY algorithm (Younger, 1967), more designed for their theoretical interest, and not for practical purposes. The reason for this could be that there are not many implementations of these grammar formalisms. However, since a very important subclass of the Grammatical Framework (Ranta, 2004) is equivalent to LCFRS/MCFG (Ljunglöf, 2004a; Ljunglöf, 2004b), there is a need for practical parsing algorithms. In this paper we describe four different parsing algorithms for Linear Context-Free Rewriting Systems. The algorithms are described as deduction systems, and possible optimizations are discussed. 1 Introductory definitions A record is a structure Γ = {r1 = a1;...; rn = an}, where all ri are distinct. That this can be seen as a set of feature-value pairs. This means that we can define a simple version of record unification Γ1 ⊔ Γ2 as the union Γ1∪Γ2, provided that there is no r such that Γ1.r ̸ = Γ2.r. We sometimes denote a sequence X1,..., Xn by the more compact ⃗ X. To update the ith record in a list of records, we write ⃗Γ[i: = Γ]. To substitute a variable Bk for a record Γk in any data structure Γ, we writ

Translating Platform-Independent Code into Natural Language Texts

Understanding software artifacts is not only time-consuming, without the proper training and experience it can be impossible. From a model-driven perspective there are two benefits from translating platform-independent models into natural language texts: First, the non-functional properties of the solution have already been omitted meaning that the translations focus on describing the functional behaviour of the system. Second, the platform-independent models are reusable across platforms and so are the translations generated from them. As a proof-of-concept a platform-independent Action language is translated into natural language texts through the framework of model transformations

Sustainable AI and Disruptive Policy – AI Regulatory Sandboxes

The rapid pace of digitalization and the new opportunities for value creation has raised a concern that regulation is lagging behind and becoming an obstacle. A number of tools have been proposed in order to facilitate innovation that is aligned with existing or upcoming policies. A specific case of both facilitating and regulating innovation is the EU’s proposed regulation of AI systems. The act not only poses legal requirements on providers and users of AI systems but also includes measures for facilitating innovation – the concept of regulatory sandboxes is defined with specific purposes together with legal exempts. At the time of releasing our paper, the trilogue has reached a political agreement. This means the proposed AI Act will be, even though we do not yet have the final wording. By mapping the negotiation mandates of the European Commission, the European Parliament and the Council of the European Union against Swedish experiences of facilitating innovation and regulatory compliance in relation to AI, we still suggest launching pilots for regulatory sandboxes without delay. Based on our own experiences from conducting policy labs and those reported on by others from their regulatory trials, we conclude that it takes time to grow confidence in defining a research agenda with other stakeholders and then strike the balance between facilitation and surveillance of innovation. Something that will require institutional learning and capacity building. The mandate to foster and facilitate regulatory compliance as well as innovation, given to the public sector through the AI Act’s regulatory sandboxes, is disruptive. It changes the role and responsibilities for some national authorities, requiring the acquisition of new competences and resources, as well as for the private sector. When they team up with a competent authority the mandate to act becomes larger, as does the responsibility with regards to which kinds of innovation to drive. Conducting trials in the current window of opportunity, between now and when the AI Act is in force, will create experiences that policy makers and stakeholders can draw on when creating the detailed guidelines for organising regulatory sandboxes. Adopting an incremental and iterative process enables a transition from learning the basics of selecting a case and finding relevant partners to detailing how to process data and sharing responsibilities and rewards.This publication is partly financed by the Swedish Innovation Agency, grant number 2021-03639. </p