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Industrial Track

The Industrial Track is an excellent vehicle for companies to advertise and promote their innovative products and services, connect with other companies and engage in discussions about research and development initiatives.

This event is held in parallel with a set of related conferences, namely MODELSWARD, ICISSP and SENSORNETS, attracting more than 1200 researchers from more than 60 countries in all continents, creating opportunities for knowledge and technology sharing, and facilitating future collaboration networks involving industrial project partners and interested conference delegates.

Furthermore, a parallel satellite event is being organized to attract European Projects and to stimulate discussions around the new European Framework for supporting R&D, Horizon 2020, which will include the participation of representatives from the European Commission.

The Industrial Track will include the following forms of participation:

  • Lease of a booth (2x2m with a table and chair) for distributing information or for demonstration purposes, which will be free of charge with the registration at the conference of at least one representative of the Company
  • Poster Display
  • Presentation/Demonstration of project results either orally or in other formats
  • Organization of a special session, workshop or a panel/round-table, focused on the company projects and topics of research
  • Tutorial
  • Company Presentation

Bran Selic, Malina Software Corp., Canada

February 20
09:00 – 10:30 - Oral Presentations:

  • Modeling and Analysis of Automotive Systems: Current Approaches and Future Trends.

Presenter: Ramesh S, General Motors Global R&D, USA
Abstract: The fierce competition among automotive manufacturers in introducing Advanced Driver Assist Systems (ADAS) and autonomous features has led to the explosive growth of the Electrical/Electronics (E/E) assets, including Software, in today's and future vehicles. The resource demand and quality requirements of these assets has increased consequently. Rigorous methodologies and tools are required for developing the E/E assets to meet the quality demands of these assets. This paper summarizes the current practices used in the industry for managing the development of these assets and discusses the future trends. The summary includes the description of three development strategies that are becoming important and critical, which are Model-driven Feature Development, Product Line Approach and Virtual Development and Integration of E/E architectures.

  • Model-Driven Development Challenges and Solutions

Presenter: Juha-Pekka Tolvanen, MetaCase, Finland
Abstract: Model-Driven Development is reported to succeed the best when modelling is based on domain-specific languages. Despite significant benefits MDD has not been applied as widely as expected. Costly definition of languages and related generators with tooling, their maintenance when the domain is not stable, challenges in scalability, and collaboration are some reasons that several studies mention. We believe these statements are justifiable but only when applying traditional programming tooling for modelling. Instead we show with data from practice that many of the challenges reported can be solved when using tools built for modelling in the first place.

  • Search-based Decision Ordering to Support Product Line Engineering of Cyber-Physical System

Presenter: Tao Yue, Simula Research Laboratory, Norway
Abstract: Industrial Cyber Physical Systems (CPSs) are naturally complex. Manual configuration of CPS product lines is error-prone and inefficient, which warrants the need for automated support of product configuration activities such as decision inference and decision ordering. A fully automated solution is often impossible for CPSs since some decisions must be made manually by configuration engineers and thus requiring an interactive and step-by-step configuration solution. Having an interactive solution with tool support in mind, we propose a search-based solution (named as Zen-DO) to support optimal ordering of configuration steps. The optimization objective has three parts: 1) minimizing overall manual configuration steps, 2) configuring most constraining decisions first, and 3) satisfying ordering dependencies among variabilities. We formulated our optimization objective as a fitness function and investigated it along with four search algorithms: Alternating Variable Method (AVM), (1+1) Evolutionary Algorithm (EA), Genetic Algorithm, and Random Search (a comparison baseline). Their performance is evaluated in terms of finding an optimal solution for two real-world case studies of varying complexity and results show that AVM and (1+1) EA significantly outperformed the others.

11:45 - 13:15 - Industrial Panel: "On the Adoption of Model-Based Methods in Industry"
Model-Based Engineering (MBE) has been touted as a new and substantively different approach to software development when compared to traditional methods, characterized by higher levels of abstraction and automation. Despite the availability of published and verifiable evidence that MBE can significantly boost both developer productivity and product quality in industrial projects, adoption of this approach by industry has been below expectations. Given this state of affairs, in this session we ask a panel of well-known industry experts to discuss their personal experience with the application of MBE in industrial practice and to present their views on the following core issues: (1) what are the reasons that MBE has not gained more traction in industrial software development and (2) what needs to be done to increase the adoption of MBE by industry. The audience will be encouraged to ask their own questions and voice their opinions about these and related issues.

Panel Moderator: Bran Selic, Malina Software Corp., Canada

Panel Participants
  • Francis Bordeleau, Product Manager SW Development, Ericsson, Canada
  • Juha-Pekka Tolvanen, CEO MetaCase, Finland
  • Ramesh S, Senior Technical Fellow, General Motors Global R&D, USA
  • Tao Yue, Senior Research Scientist, Simula Research Laboratory, Norway