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Handling Uncertainty in Automatically Generated Implementation Models in the Automotive Domain
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems. Arcticus Syst, Järfälla, Sweden.ORCID iD: 0000-0002-8027-0611
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0003-0416-1787
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0002-0401-1036
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0003-3242-6113
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2016 (English)In: 42nd Euromicro Conference series on Software Engineering and Advanced Applications SEAA 2016, 2016, p. 173-180Conference paper, Published paper (Refereed)
Abstract [en]

Models and model transformations, the two core constituents of Model-Driven Engineering, aid in software development by automating, thus taming, error-proneness of tedious engineering activities. In most cases, the result of these automated activities is an overwhelming amount of information. This is the case of one-to-many model transformations that, e.g. in designspace exploration, can potentially generate a massive amount of candidate models (i.e., solution space) from one single model. In our scenario, from one design model we generate a set of possible implementation models on which timing analysis is run. The aim is to find the best model from a timing perspective. However, multiple implementation models can have equally good analysis results. Therefore, the engineer is expected to investigate the solution space for making a final decision, using criteria which fall outside the analysis’ criteria themselves. Since candidate models can be many and very similar to each other, manually finding differences and commonalities is an impractical and errorprone task. In order to provide the engineer with an expressive representation of models’ commonalities and differences, we propose the use of modelling with uncertainty. We achieve this by elevating the solution space to a first-class status, adopting a compact notation capable of representing the solution space by means of a single model with uncertainty. Commonalities and differences are thus represented by means of uncertainty points for the engineer to easily grasp them and consistently make her decision without manually inspecting each model individually.

Place, publisher, year, edition, pages
2016. p. 173-180
National Category
Computer Systems
Identifiers
URN: urn:nbn:se:mdh:diva-32852DOI: 10.1109/SEAA.2016.32ISI: 000386649000027ISBN: 978-1-5090-2819-1 (print)OAI: oai:DiVA.org:mdh-32852DiVA: diva2:1009574
Conference
42nd Euromicro Conference series on Software Engineering and Advanced Applications SEAA 2016, 31 Aug 2016, Cyprus, Cyprus
Projects
SynthSoft - Synthesizing Predictable Software for Distributed Embedded Systems
Available from: 2016-09-30 Created: 2016-08-24 Last updated: 2017-11-30Bibliographically approved
In thesis
1. A Model-driven Development Approach with Temporal Awareness for Vehicular Embedded Systems
Open this publication in new window or tab >>A Model-driven Development Approach with Temporal Awareness for Vehicular Embedded Systems
2017 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Considering the ubiquitousness of software in modern vehicles, its increased value and development cost, an efficient software development became of paramount importance for the vehicular domain. It has been identified that early verification of non functional properties of  vehicular embedded software such as, timing, reliability and safety, is crucial to efficiency. However, early verification of non functional properties is hard to achieve with traditional software development approaches due to the abstraction and the lack of automation of these methodologies.

 

This doctoral thesis aims at improving efficiency in vehicular embedded software development by minimising the need for late, expensive and time consuming software modifications with early design changes, identified through timing verification, which usually are cheaper and faster. To this end, we introduce a novel model-driven approach which exploits the interplay of two automotive-specific modelling languages for the representation of functional and execution models and defines a suite of model transformations for their automatic integration.

 

Starting from a functional model (expressed by means of EAST-ADL), all the execution models (expressed by means of the Rubus Component Model) entailing unique timing configurations are derived. Schedulability analysis selects the set of the feasible execution models with respect to specified timing requirements. Eventually, a reference to the selected execution models along with their analysis results is automatically created in the related functional model to allow the engineer to investigate them.

 

The main scientific contributions of this doctoral thesis are i) a metamodel definition for the Rubus Component Model, ii) an automatic mechanism for the generation of Rubus models from EAST-ADL, iii) an automatic mechanism for the selection and back-propagation of the analysis results and related Rubus models to design level and iv) a compact notation for visualising the selected Rubus models by means of a single execution model.

Place, publisher, year, edition, pages
Västerås: Mälardalen University, 2017
Series
Mälardalen University Press Dissertations, ISSN 1651-4238 ; 250
National Category
Embedded Systems Software Engineering Computer Sciences
Research subject
Computer Science
Identifiers
urn:nbn:se:mdh:diva-37361 (URN)978-91-7485-366-7 (ISBN)
Public defence
2018-01-12, Gamma, Mälardalens högskola, Västerås, 10:15 (English)
Opponent
Supervisors
Available from: 2017-11-30 Created: 2017-11-29 Last updated: 2018-01-13Bibliographically approved

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Bucaioni, AlessioCicchetti, AntonioCiccozzi, FedericoMubeen, SaadSjödin, MikaelPierantonio, Alfonso
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