You are required to read and agree to the below before accessing a full-text version of an article in the IDE article repository.

The full-text document you are about to access is subject to national and international copyright laws. In most cases (but not necessarily all) the consequence is that personal use is allowed given that the copyright owner is duly acknowledged and respected. All other use (typically) require an explicit permission (often in writing) by the copyright owner.

For the reports in this repository we specifically note that

  • the use of articles under IEEE copyright is governed by the IEEE copyright policy (available at http://www.ieee.org/web/publications/rights/copyrightpolicy.html)
  • the use of articles under ACM copyright is governed by the ACM copyright policy (available at http://www.acm.org/pubs/copyright_policy/)
  • technical reports and other articles issued by M‰lardalen University is free for personal use. For other use, the explicit consent of the authors is required
  • in other cases, please contact the copyright owner for detailed information

By accepting I agree to acknowledge and respect the rights of the copyright owner of the document I am about to access.

If you are in doubt, feel free to contact webmaster@ide.mdh.se

Handling Uncertainty in Automatically Generated Implementation Models in the Automotive Domain

Fulltext:


Publication Type:

Conference/Workshop Paper

Venue:

42nd Euromicro Conference series on Software Engineering and Advanced Applications


Abstract

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.

Bibtex

@inproceedings{Bucaioni4362,
author = {Alessio Bucaioni and Antonio Cicchetti and Federico Ciccozzi and Saad Mubeen and Mikael Sj{\"o}din and Alfonso Pierantonio},
title = {Handling Uncertainty in Automatically Generated Implementation Models in the Automotive Domain},
month = {September},
year = {2016},
booktitle = {42nd Euromicro Conference series on Software Engineering and Advanced Applications },
url = {http://www.es.mdh.se/publications/4362-}
}