DocumentCode
155171
Title
Exploring Model-Based Repositories for a Broad Range of Industrial Applications and Challenges
Author
Tao Yue ; Ali, Shady ; Descour, Arnaud ; Qitao Gan ; Liaaen, Marius ; Merkesvik, Geir Magne ; Nielsen, Boas Krogh ; Nygard, Jan ; Olafsen, Bjorn Ove ; Waal, Anne Lise
Author_Institution
Simula Res. Lab., Lysaker, Norway
fYear
2014
fDate
2-3 Oct. 2014
Firstpage
37
Lastpage
46
Abstract
Nowadays, systems are becoming increasingly complex and large and the process of developing such large-scale systems is becoming complicated with high cost and enormous effort required. Such a complicated process has a prominent challenge to ensure the quality of delivered artifacts. Therefore there is clearly a need to facilitate reuse of developed artifacts (e.g., requirements, architecture, tests) and enable automated analyses such as risk analyses, prioritizing test cases, change impact analysis, with the objective to reduce cost, effort and improve quality. Model-based engineering provides a promising mechanism to facilitate reuse and enable automation. The key idea is to use models as the backbone of structuring repositories that contain reusable artifacts (e.g., test cases, requirements). Such a backbone model is subse-quently used to enable various types of automation such as model-based testing and automated rule verification. In this paper, we report 12 industrial projects from five different industry domains that all require the construction of model-based repositories to enable various types of automation. We believe using models as the backbone to structure repositories for the purpose of enabling different types of automation in different contexts is a new and non-conventional model-based development research approach. This exploratory paper will serve the basis for future research to derive a generic model-based repository.
Keywords
formal verification; program testing; software quality; automated rule verification; large-scale system; model-based engineering; model-based repository; model-based testing; risk analysis; Analytical models; Automation; Cancer; Optimization; Testing; Training; Unified modeling language; Analysis; Automation; Backbone Model; Generation; Model-based Repository; Model-based Repository Engineering; Optimization;
fLanguage
English
Publisher
ieee
Conference_Titel
Quality Software (QSIC), 2014 14th International Conference on
Conference_Location
Dallas, TX
ISSN
1550-6002
Print_ISBN
978-1-4799-7197-8
Type
conf
DOI
10.1109/QSIC.2014.18
Filename
6958385
Link To Document