Book Chapter10.1007/0-387-21513-1_11
The Object Constraint Language (OCL)
Sinan Si Alhir
- 01 Jan 2002
- pp 364-390
133
TL;DR: This chapter provides an introduction to using the Object Constraint Language (OCL) in composing UML models with an introductory understanding of how to use the OCL.
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Abstract: This chapter provides an introduction to using the Object Constraint Language (OCL) in composing UML models. Our goal in this chapter is to gain an introductory understanding of how to use the OCL.
read more
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Citations
Testing vision-based control systems using learnable evolutionary algorithms
Raja Ben Abdessalem,Shiva Nejati,Lionel C. Briand,Thomas Stifter +3 more
- 27 May 2018
TL;DR: This work proposes an automated testing algorithm that builds on learnable evolutionary algorithms that outperforms a baseline evolutionary search algorithm and generates 78% more distinct, critical test scenarios compared to the baseline algorithm.
Investigating the use of analysis contracts to improve the testability of object-oriented code
TL;DR: A thorough case study is run where OCL contracts are defined, instrument them using a commercial tool and assess the benefits and limitations of doing so to support the automated detection of failures and the isolation of faults.
90
A model-driven process for engineering a toolset for a formal method
TL;DR: A model‐driven software process suitable to develop a set of integrated tools around a formal method that exploits concepts and technologies of the Model‐driven Engineering (MDE) approach, such as metamodelling and automatic generation of software artifacts from models.
82
System Architecture Virtual Integration: An Industrial Case Study
Peter H. Feiler,Jörgen Hansson,Dionisio de Niz,Lutz Wrage +3 more
- 01 Nov 2009
TL;DR: The international consortium of aerospace companies with government participation has initiated the System Architecture Virtual Integration program, whose goal is to achieve an affordable solution through a paradigm shift of "integrate then build".
On the interoperability of model-to-model transformation languages
Frédéric Jouault,Ivan Kurtev +1 more
TL;DR: This paper compares several model-to-model transformation languages and proposes a set of heuristics to reason about the problems that must be addressed when translators between languages have to be developed.
51
References
Testing vision-based control systems using learnable evolutionary algorithms
Raja Ben Abdessalem,Shiva Nejati,Lionel C. Briand,Thomas Stifter +3 more
- 27 May 2018
TL;DR: This work proposes an automated testing algorithm that builds on learnable evolutionary algorithms that outperforms a baseline evolutionary search algorithm and generates 78% more distinct, critical test scenarios compared to the baseline algorithm.
Investigating the use of analysis contracts to improve the testability of object-oriented code
TL;DR: A thorough case study is run where OCL contracts are defined, instrument them using a commercial tool and assess the benefits and limitations of doing so to support the automated detection of failures and the isolation of faults.
90
A model-driven process for engineering a toolset for a formal method
TL;DR: A model‐driven software process suitable to develop a set of integrated tools around a formal method that exploits concepts and technologies of the Model‐driven Engineering (MDE) approach, such as metamodelling and automatic generation of software artifacts from models.
82
System Architecture Virtual Integration: An Industrial Case Study
Peter H. Feiler,Jörgen Hansson,Dionisio de Niz,Lutz Wrage +3 more
- 01 Nov 2009
TL;DR: The international consortium of aerospace companies with government participation has initiated the System Architecture Virtual Integration program, whose goal is to achieve an affordable solution through a paradigm shift of "integrate then build".
Uncertainty-wise test case generation and minimization for Cyber-Physical Systems
TL;DR: This work proposes a set of uncertainty-wise test case generation and test case minimization strategies that rely on test ready models explicitly specifying subjective uncertainty, and proposes a novel methodology for designing and introducing indeterminacy sources in the environment during test execution.
49