Multi-objectives Refinement of AADL Models for the Synthesis Embedded Systems (mu-RAMSES)

Rahmoun, Smail; Borde, Étienne; Pautet, Laurent

doi:10.1109/iceccs.2015.13

Cited by 5 publications

(2 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…forward engineering). For instance, OCARINA [11] and RAMSES [12] support automatic code generation from AADL to C, Ada and Java. Regarding the reverse generation of AADL models, Wang et al [13] propose an approach 75 for extracting AADL models from existing embedded software in order to reduce maintenance costs.…”

Section: Research Problemsmentioning

confidence: 99%

C2AADL_Reverse: A Model-Driven Reverse Engineering Approach for Development and Verification of Safety-Critical Software

Yang,

Qiu,

Zhou

et al. 2023

Ada Lett.

View full text Add to dashboard Cite

The safety-critical system communities have been struggling to manage and maintain their legacy software systems because upgrading such systems has been a complex challenge. To overcome or reduce this problem, reverse engineering has been increasingly used in safety-critical systems. This paper proposes C2AADL_Reverse, a model-driven reverse engineering approach for safety-critical software development and verification. C2AADL_Reverse takes multi-task C source code as input, and generates AADL (Architecture Analysis and Design Language) model of the legacy software systems. Compared with the existing works, this paper considers more reversed construction including AADL component structure, behavior, and multi-threaded run-time information. Moreover, two types of activities are proposed to ensure the correctness of C2AADL_Reverse. First, it is necessary to validate the reverse engineering process. Second, the generated AADL models should conform to desired critical properties. We propose the verification of the reverse-engineered AADL model by using UPPAAL to establish component-level properties and the Assume Guarantee REasoning Environment (AGREE) to perform compositional verification of the architecture. This combination of verification tools allows us to iteratively explore design and verification of detailed behavioral models, and to scale formal analysis to large models. In addition, the prototype tool and the evaluation of C2AADL_Reverse using a real-world aerospace case study are presented.

show abstract

Section: Research Problemsmentioning

confidence: 99%

C2AADL_Reverse: A Model-Driven Reverse Engineering Approach for Development and Verification of Safety-Critical Software

Yang,

Qiu,

Zhou

et al. 2023

Ada Lett.

View full text Add to dashboard Cite

show abstract

“…The approach has been prototyped for AADL models refined with the RAMSES tool and model transformations implemented as story diagrams. In [74], Rahmoun et al proposed an approach that automates the identification of model transformation alternatives (MTAs) taking into account their dependencies, and selections of MTAs based on evolutionary algorithms that produce the best output models with respect to nonfunctional properties.…”

Section: Model Refinementmentioning

confidence: 99%

An Approach to Generate the Traceability Between Restricted Natural Language Requirements and AADL Models

Wang¹,

Yang²,

Huang³

et al. 2020

IEEE Trans. Rel.

View full text Add to dashboard Cite

Requirements traceability is broadly recognized as a critical element of any rigorous software development process, especially for building safety-critical software (SCS) systems. Modeldriven development (MDD) is increasingly used to develop SCS in many domains, such as automotive and aerospace. MDD provides new opportunities for establishing traceability links through modeling and model transformations. Architecture Analysis and Design Language (AADL) is a standardized architecture description language for embedded systems, which is widely used in avionics and aerospace industries to model safety-critical applications. However, there is a big challenge to automatically establish the traceability links between requirements and AADL models in the context of MDD, because requirements are mostly written as free natural language texts, which are often ambiguous and difficult to be processed automatically. To bridge the gap between natural language requirements (NLRs) and AADL models, we propose an approach to generate the traceability links between NLRs and AADL models. First, we propose a requirement modeling method based on the restricted natural language, which is named as RM-RNL. The RM-RNL can eliminate the ambiguity of NLRs and barely change engineers' habits of requirement specification. Second, we present a method to automatically generate the initial AADL models from the RM-RNLs and to automatically establish traceability links between the elements of the RM-RNL and the generated AADL models. Third, we refine the initial AADL models through patterns to achieve the change of requirements and traceability links. Finally, we demonstrate the effectiveness of our approach with industrial case studies and evaluation experiments.

show abstract

Multi-objective design exploration approach for Ravenscar real-time systems

et al. 2018

View full text Add to dashboard Cite

Multi-objectives Refinement of AADL Models for the Synthesis Embedded Systems (mu-RAMSES)

Cited by 5 publications

References 15 publications

C2AADL_Reverse: A Model-Driven Reverse Engineering Approach for Development and Verification of Safety-Critical Software

C2AADL_Reverse: A Model-Driven Reverse Engineering Approach for Development and Verification of Safety-Critical Software

An Approach to Generate the Traceability Between Restricted Natural Language Requirements and AADL Models

Multi-objective design exploration approach for Ravenscar real-time systems

Contact Info

Product

Resources

About