A Model-Based Testing Framework for Automotive Embedded Systems

Marinescu, Raluca; Saadatmand, Mehrdad; Bucaioni, Alessio; Seceleanu, Cristina; Pettersson, Paul

doi:10.1109/seaa.2014.70

Cited by 18 publications

(10 citation statements)

References 17 publications

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“…Here, due to space limitation, we only report some similar work applying verification and testing in a similar context: [22,25] provide an integrated methodology for formal verification and model-based testing of automotive embedded systems. The authors introduce an architectural description language that is supported by timed-automata based verification and modelbased testing against functional requirements.…”

Section: System Modelling Methodsmentioning

confidence: 99%

Towards an Integrated Approach to Verification and Model-Based Testing in System Engineering

Lefticaru

Konur

Yildirim

et al. 2017

2017 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and I

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Section: System Modelling Methodsmentioning

confidence: 99%

Towards an Integrated Approach to Verification and Model-Based Testing in System Engineering

Lefticaru

Konur

Yildirim

et al. 2017

2017 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and I

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“…The Brake-by-Wire (BBW) system is a hard real-time controller for automobiles [33]. Recently, many researchers explore the BBW as case studies for code validation [34], resource usage [35], requirements verification [36] and testing [33]. In this paper, the BBW system is an executable jar file developed by Feng et al [33] and the requirements are described as natural languages.…”

Section: A Bbw Systemmentioning

confidence: 99%

Control of Black-Box Embedded Systems by Integrating Automaton Learning and Supervisory Control Theory of Discrete-Event Systems

Zhang

Feng

2020

IEEE Trans. Automat. Sci. Eng.

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The paper presents an approach to the control of black-box embedded systems by integrating automaton learning and supervisory control theory (SCT) of discrete-event systems (DES), where automaton models of both the system and requirements are unavailable or hard to obtain. First, the system is tested against the requirements. If all the requirements are satisfied, no supervisor is needed and the process terminates. Otherwise, a supervisor is synthesized to enforce the system to satisfy the requirements. To apply SCT and automaton learning technologies efficiently, the system is abstracted to be a finite-discrete model. Then, a C * learning algorithm is proposed based on the classical L * algorithm to infer a Moore automaton describing both the behavior of the system and the conjunctive behavior of the system and the requirements. Subsequently, a supervisor for the system is derived from the learned Moore automaton and patched on the system. Finally, the controlled system is tested again to check the correctness of the supervisor. If the requirements are still not satisfied, a larger Moore automaton is learned and a refined supervisor is synthesized. The whole process iterates until the requirements hold in the controlled system. The effectiveness of the proposed approach is manifested through two realistic case studies. Note to Practitioners-Supervisory control theory of DES can synthesize maximally permissive supervisory controllers to ensure the correctness of software-controlled processes. The applicationManuscript of supervisory control theory relies on automaton models of the plant and specifications; however, the required models are often unavailable and difficult to obtain for black-box embedded systems. Automaton learning is an effective method for inferring models of black-box systems. This paper integrates the two technologies so that the supervisory control theory is applicable to the development of black-box embedded software systems. The proposed approach is implemented in a toolchain that connects automaton learning algorithms, SCT, and testing algorithms via scripts. The obtained supervisor is implemented as a software patch to monitor and control the original system online.Index Terms-Automaton learning algorithm, black-box embedded system, software testing, supervisory control theory.

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“…Testing software based on extra-functional properties at the architectural level has received less attention [7,[36][37][38][39][40] than the functional testing of such models. In our previous work [7], we explored the use of statistical model checking for analysis and performance testing of EAST-ADL models and used manually injected faults to measure test effectiveness.…”

Section: Related Workmentioning

confidence: 99%

Model Testing of Complex Embedded Systems Using EAST-ADL and Energy-Aware Mutations

Enoiu

Seceleanu

2020

Designs

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Nowadays, embedded systems are increasingly complex, meaning that traditional testing methods are costly to use and infeasible to directly apply due to the complex interactions between hardware and software. Modern embedded systems are also demanded to function based on low-energy computing. Hence, testing the energy usage is increasingly important. Artifacts produced during the development of embedded systems, such as architectural descriptions, are beneficial abstractions of the system’s complex structure and behavior. Electronic Architecture and Software Tools Architecture Description Language (EAST-ADL) is one such example of a domain-specific architectural language targeting the automotive industry. In this paper, we propose a method for testing design models using EAST-ADL architecture mutations. We show how fault-based testing can be used to generate, execute and select tests using energy-aware mutants—syntactic changes in the architectural description, used to mimic naturally occurring energy faults. Our goal is to improve testing of complex embedded systems by moving the testing bulk from the actual systems to models of their behaviors and non-functional requirements. We combine statistical model-checking, increasingly used in quality assurance of embedded systems, with EAST-ADL architectural models and mutation testing to drive the search for faults. We show the results of applying this method on an industrial-sized system developed by Volvo GTT. The results indicate that model testing of EAST-ADL architectural models can reduce testing complexity by bringing early and cost-effective automation.

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A Model-Based Testing Framework for Automotive Embedded Systems

Cited by 18 publications

References 17 publications

Towards an Integrated Approach to Verification and Model-Based Testing in System Engineering

Towards an Integrated Approach to Verification and Model-Based Testing in System Engineering

Control of Black-Box Embedded Systems by Integrating Automaton Learning and Supervisory Control Theory of Discrete-Event Systems

Model Testing of Complex Embedded Systems Using EAST-ADL and Energy-Aware Mutations

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