Synthesis of self-adaptable energy aware software for heterogeneous multicore embedded systems

2021 ◽  
Vol 123 ◽  
pp. 114184
Author(s):  
Stanisław Deniziak ◽  
Leszek Ciopiński
Author(s):  
Luca Santinelli ◽  
Mauro Marinoni ◽  
Francesco Prosperi ◽  
Francesco Esposito ◽  
Gianluca Franchino ◽  
...  

Designs ◽  
2020 ◽  
Vol 4 (1) ◽  
pp. 5
Author(s):  
Eduard Paul Enoiu ◽  
Cristina Seceleanu

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.


Computing ◽  
2015 ◽  
Vol 98 (3) ◽  
pp. 279-301 ◽  
Author(s):  
Guohui Wang ◽  
Yong Guan ◽  
Yi Wang ◽  
Zili Shao

2017 ◽  
Vol 16 (2) ◽  
pp. 1-25 ◽  
Author(s):  
Jing Liu ◽  
Kenli Li ◽  
Dakai Zhu ◽  
Jianjun Han ◽  
Keqin Li

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