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Dynamic and execution views to improve validation, testing, and optimization of autonomous driving software

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10.1007/s11219-022-09609-x
 
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hdl:2117/384775

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Alcón Doganoc, MiguelMés informació
Tabani, Hamid
Abella Ferrer, JaumeMés informació
Cazorla Almeida, Francisco Javier
Document typeArticle
Defense date2023-06
PublisherSpringer Nature
Rights accessOpen Access
All rights reserved. This work is protected by the corresponding intellectual and industrial property rights. Without prejudice to any existing legal exemptions, reproduction, distribution, public communication or transformation of this work are prohibited without permission of the copyright holder
Abstract
The adoption of autonomous driving (AD) software executed on high-performance multi-processor systems on chip (MPSoCs) contributes to increasing the overall system’s safety and efficiency. However, existing AD software frameworks are provided as complete implementations that do not follow any domain-specific safety-requirement centric development process. In this paper, we develop, for the first time, ISO 26262 dynamic views of a representative AD framework, Apollo. Dynamic views are a key element of software architectural design that links safety software requirements with their implementation, and are the basis to verify that all casuistics are properly considered in the design and tested in the validation tests. We also show that dynamic views miss key information of the execution parallelism of Apollo, needed to assess and improve execution efficiency to meet performance-related safety requirements and reduce resource utilization. We cover this gap by proposing execution views that capture the parallelism exploited by the analyzed application on the target MPSoC. Execution views improve greatly resource usage testing, which is required by ISO 26262, and allow better resource utilization contributing to the stringent cost-reduction requirements in automotive domains
CitationAlcón, M. [et al.]. Dynamic and execution views to improve validation, testing, and optimization of autonomous driving software. "Software quality journal", Juny 2023, vol 31, núm. 2, p. 405-439. 
URIhttp://hdl.handle.net/2117/384775
DOI10.1007/s11219-022-09609-x
ISSN1573-1367
Publisher versionhttps://link.springer.com/article/10.1007/s11219-022-09609-x
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  • Computer Sciences - Articles de revista [360]
  • Doctorat en Arquitectura de Computadors - Articles de revista [202]
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