2020 IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW) 2020
DOI: 10.1109/issrew51248.2020.00040
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Instrumenting Compiler Pipeline to Synthesise Traceable Runtime Memory Layouts in Mixed-critical Applications

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Cited by 2 publications
(3 citation statements)
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“…In short, accurate selection and classification of software elements can help to achieve better coverage of safety measures that operate on data/memory. This work is based on our original paper [Kajtazović et al, 2020] and extends it as follows:…”
Section: Methods and Contributionsmentioning
confidence: 99%
See 1 more Smart Citation
“…In short, accurate selection and classification of software elements can help to achieve better coverage of safety measures that operate on data/memory. This work is based on our original paper [Kajtazović et al, 2020] and extends it as follows:…”
Section: Methods and Contributionsmentioning
confidence: 99%
“…As pointed out by Brauer et al [Brauer et al, 2015], representation of the software behaviour in runtime memory differs to what we have in the source code. More specifically, as we've shown in our previous work [Kajtazović et al, 2020], that compilers may, in the course of the compilation process, create various housekeeping data and managing code which are part of the software runtime environment for our RTOS, applications. These artefacts are interlinked with the rest of software in a way that, in some situations, correct functioning of the overall system may depend on their integrity.…”
Section: Problem Statementmentioning
confidence: 99%
“…Using this approach, we can optimize resource utilization, making this pattern more suitable for implementation in a microcontroller environment. To optimize the implementation of this pattern, using both memory and computational performance, we will not use run-time-type information (RTTI) in the implementation [18][19][20]. RTTI is a mechanism that allows us to obtain data-type information at run-time.…”
Section: Dependency Inversion Principlementioning
confidence: 99%