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Artifacts for the evaluation of the paper In-Vivo Stack Overflow Detection and Stack Size Estimation for Low-End Multithreaded Operating Systems using Virtual Prototypes which will be published as part of FDL21. The artifacts provided here use pre-compiled binaries and pre-generated stack usage databases. Based on these provided files, the stack size estimation and performance evaluation performed in the paper can be replicated. Various README.md files, which provide more information on individual artifacts, are also included. The software used in conjunction with these artifacts is also freely available on GitHub: https://github.com/agra-uni-bremen/fdl21-stackuse-vp https://github.com/agra-uni-bremen/stack-usage-db
memory usage, stack overflows, RISC-V, constrained devices, virtual prototypes, internet of things, RIOT
memory usage, stack overflows, RISC-V, constrained devices, virtual prototypes, internet of things, RIOT
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 1 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
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