WCET-Aware Partial Control-Flow Checking for Resource-Constrained Real-Time Embedded Systems

2014 ◽  
Vol 61 (10) ◽  
pp. 5652-5661 ◽  
Author(s):  
Zonghua Gu ◽  
Chao Wang ◽  
Ming Zhang ◽  
Zhaohui Wu
IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 42394-42406 ◽  
Author(s):  
Ming Zhang ◽  
Zonghua Gu ◽  
Hong Li ◽  
Nenggan Zheng

Author(s):  
Michael Kramer ◽  
Martin Horauer

Embedded Systems software reliability is increasingly important, therefore methods to harden existing software are needed. In general, hardening software against various failures is a necessity in modern computer systems. A lot of work has been published regarding many possible ways to achieve this non-functional requirement. Relevant topics include, e.g., test procedures, recommended development flows, and hardware measures like watchdog timers. One of these methods seems very promising to be software implemented in modern embedded systems: Control Flow Checking by signatures. Various authors have shown the effectiveness and feasibility of Control Flow Checking (CFC) by signatures for personal computer software. For instance it has been shown for standard computer-systems, that CFC is capable of reducing undetected control flow errors by at least one magnitude. This survey will focus on the applicability of such software hardening methods to embedded systems, while adhering mainly to software based approaches. Published methods will be summarized and compared. Furthermore methods to simplify derived control-flow graphs to essential states will be emphasized. Finally the possibility to apply run-time verification to the Control-flow Checking Software is considered.


Electronics ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 13
Author(s):  
Balaji M ◽  
Chandrasekaran M ◽  
Vaithiyanathan Dhandapani

A Novel Rail-Network Hardware with simulation facilities is presented in this paper. The hardware is designed to facilitate the learning of application-oriented, logical, real-time programming in an embedded system environment. The platform enables the creation of multiple unique programming scenarios with variability in complexity without any hardware changes. Prior experimental hardware comes with static programming facilities that focus the students’ learning on hardware features and programming basics, leaving them ill-equipped to take up practical applications with more real-time constraints. This hardware complements and completes their learning to help them program real-world embedded systems. The hardware uses LEDs to simulate the movement of trains in a network. The network has train stations, intersections and parking slots where the train movements can be controlled by using a 16-bit Renesas RL78/G13 microcontroller. Additionally, simulating facilities are provided to enable the students to navigate the trains by manual controls using switches and indicators. This helps them get an easy understanding of train navigation functions before taking up programming. The students start with simple tasks and gradually progress to more complicated ones with real-time constraints, on their own. During training, students’ learning outcomes are evaluated by obtaining their feedback and conducting a test at the end to measure their knowledge acquisition during the training. Students’ Knowledge Enhancement Index is originated to measure the knowledge acquired by the students. It is observed that 87% of students have successfully enhanced their knowledge undergoing training with this rail-network simulator.


2018 ◽  
Vol 53 (4) ◽  
pp. 543-556 ◽  
Author(s):  
Simon Moll ◽  
Sebastian Hack
Keyword(s):  

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