A methodology for evaluating the functional dependability of the components of an embedded software and hardware microprocessor-based control system

Aim. To analyse the dependability terminology as regards embedded software and hardware systems, to develop a methodology for assessing the functional dependability of the components of embedded software and hardware computer-based control systems, and to conduct a practical assessment of the dependability of the modern software and hardware components of embedded computers and microcontrollers for the purpose of selecting the optimal control system architecture. A prototype medical robot intended for holding surgical instruments, Farabeuf retractors, etc. is used as the controllable object. The robotics system includes a microprocessor unit based on a common single-board computer that implements high-level control and voice command recognition functions, an additional microprocessor unit for controlling servo drives and receiving input signals, as well as the actuating modules, i.e., drives. Methods. The paper uses reference source analysis, analyses non-peer-reviewed collections of documents, previously restricted foreign standards and publications. Results. The author presents a method for assessing the functional dependability of the components of an embedded software and hardware control system. The probability of no failure of software and hardware components of the examined system was calculated based on statistical estimates and on the amount of code. Despite the different calculation methods and reference data, the results are generally close. The paper also estimated the probability of no software failure for an alternative control system architecture, whereas a part of important functions is shared with an additional software and hardware unit having a higher level of dependability. In this case, such is an Atmega32 microcontroller that is to directly control the drives. A comparative analysis of the results shows that the additional level with partially parallelised functions and partial control channel redundancy significantly improved the assessment of the system’s probability of no failure under predefined conditions. Based on the calculated data, the paper defines a control system architecture with two system levels that has high values of probability of no failure. Conclusion. Given the trend of growing numbers of functions being integrated within a single microprocessor-based system, improved functional dependability should be achieved through a two-level functional architectural solution, whereas the key tasks in terms of direct interaction with the hardware environment are redistributed in favour of a separate hardware module. Additionally, as regards embedded systems, such an approach often allows defining a lower, real-time system layer and an upper system layer that is responsible for highlevel functions such as speech recognition, data communication via interfaces, and artificial intelligence. The matter of practical evaluation of embedded software dependability is not yet completely resolved. Such software is characterised by the lack of virtualisation and a level of hardware abstraction, which, in turn, causes a close relationship with the hardware and peripherals. Obviously, repeating the required tests is not enough. Test combinations should include external hardware effects (signal level anomalies) and software effects on the periphery of a microcontroller.

1. Deepa V.V., Thamotharan B., Mahto D. et al. Smart embedded health monitoring system and secure electronic health record (EHR) transactions using blockchain technology. SoftComput 2023;27:12741–12756. DOI: 10.1007/s00500-023-08893-4.

2. Siraj I., Bharti P.S. Reliability analysis of a 3D Printing process. Procedia Computer Science 2020;173:191-200. DOI: 10.1016/j.procs.2020.06.023.

3. Shubinsky I.B., Schäbe H. On the definition of functional reliability. RT&A 2012;4(27). (accessed 12.08.2024). Available at: https://cyberleninka.ru/article/n/on-the-definition-of-functional-reliability.

4. Burgazzi L. Reliability Evaluation of Passive Systems Through Functional Reliability Assessment. Nuclear Technology 2003;144. DOI: 10.13182/NT144-145.

5. Shubinsky I.B. [Structural dependability of information systems. Analysis methods]. Moscow: Dependability Journal; 2012. (in Russ.)

6. Yershov G.A., Semerikov V.N., Semerikov N.V. [What to believe? On the system of standards “Dependability in engineering”]. Standarty i kachestvo 2018;8:14-19. (in Russ.)

7. Netes V.А. [How to regain trust? About the system of standards “Dependability in engineering”]. Standarty i kachestvo 2019;2:19-24. (in Russ.)

8. Potapov I.V., Baeva M.A. Terminology issues related to reliability of programs and software. Dependability 2015;(4):65-74. DOI: 10.21683/1729-2646-2015-0-465-74.

9. Shubinsky I.B. Methods of software functional dependability assurance. Dependability 2014;(4):87-101. DOI: 10.21683/1729-2646-2014-0-4-87-101.

10. Netes V.A. Item in dependability: definition and content of the concept. Dependability 2019;19(4):3-7. DOI: 10.21683/1729-2646-2019-19-4-3-7.

11. Klimov S.M., Sosnovsky Yu.V. Method of assessing the protection of computer-based control systems under information technology interference. Dependability 2018; 18(4):36-44. DOI: 10.21683/1729-1729-26462018-18-4-44.

12. Kapur K., Lamberson L. Ushakov I.A., editor. Reliability in Engineering Design. Moscow: Mir; 1980.

13. Burenok V.M., Tyulin A.E., editors. [Systematic substantiation of the conceptual provisions of the application of advanced space technologies]. Moscow: Innovatsionnoye mashinostroyeniye; 2023. (in Russ.)

14. Littlewood B., Strigini L. Validation of Ultra-High Dependability for Software-based Systems. Commun. ACM 1993;36:69-80. DOI: 10.1145/163359.163373.

15. Belov A.S., Dobrynin M.M., Gorshkov A.A., Shugurov D.E. Proposal for determining the operational reliability of software complex technical systems. News of the Tula state university. Technical sciences 2022;9:143-148. DOI: 10.24412/2071-6168-2022-9-143-148. (in Russ.)

16. Ivutin A.N., Suslin A.A. Some remarkable appliances of statistical distributions in software reliability estimation. News of the Tula state university. Technical sciences 2011;2:568-575. (in Russ.)