4.6 Article

Knowledge-Based Verification of Concatenative Programming Patterns Inspired by Natural Language for Resource-Constrained Embedded Devices

期刊

SENSORS
卷 21, 期 1, 页码 -

出版社

MDPI
DOI: 10.3390/s21010107

关键词

embedded systems; wireless sensor networks; internet of things; symbolic programming; distributed programming; concatenative languages; forth

资金

  1. Crowdsense Project-PO FESR Sicilia [08PA000PA90190, PRJ-0343, CUP: G29J18000740007]

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This methodology proposes a programming pattern inspired by natural language to verify applications interacting with physical environments, reducing the need for ontologies and encouraging the adoption of symbolic code execution on resource-constrained devices. The rule-based system supports real-time verification of software under test on target devices, evaluating the effects of SUT execution on hardware, and generating test code to highlight potential software issues that may arise during repeated execution.
We propose a methodology to verify applications developed following programming patterns inspired by natural language that interact with physical environments and run on resource-constrained interconnected devices. Natural language patterns allow for the reduction of intermediate abstraction layers to map physical domain concepts into executable code avoiding the recourse to ontologies, which would need to be shared, kept up to date, and synchronized across a set of devices. Moreover, the computational paradigm we use for effective distributed execution of symbolic code on resource-constrained devices encourages the adoption of such patterns. The methodology is supported by a rule-based system that permits runtime verification of Software Under Test (SUT) on board the target devices through automated oracle and test case generation. Moreover, verification extends from syntactic and semantic checks to the evaluation of the effects of SUT execution on target hardware. Additionally, by exploiting rules tying sensors and actuators to physical quantities, the effects of code execution on the physical environment can be verified. The system is also able to build test code to highlight software issues that may arise during repeated SUT execution on the target hardware.

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