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

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...

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Bibliographic Details
Published in:Sensors (Basel, Switzerland) Switzerland), 2020-12, Vol.21 (1), p.107
Main Authors: Gaglio, Salvatore, Lo Re, Giuseppe, Martorella, Gloria, Peri, Daniele
Format: Article
Language:English
Subjects:
Actuators
Automation
Building codes
concatenative languages
distributed programming
Embedded systems
Internet of Things
Investigations
Java
Language
Natural language
Operating systems
Semantics
Software
symbolic programming
Verification
wireless sensor networks
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Summary: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.
ISSN:1424-8220
1424-8220
DOI:10.3390/s21010107