Literature DB >> 33375337

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

Salvatore Gaglio1,2, Giuseppe Lo Re1, Gloria Martorella1, Daniele Peri1.   

Abstract

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.

Entities:  

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

Year:  2020        PMID: 33375337     DOI: 10.3390/s21010107

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.576


  1 in total

1.  Time-Constrained Node Visit Planning for Collaborative UAV-WSN Distributed Applications.

Authors:  Andrea Augello; Salvatore Gaglio; Giuseppe Lo Re; Daniele Peri
Journal:  Sensors (Basel)       Date:  2022-07-15       Impact factor: 3.847

  1 in total

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