6533b82bfe1ef96bd128e163

RESEARCH PRODUCT

Knowledge-based verification of concatenative programming patterns inspired by natural language for resource-constrained embedded devices

Gloria MartorellaSalvatore GaglioDaniele PeriGiuseppe Lo Re

subject

Computer scienceinternet of thing02 engineering and technologycomputer.software_genrelcsh:Chemical technologyBiochemistryOracleArticleAnalytical ChemistryDomain (software engineering)Softwarewireless sensor network0202 electrical engineering electronic engineering information engineeringlcsh:TP1-1185Electrical and Electronic Engineeringdistributed programmingwireless sensor networksEmbedded systemInstrumentationAbstraction (linguistics)concatenative languagessymbolic programmingSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniSymbolic programmingProgramming languagebusiness.industryRuntime verification020206 networking & telecommunications020207 software engineeringcomputer.file_formatforthinternet of thingsAtomic and Molecular Physics and Opticsconcatenative languageProgramming patternsembedded systemsExecutablebusinesscomputerNatural language

description

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.

10.3390/s21010107http://hdl.handle.net/10447/462057