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Knowledge-Based Verification of Concatenative Programming Patterns Inspired by Natural Language for
Salvatore Gaglio1,2, Giuseppe Lo Re1, Gloria Martorella1
1Department of Engineering, University of Palermo, Viale delle Scienze, Ed.6, 90128 Palermo, Italy.
This study introduces a new method for verifying natural language-inspired applications on resource-constrained devices. It enables runtime verification and testing of software interacting with physical environments.
Area of Science:
- Computer Science
- Software Engineering
- Embedded Systems
Background:
- Resource-constrained devices require efficient programming paradigms.
- Interacting with physical environments necessitates robust verification methods.
- Traditional verification approaches often struggle with distributed, resource-limited systems.
Purpose of the Study:
- To propose a methodology for verifying applications using natural language-inspired programming patterns.
- To enable runtime verification on resource-constrained interconnected devices.
- To reduce reliance on complex, synchronized ontologies for mapping physical concepts to code.
Main Methods:
- Utilizing natural language programming patterns to map physical concepts directly to executable code.
- Employing a rule-based system for automated oracle and test case generation.
- Performing runtime verification on-board target devices, including syntactic, semantic, and physical effect checks.
- Leveraging sensor and actuator rules to verify code execution impact on the physical environment.
Main Results:
- Successful runtime verification of software under test (SUT) on target hardware.
- Automated generation of test cases and oracles for comprehensive testing.
- Verification of code execution effects on both hardware and the physical environment.
- Identification of potential software issues through repeated execution testing.
Conclusions:
- The proposed methodology effectively verifies applications on resource-constrained devices using natural language-inspired patterns.
- This approach simplifies development by avoiding complex ontology management.
- It enhances the reliability of software interacting with physical systems.

